diff --git a/.gitignore b/.gitignore
index d2fed56..0943a8b 100644
--- a/.gitignore
+++ b/.gitignore
@@ -28,8 +28,14 @@ dpnegf/negf/check.ipynb
 dpnegf/tests/data/test_negf/show.ipynb
 dpnegf/tests/data/test_tbtrans/show.ipynb
 # tutorial files
-dpnegf/examples/graphene/negf_output_k20/self_energy/self_energy_leadL.h5
-dpnegf/examples/graphene/negf_output_k20/self_energy/self_energy_leadR.h5
+examples/graphene/negf_output_k20/self_energy/self_energy_leadL.h5
+examples/graphene/negf_output_k20/self_energy/self_energy_leadR.h5
+examples/hBN/negf_output_k20/self_energy/self_energy_leadL.h5
+examples/hBN/negf_output_k20/self_energy/self_energy_leadR.h5
+examples/hBN/negf_output_k50/self_energy/*
+examples/hBN/negf_output_k70/self_energy/*
+
+
 
 run_config.json
 dpnegf/nnet/__pycache__/
diff --git a/docs/hands_on/index.rst b/docs/hands_on/index.rst
index 7591743..a783fbc 100644
--- a/docs/hands_on/index.rst
+++ b/docs/hands_on/index.rst
@@ -4,3 +4,4 @@ A quick Example
 
 .. toctree::
    tutorial1_c_chain
+   tutorial2_2d_mat
diff --git a/docs/hands_on/tutorial2_2d_mat.ipynb b/docs/hands_on/tutorial2_2d_mat.ipynb
index d8b089f..06d0c13 100644
--- a/docs/hands_on/tutorial2_2d_mat.ipynb
+++ b/docs/hands_on/tutorial2_2d_mat.ipynb
@@ -53,7 +53,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 3,
    "id": "026e2584",
    "metadata": {},
    "outputs": [
@@ -61,7 +61,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "POSCAR\tband.json\tband_plot\tband_plot_api\textra_baseline\tnegf.json\tnegf_output\tnegf_output_k100\tnegf_output_k20\tnegf_output_k50\tstru_negf.xyz\tstruct.xyz\ttrain\n"
+      "band.json\tband_plot_api\textra_baseline\tnegf.json\tnegf_output\tnegf_output_k100\tnegf_output_k20\tstru_negf.xyz\tstruct.xyz\ttrain\n"
      ]
     }
    ],
@@ -90,13 +90,7 @@
       "DPNEGF INFO                                      Version Info                                  \n",
       "DPNEGF INFO    --------------------------------------------------------------------------------\n",
       "DPNEGF INFO    DPNEGF               : 0.1.1.dev148+0e0863a\n",
-      "DPNEGF INFO    DeePTB               : 2.1.2.dev53+5b97981\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
+      "DPNEGF INFO    DeePTB               : 2.2.1.dev17+024a5fe\n",
       "DPNEGF INFO    ================================================================================\n",
       "\n"
      ]
@@ -208,15 +202,15 @@
       "DPNEGF INFO    KPOINTS  klist: 300 kpoints\n",
       "DPNEGF INFO    The eigenvalues are already in data. will use them.\n",
       "DPNEGF INFO    Calculating Fermi energy in the case of spin-degeneracy.\n",
-      "DPNEGF INFO    Fermi energy converged after 21 iterations.\n",
-      "DPNEGF INFO    q_cal: 7.99999860016806, total_electrons: 8.0, diff q: 1.3998319401409276e-06\n",
-      "DPNEGF INFO    Estimated E_fermi: -3.582991372133437 based on the valence electrons setting nel_atom : {'C': 4} .\n",
+      "DPNEGF WARNING Fermi level bisection did not converge under tolerance 1e-10 after 57 iterations.\n",
+      "DPNEGF INFO    q_cal: 7.9999999708937874, total_electrons: 8.0, diff q: 2.910621255125534e-08\n",
+      "DPNEGF INFO    Estimated E_fermi: -3.5829840898513794 based on the valence electrons setting nel_atom : {'C': 4} .\n",
       "DPNEGF INFO    No Fermi energy provided, using estimated value: -3.5830 eV\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x560 with 1 Axes>"
       ]
@@ -259,6 +253,14 @@
     "               ref_band = task_options['ref_band'],)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "b1cec023",
+   "metadata": {},
+   "source": [
+    "The DFT band structure demonstrates excellent agreement with the DeePTB model. Critically, the model accurately reproduces the hallmark electronic features of graphene. The Fermi level  is correctly positioned at the Dirac point, located at the K high-symmetry point of the Brillouin zone. The linear dispersion near this point, forming the characteristic Dirac cone, is clearly visible and matches the reference data precisely."
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "cca83808",
@@ -277,7 +279,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "id": "558867cd",
    "metadata": {},
    "outputs": [
@@ -321,7 +323,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 7,
    "id": "1c95296d",
    "metadata": {},
    "outputs": [
@@ -393,7 +395,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 8,
    "id": "ceffb8de",
    "metadata": {},
    "outputs": [
@@ -424,7 +426,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 9,
    "id": "4322d59f",
    "metadata": {},
    "outputs": [
@@ -447,7 +449,7 @@
        "  'useBloch': False}}"
       ]
      },
-     "execution_count": 20,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -467,7 +469,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 10,
    "id": "5c9f9038",
    "metadata": {},
    "outputs": [
@@ -591,7 +593,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 11,
    "id": "4aef7816",
    "metadata": {},
    "outputs": [],
@@ -606,7 +608,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 12,
    "id": "8cb138b4",
    "metadata": {},
    "outputs": [
@@ -616,7 +618,7 @@
        "dict_keys(['k', 'wk', 'uni_grid', 'DOS', 'T_k', 'LDOS', 'T_avg'])"
       ]
      },
-     "execution_count": 23,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -627,13 +629,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 13,
    "id": "b5fd4d8f",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -660,7 +662,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 14,
    "id": "f1f6ee6b",
    "metadata": {},
    "outputs": [],
@@ -682,7 +684,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 15,
    "id": "e058e426",
    "metadata": {},
    "outputs": [
@@ -888,7 +890,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": null,
    "id": "f98b0fe4",
    "metadata": {},
    "outputs": [
@@ -913,6 +915,7 @@
     "plt.plot(negf_out['uni_grid'], negf_out['T_avg'])\n",
     "plt.xlabel('Energy (eV)')\n",
     "plt.title('Total Transmission kmesh=[1,20,1]')\n",
+    "plt.xlim(-10,10)\n",
     "plt.grid()\n",
     "plt.show()"
    ]
@@ -927,13 +930,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 5,
    "id": "0d4308ff",
    "metadata": {},
    "outputs": [],
    "source": [
     "import numpy as np\n",
     "import matplotlib.pyplot as plt\n",
+    "import torch\n",
     "output = 'negf_output_k100'\n",
     "results_path = os.path.join(output, 'negf.out.pth')\n",
     "if os.path.exists(results_path) is False:\n",
@@ -944,7 +948,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 6,
    "id": "bc38754a",
    "metadata": {},
    "outputs": [],
@@ -956,13 +960,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "id": "43609801",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -977,7 +981,1586 @@
     "plt.xlabel('Energy (eV)')\n",
     "plt.title('Total Transmission')\n",
     "plt.grid()\n",
-    "plt.legend()\n",
+    "plt.legend(loc='upper center')\n",
+    "plt.xlim(-10,10)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "caed4ce0",
+   "metadata": {},
+   "source": [
+    "The transmission spectra further validate the model's accuracy for transport simulations. The initial Gamma-point calculation shows integer plateaus in the transmission, which is characteristic of ballistic transport in one-dimensional channels. However, to capture the full picture of 2D transport, a summation over the transverse k-points is necessary. The final plot, which compares the total transmission from DeePTB-NEGF with that from a full DFT-NEGF calculation, shows remarkable consistency. Both methods produce the distinctive V-shaped transmission spectrum around the Fermi level, a direct consequence of graphene's linear density of states. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "23585f4d",
+   "metadata": {},
+   "source": [
+    "## 2. Quantum Transport in hBN\n",
+    "\n",
+    "Here we extend DPNEGF's application to **hBN** illustrating its capability to various materials.\n",
+    "\n",
+    "For simpilicy, we have prepared a model in `example/hBN/train/`. Users can just run the same commands above to repeat the procedures."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "348a915c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "DPNEGF INFO    ================================================================================\n",
+      "DPNEGF INFO                                      Version Info                                  \n",
+      "DPNEGF INFO    --------------------------------------------------------------------------------\n",
+      "DPNEGF INFO    DPNEGF               : 0.1.1.dev148+0e0863a\n",
+      "DPNEGF INFO    DeePTB               : 2.2.1.dev17+024a5fe\n",
+      "DPNEGF INFO    ================================================================================\n",
+      "\n",
+      "DPNEGF INFO    The ['overlap_param'] are frozen!\n",
+      "DPNEGF INFO    The ['overlap_param'] are frozen!\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "band.json\tband_plot_api\textra_baseline\tnegf.json\tnegf_output_k20\tnegf_output_k70\tsiesta.TBT.AVTRANS_Left-Right\tsiesta.TBT.nc\tstru_negf.xyz\ttrain\n",
+      "Atoms(symbols='NB', pbc=True, cell=[[2.5039999485, 0.0, 0.0], [-1.2519999743, 2.1685275665, 0.0], [0.0, 0.0, 30.0]])\n"
+     ]
+    }
+   ],
+   "source": [
+    "import os\n",
+    "from pathlib import Path\n",
+    "from dptb.nn.build import build_model\n",
+    "from ase.io import read\n",
+    "from dpnegf.utils.loggers import set_log_handles\n",
+    "import logging\n",
+    "from pathlib import Path\n",
+    "\n",
+    "\n",
+    "workdir='../../examples/hBN'\n",
+    "wd = Path(workdir)\n",
+    "if not wd.is_dir():\n",
+    "    raise FileNotFoundError(f\"Workdir '{wd}' not found. Please adjust 'workdir'.\")\n",
+    "os.chdir(wd)\n",
+    "print(\"\\t\".join(sorted(os.listdir(\".\"))))\n",
+    "\n",
+    "results_path = 'band_plot_api'\n",
+    "log_path = os.path.join(results_path, 'log')\n",
+    "log_level = logging.INFO\n",
+    "set_log_handles(log_level, Path(log_path) if log_path else None)\n",
+    "\n",
+    "\n",
+    "model =  \"./train/train_out/checkpoint/nnsk.best.pth\" # the model for demonstration\n",
+    "model = build_model(model)\n",
+    "\n",
+    "# read the structure\n",
+    "structure =  \"./train/data/POSCAR\" \n",
+    "atoms = read(structure)\n",
+    "print(atoms)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1328b585",
+   "metadata": {},
+   "source": [
+    "The band predicted by the model is shown:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "9942e616",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "DPNEGF ERROR   TBPLaS is not installed. Thus the TBPLaS is not available, Please install it first.\n",
+      "/opt/mamba/envs/dpnegf-dev/lib/python3.10/site-packages/torch/nested/__init__.py:107: UserWarning: The PyTorch API of nested tensors is in prototype stage and will change in the near future. (Triggered internally at ../aten/src/ATen/NestedTensorImpl.cpp:178.)\n",
+      "  return torch._nested_tensor_from_tensor_list(ts, dtype, None, device, None)\n",
+      "DPNEGF WARNING eig_solver is not set, using default 'torch'.\n",
+      "DPNEGF INFO    KPOINTS  klist: 300 kpoints\n",
+      "DPNEGF INFO    The eigenvalues are already in data. will use them.\n",
+      "DPNEGF INFO    Calculating Fermi energy in the case of spin-degeneracy.\n",
+      "DPNEGF INFO    Fermi energy converged after 3 iterations.\n",
+      "DPNEGF INFO    q_cal: 7.999999999999999, total_electrons: 8.0, diff q: 8.881784197001252e-16\n",
+      "DPNEGF INFO    Estimated E_fermi: -2.8933583906146634 based on the valence electrons setting nel_atom : {'B': 3, 'N': 5} .\n",
+      "DPNEGF INFO    No Fermi energy provided, using estimated value: -2.8934 eV\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x560 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from dptb.postprocess.bandstructure.band import Band\n",
+    "\n",
+    "\n",
+    "task_options = {\n",
+    "        \"task\": \"band\",\n",
+    "        \"kline_type\":\"abacus\",\n",
+    "        \"kpath\":[\n",
+    "                [0, 0, 0, 110],\n",
+    "                [0.5, 0, 0, 62],\n",
+    "                [0.3333333, 0.3333333, 0, 127],\n",
+    "                [0, 0, 0, 1]\n",
+    "                ],\n",
+    "        \"klabels\":[\"G\", \"M\", \"K\", \"G\"],\n",
+    "        \"emin\":-20,\n",
+    "        \"emax\": 15,\n",
+    "        \"nel_atom\":{\"B\": 3,\n",
+    "                    \"N\": 5},\n",
+    "        \"ref_band\": \"./train/data/kpath.0/eigenvalues.npy\"\n",
+    "\n",
+    "       }\n",
+    "\n",
+    "\n",
+    "\n",
+    "band = Band(model, results_path)\n",
+    "AtomicData_options = { \"pbc\": True}\n",
+    "band.get_bands(data = atoms, \n",
+    "               kpath_kwargs = task_options,\n",
+    "               AtomicData_options = AtomicData_options)\n",
+    "band.band_plot(emin = task_options['emin'],\n",
+    "               emax = task_options['emax'],\n",
+    "               ref_band = task_options['ref_band'],)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c265e7fd",
+   "metadata": {},
+   "source": [
+    "The NEGF calculation on hBN can be done:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "f855b513",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "DPNEGF INFO    Numba is available and JIT functions are compiled.\n"
+     ]
+    }
+   ],
+   "source": [
+    "try:\n",
+    "    from dpnegf.runner.NEGF import NEGF\n",
+    "except ImportError as e:\n",
+    "    raise ImportError(\"dpnegf not found. Please install firstly.\") from e\n",
+    "\n",
+    "import json\n",
+    "negf_input_file =  \"negf.json\" \n",
+    "structure =  \"stru_negf.xyz\" \n",
+    "\n",
+    "with open(negf_input_file, \"r\") as f:\n",
+    "    negf_json = json.load(f)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "a56c0772",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "DPNEGF INFO    The AtomicData_options is:\n",
+      "               {\n",
+      "                   \"r_max\": {\n",
+      "                       \"B-B\": 4.82,\n",
+      "                       \"B-N\": 4.640000000000001,\n",
+      "                       \"N-B\": 4.640000000000001,\n",
+      "                       \"N-N\": 4.45\n",
+      "                   },\n",
+      "                   \"er_max\": null,\n",
+      "                   \"oer_max\": 6.3\n",
+      "               }\n"
+     ]
+    }
+   ],
+   "source": [
+    "AtomicData_options = NEGF.update_atomicdata_options(model)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "9aaf9455",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "DPNEGF INFO    ------ k-point for NEGF -----\n",
+      "DPNEGF INFO    Gamma Center: False\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "DPNEGF INFO    Time Reversal: True\n",
+      "DPNEGF INFO    k-points Num: 1\n",
+      "DPNEGF INFO    k-points: [[-0. -0. -0.]]\n",
+      "DPNEGF INFO    k-points weights: [1.]\n",
+      "DPNEGF INFO    --------------------------------\n",
+      "DPNEGF INFO    The AtomicData_options is:\n",
+      "               {\n",
+      "                   \"r_max\": {\n",
+      "                       \"B-B\": 4.82,\n",
+      "                       \"B-N\": 4.640000000000001,\n",
+      "                       \"N-B\": 4.640000000000001,\n",
+      "                       \"N-N\": 4.45\n",
+      "                   },\n",
+      "                   \"er_max\": null,\n",
+      "                   \"oer_max\": 6.3\n",
+      "               }\n",
+      "DPNEGF INFO    The structure is sorted lexicographically in this version!\n",
+      "DPNEGF INFO    Lead principal layers translational equivalence error (on average): 3.803219e-09 (threshold: 1.000000e-05)\n",
+      "DPNEGF INFO    Lead principal layers translational equivalence error (on average): 2.120221e-09 (threshold: 1.000000e-05)\n",
+      "DPNEGF INFO    The coupling width of lead_L is 54.\n",
+      "DPNEGF WARNING WARNING, the lead's hamiltonian attained from diffferent methods have slight differences   RMSE = 0.0000001.\n",
+      "DPNEGF INFO    The coupling width of lead_R is 54.\n",
+      "DPNEGF WARNING WARNING, the lead's hamiltonian attained from diffferent methods have slight differences   RMSE = 0.0000003.\n",
+      "DPNEGF INFO    The Hamiltonian is block tridiagonalized into 5 subblocks.\n",
+      "DPNEGF INFO       the number of elements in subblocks: 43092\n",
+      "DPNEGF INFO                   occupation of subblocks: 51.953125 %\n",
+      "DPNEGF INFO    --------------------------------------------------------------------------------\n",
+      "DPNEGF INFO    The Hamiltonian has been initialized by model.\n",
+      "DPNEGF INFO    ================================================================================\n",
+      "DPNEGF INFO    -------------Fermi level calculation-------------\n",
+      "DPNEGF WARNING No doping detected in lead_L, fixed_charge = 0\n",
+      "DPNEGF WARNING No doping detected in lead_R, fixed_charge = 0\n",
+      "DPNEGF INFO    Number of electrons in lead_L: {'B': 3, 'N': 5}\n",
+      "DPNEGF INFO    Number of electrons in lead_R: {'B': 3, 'N': 5}\n",
+      "DPNEGF INFO    -----Calculating Fermi level for lead_L-----\n",
+      "DPNEGF INFO    KPOINTS  kmesh sampling: 535 kpoints\n",
+      "DPNEGF INFO    Getting eigenvalues from the model.\n",
+      "DPNEGF INFO    Calculating Fermi energy in the case of spin-degeneracy.\n",
+      "DPNEGF INFO    Fermi energy converged after 3 iterations.\n",
+      "DPNEGF INFO    q_cal: 128.00000000000006, total_electrons: 128.0, diff q: 5.684341886080802e-14\n",
+      "DPNEGF INFO    Estimated E_fermi: -2.870708359971734 based on the valence electrons setting nel_atom : {'B': 3, 'N': 5} .\n",
+      "DPNEGF INFO    -----Calculating Fermi level for lead_R-----\n",
+      "DPNEGF INFO    KPOINTS  kmesh sampling: 535 kpoints\n",
+      "DPNEGF INFO    Getting eigenvalues from the model.\n",
+      "DPNEGF INFO    Calculating Fermi energy in the case of spin-degeneracy.\n",
+      "DPNEGF INFO    Fermi energy converged after 3 iterations.\n",
+      "DPNEGF INFO    q_cal: 128.00000000000006, total_electrons: 128.0, diff q: 5.684341886080802e-14\n",
+      "DPNEGF INFO    Estimated E_fermi: -2.870710982576104 based on the valence electrons setting nel_atom : {'B': 3, 'N': 5} .\n",
+      "DPNEGF INFO    -------------------------------------------------\n",
+      "DPNEGF INFO    Zero bias case detected.\n",
+      "DPNEGF INFO    Fermi level for lead_L: -2.870708359971734\n",
+      "DPNEGF INFO    Fermi level for lead_R: -2.870710982576104\n",
+      "DPNEGF INFO    Electrochemical potential for lead_L: -2.870708359971734\n",
+      "DPNEGF INFO    Electrochemical potential for lead_R: -2.870710982576104\n",
+      "DPNEGF INFO    Reference energy E_ref: -2.870708359971734\n",
+      "DPNEGF INFO    =================================================\n",
+      "\n",
+      "DPNEGF INFO    ------Self-energy calculation------\n",
+      "DPNEGF INFO    Calculating self-energy and saving to ./negf_output/self_energy\n",
+      "DPNEGF INFO    Merging 400 tmp self energy files into ./negf_output/self_energy/self_energy_leadL.h5\n",
+      "DPNEGF INFO    Merge complete.\n",
+      "DPNEGF INFO    Merging 400 tmp self energy files into ./negf_output/self_energy/self_energy_leadR.h5\n",
+      "DPNEGF INFO    Merge complete.\n",
+      "DPNEGF INFO    -----------------------------------\n",
+      "\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,-0.0000,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import shutil\n",
+    "output = \"./negf_output\"  \n",
+    "if os.path.isdir(output):\n",
+    "    shutil.rmtree(output, ignore_errors=True)\n",
+    "os.makedirs(output, exist_ok=True)\n",
+    "\n",
+    "negf = NEGF(\n",
+    "    model=model,\n",
+    "    structure=structure,\n",
+    "    results_path=output,\n",
+    "    use_saved_se=False, # whether to use the saved self-energy  \n",
+    "    se_info_display=False,\n",
+    "    **negf_json['task_options']\n",
+    ")\n",
+    "   \n",
+    "negf.compute()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "2e632557",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import torch\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "output = \"./negf_output\"\n",
+    "results_path = os.path.join(output, 'negf.out.pth')\n",
+    "if os.path.exists(results_path) is False:\n",
+    "    raise FileNotFoundError(f\"Results file {results_path} not found. Please check if the NEGF calculation was successful.\")\n",
+    "negf_out = torch.load(results_path,weights_only=False)\n",
+    "\n",
+    "plt.plot(negf_out['uni_grid'], negf_out['T_avg'])\n",
+    "plt.xlabel('Energy (eV)')\n",
+    "plt.title('Total Transmission kmesh=[1,1,1]')\n",
+    "plt.xlim(-10,10)\n",
+    "plt.grid()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "76d8e22a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Increase k-point sampling for better accuracy\n",
+    "negf_json['task_options'][\"stru_options\"]['kmesh'] = [1,20,1]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d2c9dece",
+   "metadata": {},
+   "source": [
+    "As well, it takes 23 mins in a 8-core CPU."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "afa89bf1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "DPNEGF INFO    ------ k-point for NEGF -----\n",
+      "DPNEGF INFO    Gamma Center: False\n",
+      "DPNEGF INFO    Time Reversal: True\n",
+      "DPNEGF INFO    k-points Num: 10\n",
+      "DPNEGF INFO    --------------------------------\n",
+      "DPNEGF INFO    The AtomicData_options is:\n",
+      "               {\n",
+      "                   \"r_max\": {\n",
+      "                       \"B-B\": 4.82,\n",
+      "                       \"B-N\": 4.640000000000001,\n",
+      "                       \"N-B\": 4.640000000000001,\n",
+      "                       \"N-N\": 4.45\n",
+      "                   },\n",
+      "                   \"er_max\": null,\n",
+      "                   \"oer_max\": 6.3\n",
+      "               }\n",
+      "DPNEGF INFO    The structure is sorted lexicographically in this version!\n",
+      "DPNEGF INFO    Lead principal layers translational equivalence error (on average): 3.803219e-09 (threshold: 1.000000e-05)\n",
+      "DPNEGF INFO    Lead principal layers translational equivalence error (on average): 2.120221e-09 (threshold: 1.000000e-05)\n",
+      "DPNEGF INFO    The coupling width of lead_L is 54.\n",
+      "DPNEGF WARNING WARNING, the lead's hamiltonian attained from diffferent methods have slight differences   RMSE = 0.0000001.\n",
+      "DPNEGF INFO    The coupling width of lead_R is 54.\n",
+      "DPNEGF WARNING WARNING, the lead's hamiltonian attained from diffferent methods have slight differences   RMSE = 0.0000003.\n",
+      "DPNEGF INFO    The Hamiltonian is block tridiagonalized into 5 subblocks.\n",
+      "DPNEGF INFO       the number of elements in subblocks: 43092\n",
+      "DPNEGF INFO                   occupation of subblocks: 51.953125 %\n",
+      "DPNEGF INFO    --------------------------------------------------------------------------------\n",
+      "DPNEGF INFO    The Hamiltonian has been initialized by model.\n",
+      "DPNEGF INFO    ================================================================================\n",
+      "DPNEGF INFO    -------------Fermi level calculation-------------\n",
+      "DPNEGF WARNING No doping detected in lead_L, fixed_charge = 0\n",
+      "DPNEGF WARNING No doping detected in lead_R, fixed_charge = 0\n",
+      "DPNEGF INFO    Number of electrons in lead_L: {'B': 3, 'N': 5}\n",
+      "DPNEGF INFO    Number of electrons in lead_R: {'B': 3, 'N': 5}\n",
+      "DPNEGF INFO    -----Calculating Fermi level for lead_L-----\n",
+      "DPNEGF INFO    KPOINTS  kmesh sampling: 535 kpoints\n",
+      "DPNEGF INFO    Getting eigenvalues from the model.\n",
+      "DPNEGF INFO    Calculating Fermi energy in the case of spin-degeneracy.\n",
+      "DPNEGF INFO    Fermi energy converged after 3 iterations.\n",
+      "DPNEGF INFO    q_cal: 128.00000000000006, total_electrons: 128.0, diff q: 5.684341886080802e-14\n",
+      "DPNEGF INFO    Estimated E_fermi: -2.870708359971734 based on the valence electrons setting nel_atom : {'B': 3, 'N': 5} .\n",
+      "DPNEGF INFO    -----Calculating Fermi level for lead_R-----\n",
+      "DPNEGF INFO    KPOINTS  kmesh sampling: 535 kpoints\n",
+      "DPNEGF INFO    Getting eigenvalues from the model.\n",
+      "DPNEGF INFO    Calculating Fermi energy in the case of spin-degeneracy.\n",
+      "DPNEGF INFO    Fermi energy converged after 3 iterations.\n",
+      "DPNEGF INFO    q_cal: 128.00000000000006, total_electrons: 128.0, diff q: 5.684341886080802e-14\n",
+      "DPNEGF INFO    Estimated E_fermi: -2.870710982576104 based on the valence electrons setting nel_atom : {'B': 3, 'N': 5} .\n",
+      "DPNEGF INFO    -------------------------------------------------\n",
+      "DPNEGF INFO    Zero bias case detected.\n",
+      "DPNEGF INFO    Fermi level for lead_L: -2.870708359971734\n",
+      "DPNEGF INFO    Fermi level for lead_R: -2.870710982576104\n",
+      "DPNEGF INFO    Electrochemical potential for lead_L: -2.870708359971734\n",
+      "DPNEGF INFO    Electrochemical potential for lead_R: -2.870710982576104\n",
+      "DPNEGF INFO    Reference energy E_ref: -2.870708359971734\n",
+      "DPNEGF INFO    =================================================\n",
+      "\n",
+      "DPNEGF INFO    ------Self-energy calculation------\n",
+      "DPNEGF INFO    Calculating self-energy and saving to ./negf_output_k20/self_energy\n",
+      "/opt/mamba/envs/dpnegf-dev/lib/python3.10/site-packages/joblib/externals/loky/process_executor.py:782: UserWarning: A worker stopped while some jobs were given to the executor. This can be caused by a too short worker timeout or by a memory leak.\n",
+      "  warnings.warn(\n",
+      "Lopez-scheme not-so-well converged at E = -1.0913 eV: 1.0707542578228952e-08\n",
+      "DPNEGF INFO    Merging 4000 tmp self energy files into ./negf_output_k20/self_energy/self_energy_leadL.h5\n",
+      "DPNEGF INFO    Merge complete.\n",
+      "DPNEGF INFO    Merging 4000 tmp self energy files into ./negf_output_k20/self_energy/self_energy_leadR.h5\n",
+      "DPNEGF INFO    Merge complete.\n",
+      "DPNEGF INFO    -----------------------------------\n",
+      "\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.0250,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.0750,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.1250,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.1750,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.2250,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.2750,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.3250,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.3750,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.4250,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.4750,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "output = \"./negf_output_k20\"  \n",
+    "os.makedirs(output, exist_ok=True)\n",
+    "\n",
+    "negf = NEGF(\n",
+    "    model=model,\n",
+    "    structure=structure,\n",
+    "    results_path=output,\n",
+    "    use_saved_se=False, # whether to use the saved self-energy  \n",
+    "    se_info_display=False,\n",
+    "    **negf_json['task_options']\n",
+    ")\n",
+    "   \n",
+    "negf.compute()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "ddf232fb",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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oIcyePbvD472FkyVLluCxxx7zpzgRpbYFeHxHW27MNgow6gTsP6/GTYMcuCydrVVERKQcK1aswJo1awL2fH6vENuvXz+MHj0aW7Zswbx586TbzWYzAMBkMuHmm29GcXGx13Ayfvx4r887ffp06HQd1/iIVDabDUVFRR71PnK2HtjxNRLjtHj3rglINcbglY3HsP+bEpjMF6BgxjCZS9173uodDVhv1jsasN7RV+8VK1YE9Dl9CicVFRUwGAxISEhATU0NNm/ejLvvvlu63263w2KxIC0tDS0tLVi3bh0WLVrkU4F0Ol1UnVSRe70b7a6WEZNBhwvNyQCAgWlGAECZpTmiXh+e7+jCekcX1pv85VM4OXnyJH76059KA2Hvuece5ObmoqCgAMuXL4fJZMKMGTNgs9ngcDhw7bXXerSqUM+Ig2HdV4kdkOIaiMzpxEREFOl8CicTJkzArl27OtxeWFgofb1jx45eFyraeQsn2amt4aSqEYIgQKVSyVI2IiKiYOOCGQpU09gxnGQmu8JJndXudZoxERFRpGA4UaCaJtfS9e7hRB+jQd+EWADs2iEiosjGcKJAYstIYrudiTnuhIiIooHfU4kp8D4/UIGj5+qx42Q1AM+WE8AVTrafPI+S6kbsKrWg0WrHpUM6LoJHREQUzhhOFOJkVSPu+Nd2j9vSjLEe32e1tpycqGzAX784imabA9t+PQ3J8eG/YiwREZGI4UQhDp+tBwCkGWNwxbA+SI2PwaxR6R7HiN06245Xo67ZNS7lWGUDxjKcEBFRBGE4UQhxHMnFg1Px4s35Xo8Z0Dqd+ERV25iT0upGjM1ODnr5iIiIQoUDYhWi9Lxrt2GxdcSbbC/3cXAsERFFGoYThSitdoUTbwFE1CchFrFaz1PGcEJERJGG4UQhSs+7QkZXLScqlarD/SVVDCdERBRZGE4UwCm0detkdRFOgI7hhS0nREQUaRhOFKC2BbA5BGjVKvQ3xXV5bPvwcqa2Gc02RzCLR0REFFIMJzJyOgWUWZpwot61iZ85WQ+tputT4t5yEtM6/mR3qSVoZSQiIgo1hhMZLX69GFNe2IJ/HtIA6Hq8iUg8JjU+BoPT4gEA8//+Dd7eVhK8ghIREYUQw4lM7A4nvjpSCQDQqgQkxGlxXb6528eNH5SC4f0ScNO4LMwbmynd/uXhyqCVlYiIKJS4CJtMTtc0w+EUEKNV43/HteCa2TOg0+m6fZxJr8N//+cK6fvs1Hjc9cZ2DowlIqKIwZYTmYhhIjNJD7XK/+fhTsVERBRpGE5kIoaJrBR9r55HfHxNkw01jbZel4uIiEhuDCcyEcPJgOTehRNDjFbavVhcyI2IiCicMZzIpK3lpPsZOt0Z0Np6wq4dIiKKBAwnMikVw0kvW04A16BYgOGEiIgiA8OJTEoCGE6yOCiWiIgiCKcSy6CmyQZL6+DVzGQ9jvby+cQZO2t3l2N/eS36JcTihZtHIyGu+6nJRERESsOWExlU1DYDAJIMOsTH9j4f5ppNAIDaZjt2l1qw/vsKbPjhbK+fl4iISA5sOZGB2GqSpA9My8bw9AQU3ns5Ttc04V9bT2LzoXMoqWIXDxERhSe2nMigpskVTkyGmIA958iMRFx1YT+My04GwPEnREQUvhhOZCCFkwC1nLjjirFERBTuGE5kENRwkuoKJ6UMJ0REFKYYTmTQFk4CP+RHbDk5XdsMq90R8OcnIiIKNoYTGdQGseUkNT4GhhgNBAEoO98U8OcnIiIKNoYTGQSzW0elUnHcCRERhTVOJZZBMMMJ4Fox9oczdXh/+ykcqqjDRQOSMX5gCpxOAWt2l+NsXTPGZqdgbOvMHiIiIiVhOJFBsMPJoDTXXjuf7D2NT/aeRpxOjV2/vRrbjlfj/nd3AQCMsVrs/O106DRsPCMiImVhOJGBGE4SgxROfjxpIJpaHGhosaNw72k025worW7EoYo66Zh6qx3lliZp00AiIiKlYDiRgbhCbLBaTvqb9Hj6+lEAgEMVddhXVouTVY042W7V2JNVjQwnRESkOGzTDzFBEII6W6c998Gx7QfIcsAsEREpEcNJiDXbnGhxOAGEJpxkuYUTcWG2EekJALhQGxERKRPDSYiJ4000ahWMAdiRuDtiy8mJqgacal335LIhaQDYckJERMrkUzixWCwYN24c8vPzMWrUKLz22msdjtm2bRtycnIwZMgQPPXUUwEraKSQBsPGaaFSqYL+88Rwsv3EebQ4nNCqVZgwKAUAwwkRESmTTx/dExISsHnzZhgMBjQ0NGDUqFGYO3cuUlNTpWOWLFmCt99+Gzk5OZg0aRJuuOEG5ObmBrzg4SrY04jbE8NJvdUOAMhM1ktTjUuqGiEIQkhCEhERUU/51HKi0WhgMLgudlarFYIgQBAE6f7y8nLY7Xbk5eVBo9FgwYIFWLt2bWBLHGZqmmw4db4RDqfrdTp6rh4AYDLEhOTnZyTpoXbLHlkpBmQmu85hndWO45UNISkHERGFD7vD2e3+bPVWO06db0SZJfBbpfg86MFisWDy5Mk4fPgwnn/+eaSlpUn3lZeXw2w2S9+bzWZs2rTJ6/MUFxd7vd1ms/laJMXaV1aLm/7+LexOARdlmTAjpx+e+/QQACAxVgObzSbVN5j1zjDF4ZSlGQCQmRQHrcqJvgmxOFtnxZUvbML/3TIaV4/sF7Sf700o6q1ErDfrHQ1Y7/CutyAImPN/W9HQ4sB/75vkdbHOY+caMOcvW2G1uyZ45AW4DD6Hk6SkJOzevRsVFRWYO3cu5s2bh379AndhKyoqCthzyW1DuQp2pwYAsLO0BufPWwC4mjEyhbMoLCyUjg1mvfMSVDhbq4ZODaQ0nERh4QnkJ6qxvs71C/f2hp2wn3AG7ed3JZLOty9Y7+jCekeXcK93TQvwQ4UrHry9+lOkxXU85usKFax2DVQQoA3CyAC/p4v069cPo0ePxpYtWzBv3jwAQEZGBsrKyqRjysrKkJGR4fXx48eP93r79OnTodOFZjxGsH378ffAyVPS96WNagACVt4xDhMGugal2mw2FBUVBbXeBZ3c9v6OU/j1qu+hTuyDgoKxQfnZnQlFvZWI9Wa9owHrHd713nHyPLDD1bsx/pLLcWH/hA7HfL/+MHDsOG67eAAenTEECxb8PaBl8CmcVFRUwGAwICEhATU1Ndi8eTPuvvtu6f6MjAxoNBrs2bMHOTk5eOedd7zO6OmKTqcL65Pq7pTF6vG9OO5kcN/EDnWUo94D+7h+4U6db5btNY+k8+0L1ju6sN7RJdzrXV7bIn3dYBO81uVUjWuoQHaaMSh19WlA7MmTJ3H55Zdj9OjRuPzyy3HPPfcgNzcXBQUFKC8vBwC88soruOWWWzBs2DDMnDkzqmfqlFS5Bpv2SYiVbovRqNEvwUsbmQzEmTynzjdJwYmIiKKb+zIT4gzT9sRFPMXrSKD51HIyYcIE7Nq1q8Pt7mMnJk6ciP379/e6YOHO4RQ8Fj37aKeruyszRQ+1WhlTd/ub9NCqVWhxOFFR24yMJL3cRSIiIpm5h5PaTsKJeMyA1OCEE64QGySna5pgdwqI0agxbmCydHuwUqY/NGoVMpNdgYQLshEREeC5tYm3lpOaJpu0gW1WMsNJWBEv9pnJegxy2/lXSeEE8Nx7h4iIqLtuHTG8pBljEB+kbVgYToJEPHlZKQYpAADKCydiebgJIBERNdscqKhtm8xhaWrpcIz79S1Ygr/zXBR6b3spHv7PXgCui39/Uxy0ahXsTiGoJ9MfYjh569sSbD5cKd2uU6uwZOoQTB3RFwBQUduMh/+zB+cbbbhudAZ+ctkgWcpLREQ9848vj+NQRR2WzhiOVzYcwfzxWbiwfyIA4GRVA55eewB3TxmMsdmupS2OnqvHbcu/9XiOmia7x/drdpfj3rd3Agjuh22GkyD4v41HpK9zM03QatTIMZuwr6wGI1t/MZQiLzMJAFDV0IKqBs+E/NdNR6Vw8vHucnxx8BwA4NjZeoYTIiKFe+mzQ6hrtmPb8Wocq2zAym9P4vCzrpWvHv1wL74+WoXPDlTgxHOzAbg+WJ9unSIsat+t8/Lnh6Wvc82moJWd4SQIGlo32Xv6uhzMG5MJAHh98XhUNVgV13IycXAKVi+ZhMr6tma8E1WNeHrt9x5dPe59kHVWO+wOJ7ReljQmIiL52R1O1DW7rkXHWvdQsznalowoPd+xK7+kynXb5UPTcF2+GUvf3+0RTpxOQboW/OHGPMwdY+7wHIHCcBIEDVbXZkmTh/WVpg0nx8cgOT40m/35QqVSYXRWksdtVfVWPL32e5ypbUazzYE4nabDgNnaZjtSFFgfIiJyvUd3xaTXoRSeG/aJ7/OLLhmIhDhXPHCfSnyu3gqr3QmNWoUbxpiD+gGVH30DzOkU0GRzhRNDrEbm0vgnJT4G8TEaCAKk3SbbhxNLY8dBUkREpAydLZ4mMunbVnWtabJBEASp5SQ71QCTQdfhecTrQEZSnNfNAAOJ4STAxGACAIaY8AwnKpXKY4qx0yngVLVnwu7uF5+IiOTT3QdIjy6e6kbUNNlQ1zokITPZIIUXMbgAbd0+oZh1ynASYI0tbeEkThue4QTwnGJcUdeMFocTWrUKw/oZATCcEBEpWXfv0e7dNaXVjVKrSN+EWOhjNFI4cTgFNLRe10qCvGS9O445CbCm1pNoiNEoZpl6f4i/fCVVjVJaNifrpXEmDCdERMrV3Xu0uMIr4AodjtbWEfG9X6/TQKdRweYQUNNkgzFW6xZO4js+YYCx5STAGlpczWLh2qUjEvdLKHFL1ANS2pr6OttvgYiI5Nfde3T7sSTtW0VUKlVb105rkGHLSRgTu3X04R5OWn/59pbVwGp3AnCtBmh3uL5mywkRkXJ19h7tcApwuE3cAIBvj1cj6YwriLgvd5Go16GyvgVvbytBVooeR87WA2A4CUtit058THi/tIPSXM12p2uapUV5BqXG42yd62uGEyIi5ersPbrJ5pCuUyIxdADA4D5tXTZ9jLE4dq4Bb35zUrpNpWI4CUtit064t5xkp8bj8WtGYn95DQDXtLObxmXi362/pAwnRETK1dl7dKPVLq2BkhCrxZ2XD8bJatcibX2MsZiRky4d+/CsEXhnWwnszraZPRMGpkjTjIOJ4STAIqXlBADu8LJEvfv0MiIiUqZOw0mLQ7rPZNDhvmlDO32OMQOSMWZAclDK1x0OiA2wSGk56UwiwwkRkeJ19h7d0GKXBsu6L8SmNAwnAeY+lTgStbWcdL00MhERyaez9+gm95YThpPo0SiFk/Dv1vGGU4mJiJSvs/foRoaT6BQp65x0JsnARdiIiJSu8zEndum+pBAMbPUXw0mARUu3Tr3VLq15QkREymF3OFHfuk9OcrsA4t5ykqjglpPI7HuQUaR36yTGtdXrYEWdFFYyTHqo1SpU1DbD5nBCpVIhwxQHlSp8l/AnIgo3zTaHxx5vmckGnG+skb6va7bj+/JaAMru1onMK6iMGiO8W0erUcMYq0W91Y7Zf/5Sun3K8D7IM5vw5w1HpNtm5qTjbwvHylFMIqKo89rmY3i28ACeui4HAGCM1Ur7oYmeWLNf+lrJ4YTdOgHWGOHdOgAwd4wZsVo1YrVqxGhdv0JfHanExoPnAADa1g0Pi09Uy1ZGIqJo82zhAQDAb1e7AkjfhFjMzuuP7FQDLh6U4nFskkGHSRekhbyMPcVwEmCN1sju1gGAp64bhYPPzMLBZ2bhwFMzpZ0rvz/taip8tbW1pKbJBkEQunoqIiIKkgGpBtw8LgubfjUVeZkm6fYkgw67fns1BqYFf3dhfzGcBFijLbK7ddrTqFXITHbts+BoXeI41+z6I7A7BY++TyIiCh33PXDcPzCHYm+c3mI4CbBo6NZpz30Xy5T4GPRJiJW6djjlmIgoNMxJeo/vPcNJ2zUpi+Ek+kRDt057A1La/iCyUgxQqVTcg4eIKMTah5OsTsIJW06iUGOE763jjfsvuvg1wwkRUWgZYj2vO+zWIYnYrRMfG03hpG1QVbYYTgwMJ0REoSSO+xOx5YQAAC12J+ytvxwGXTR163TRctLIcEJEFApOt9mRqfExMMa2XYfiGE6iV5PbzJRo6tbJajfmBGC3DhFRqDnddhRpP+i1vrltl+L+prhQFclvDCcBVN3YAgCI07UtThYNEuJ0GNwnHjFaNYb1MwJgOCEiCjWHW8uJ+7omAJCflQQA0Os00GqUf32Knr6HECitbgQQHk1mgfbuTy9BvdWOVGMsAIYTIqJQc7YOK1gy9QLcc+VQj/uyUgz47IHJSG23nL1SMZwEUEkUh5M+CbHokxArfc9wQkQUWuKYk7zMJMTpOg4tGNLXGOoi+U35bTthRGw5CYcFboItkeGEiCikHK29OpoI2A2e4SSAornlpD22nBARhZa4l5lGzXBCbhhO2ojhpJbhhIgoJMR1TiKg4cS3cFJaWoopU6Zg5MiRyMvLw/vvv9/hmMWLF2Pw4MHIz89Hfn4+jh49GrDCKpkgCCipYjgRseWEiCi0xHASCS0nPg2I1Wq1WLZsGfLz83HmzBmMHTsWBQUFiI/33Hb5z3/+M6655pqAFlTpLI021Fld88jFXXqjmXs4EQQBqkiI8kRECiZE0JgTn8JJ//790b9/fwBAeno60tLSUF1d3SGcRKqSqkbsLatBQW56h4ut2KXTNyE2qhZg64wYTuxOAX/54ih0Gs/Xy+Fw4odyFc58dQIzRmVgYFp0/A4REQWLuM5JJHwY9Hsq8Y4dO+BwOJCVldXhvqVLl+Kxxx5DQUEBnnnmGWg0HS/WxcXFXp/XZlNuN8D0lzbBanfiTzfnoSA33eO+4+fqALh26PWlDuKxSq63P3QqAYYYDRpbHHj+vwc7OUqD1ScPoejAWbx954SQlk8ukXq+u8N6s97RQO56OxyuJWIFpyOkZQjGz1IJgiB0f5in6upqXH755Xjttddw6aWXetx3+vRppKenw2q1YtGiRbjiiiuwZMmSDs/hLZwsWbIEjz32mK/FCZn7trqy3Ng0J24f6vS4r6hMhbUlGozv48RtQ5zeHh51dlapsP985wm+0Q7sP69GUoyA3411dHocERF17+mdGlQ2q3Bfjh2DE0P7s1esWIE1a9YE7Pl8bjmxWq24/vrr8cgjj3QIJgCkbp+4uDjcfvvtXgfNAsD48eO93j59+nTodDpfixUS921dDwAwJvdFQcEYj/u+WrUfKCnDJaOGouDKC3r8nDabDUVFRYqut78KurjPZrNh5Zoi7D+vhg1aFBTMCFm55BTJ57srrDfrHQ3krvfzP2wBmpswadKluKh1ufpQsNlsWLFiRUCf06dwIggCFi9ejCuvvBILFy70eszp06fRv39/OJ1OrFmzBjk5OT4VSKfTKfKX2em2FXWt1d6hjKcszQCAgX2MfpVfqfUOJkPrb19DiwNQa6ALg/0eAiUazzfAekcb1ju0xH6Q2Ah43X26Gnz11Vd49913sWrVKmmq8N69e3HnnXdi+/btAIAf/ehHyMvLQ15eHhwOB+69996gFDzUxJk4gPfpsVzjxHd6t2jM9VCIiHpHXL5eHW0DYi+77DI4nR3HUyxfvlz6esOGDb0vlQK5XzzP1lo9psfaHE6UW5oAMJz4QqMC4mM1aLA6UNNkkzYNJCIi34nrnKgjoBE6AqoQGu6tJfVWO6obWqTvyy1NcApArFbtsfkddc8Ux8XaiIgCQRx9EAmLsDGc9FD7i6fYjQMAJ91Who2E+eWhxA0CiYgCI2q7daJZ+4vnnlM1UivJ3rIaAOzS8YepdeCJ++vb1OJAnE7NoEdE5AOpWycC3jsZTnqofTh5Ys1+PLFmv8dtWQwnPkuM89wg8HhlA2Yu24y5Y8z4/dw8OYtGRBRW2lpOZC5IADCc9JAYTtKMMXA4BTS2eC4alhCnxaxR6d4eSl1ov0Fg8fFqWO1ObD5UKWexiIjCjjNaN/6LZuLF89rRGXjiWt/WbqHOte/WEcfynK5pQovdiRgth0UREfWEI4LGnPCdv4fEi6f4SZ8Co33LiRhOnAKk6dlERNQ9cbaOOgJaThhOeojhJDjaz9ZxnwXl/jUREXVN6tZhy0n0qGlkOAkGU5xnt04pwwkRkV+kAbERcGWPgCqEBltOgqOtW8eOeqsdVW6L25UynBAR9YggCG3dOmw5iR4MJ8EhduvUNtk6hBG2nBAR9Yzb3rTs1okmDCfB4T5bp30YYTghIuoZsUsHiIyWE04lbnX0XD2eWL3fY/dhdwwnwSEuwlZvtePptd8DAEakJ+CHM3XYX16Lu/+9Ay/enA99jEbOYhIRKZrDrekkEsacMJy0WrWzDF8e6Xrhr5T4GCTHx4SoRNHBpNchzRiLynorTp13TR2+Jq8/ztQ2w9Jow7p9Z3Bd/jnM5AJ3RESdcm854SJsEeR8o2sg5pzRGbguP8PrMRf2T4ROEwGRVEE0ahXW3nMZ9pe79ifSx2gwYWAKrr/IjJnLtqDeaufAWCKibriPOWG3TgSpaXJ154zOSsJVF/aTuTTRJd0Uh3RTnMdtmckGLLo0G/+38SjHnhARdcOjWycCwgmbAVpZWltOOKZEOcRdnhlOiIi6JkRYtw7DSataDnhVHHGXZ3brEBF1zbPlRMaCBAjDSSvOxlEeseXk1Pkmjz88IiLyJG76p1IBKnbrRA6GE+Xpb9JDp1GhxeFERW2z3MUhIlIsIYJWhwUYTgC4+upqm10DYhlOlEOjViEzmeNOiIi644igTf+AKJuts6+sBl8fda1lEqvVYM7oDCTHx6DeapdOLMOJsmSlGHC8sgElVY2YODhV7uIQUZTZePAsDlfUSd/HaNS4ZnQG0oyxMpaqI/EaFgkLsAFRFk5+/HoxztVZpe+PVzbgyTk5UpdOjEaNOF2EnNkIMSBFD4AtJ0QUemdqmvHjfxZ3uP3Q2Xr8vxtyZShR59itE6Za7E4pmIzLTgYAHGpNw2I4SdTrImIgUSThdGIikktlveuaEadTY+4YM8YPdF07ylpXs1YScUBspHTrRE04EQOISgU8PGsEAOBkVaPHfeImdKQcDCdEJJcWhxMAkGaMxYs35+POywcDaLtmKInTbbZOJIi6cJIQq0V2quuCd7qmCS12J9c4UTCudUJEcmmxu8JJjNZ1qRSvEbVKDCfigNhIWOQEURhOTAYd+hhjEadTwykA5ZYmTiNWMDGcVDW0oL6THaOJiIJBCicaz3CixJYTqVuH4SS8uLeOqFQqj+4ChhPlSozTIdngOi9sPSGiULK1duvEajuGE/fl4pXA6SpqxIybjJpw0j6AMJyED447ISI5iC0nunYtJ3angMYWh2zl8sbJAbHhqX0AcR/LwHCibOK5KqliOCGi0BEHxIpjTgwxGmhbu02U1rXj4JiT8NRZy8mhijqcqXFNFzMZYuQpHHVJPFdbj1XB3vpmQUQUbNZ2A2JVKpVix51wtk6Ycl/LBGi74G08eA6fHagAwJYTpRLP1YYfzuLaV75SXF8vEUWm9gNiAeUOinVyQGx4at9yMn5QCob1MyJWq0asVo3MZD0mDk6Rs4jUiSuG9UGGKQ4AcOB0LSrrW2QuERFFA1u7bh2g7QOu8sKJ6/9IWSE2alYdax9OEuN0WP8/k+UsEvVQRpIeXz96FSY9twFlliaUVDeiT4Ky9rUgosjTfp0TAEgyKDOcSHvrREY2ib6WkyQ9x5WEq6zWfXY4pZiIQqGrbh2lLcTGRdjCFFeBDX+cUkxEodR+tg6g5DEnrv8jpVsnasKJpZHhJNwxnBBRKIXTgFhxhdioDCelpaWYMmUKRo4ciby8PLz//vsdjjl69CjGjRuHIUOG4Oc//7liZlZwLZPwl8VwQkQhFFYtJ9HcraPVarFs2TJ8//33WL9+Pe6//340NDR4HPPwww/jySefxJEjR1BZWYlPPvkkoAX2R4vdiSabazU/hpPwlZ0aD4BjTogoNLwNiFXubJ0oHhDbv39/5OfnAwDS09ORlpaG6upq6X5BEPD1119j9uzZAIDbbrsNH3/8ceBK6yfxl0ilAhLiomaCUsQRu3XO1Daj2aaspaOJKPJ4CydKbTmRZutESDrx+0q9Y8cOOBwOZGVlSbdVVVUhJSVF2njIbDajrKzM6+OLi4u93m6z+XfCvzlWjT9tOCI1w7lrsbtOWkKsFg6HHQ4FXdfE+vpb73DlT72NOiA+VoMGqwNT//gFXl80FoP7xPv18+0OJx5b/T3yzIn40cUD/HoOf/B8s97RIFLq3Wxz7YSugSDVJV7nur4dOF2LOa9s8ThecAqordVg+cmtMMRq8aurh2F0pikkZbXZXWVVIfSvezB+nl/hpLq6Grfffjtee+21QJcHRUVFfj3u7z+osf981w1BKVobCgsL/Xr+YPO33uHO13pnxKpx2KrG6Zpm/OGDLZiT7d9y9tvPqfDhEQ0+3FmO5Kp9fj1Hb/B8RxfWOzyVnFIDUOPwwQMorPkeAGCxAmpo0GxzYs+pWi+PUgH1dQCAP360FbdcEJotN3ZVqQBoUHP+vGKvc77wOZxYrVZcf/31eOSRR3DppZd63Jeamorq6moIggCVSoWysjJkZGR4fZ7x48d7vX369OnQ6XwfF/LnI18BaMCD04ZgWHpCh/tVAC7KSpIW0FEKm82GoqIiv+sdrvyt92VTbbj33T346mgVdMn9UVAw2q+f/8Nnh4EjxwEABQUFfj2HP3i+We9oECn1Xl29E6g+h4vyclEwLlO6/eLLGnDSy9g3h92Onbt2oSFhAN4qLkNCajoKCvJDUlZh7xng0B6kpaWgoMD79TVYbDYbVqxYEdDn9CmcCIKAxYsX48orr8TChQs73K9SqTBx4kR88sknuOaaa7By5UrcfvvtPhVIp9P5/MvsdAo4db4JAHDdRVkYkGrw6fFK4E+9I4Gv9U7V6bB40iB8dbQKpyxNfr9mlfVtzZByvO4839GF9Q5PttZxHPpYz3qMyEjCiIykjsfbbLCd3AlnZgreKi5DndUesvqr1K6eA41aHdavucinAbFfffUV3n33XaxatQr5+fnIz8/H3r17ceedd2L79u0AgP/93//FE088gQsuuADJycnS4NhgOldvhdXuhEatQv+kuKD/PJKXtN5Jlf+zds7WWaWvxSl4RETuvA2I7Ym2QbP2gJepM5G28Z9PLSeXXXYZnM6O/WfLly+Xvh46dCh27NjR+5L5QFz3wpykh04TNevKRS1xGfvaZjtqGm0w+dFVV1HbLH3d4nAiTq0JWPmIKDJI65z4eF1JlGGJe3EuSFQuwqZU4ido8RM1RTZDjFba+M/fBdnOubWccFoyEXkjtpzofG45cX3uD+V046he50SpxIFJWQwnUaM3S9k3tThQ1dAifW+1h2Y0PRGFFzGcxPrachLnajmpt9ph97K8RTBE9QqxSiWuGMqWk+jRm3By6rznY9hyQkTe2LwsX98TiW6LfdY2h2bciTh0ThUh3TqKXS7166OVMMRokZ+VJN325eFKfH+6psOx35WcB8BwEk383WfnbF0znlr7vcdtbDkhX/13/xmcrGrbukOv02DOaLNf45/Iu9M1Tdh+4jxmjUqHVqaxhP4OiNVq1DDGalFvtaOmyYaU+JhgFM+DuPGfhuEkeGqbbVj0j23Q6zTY9duroVarUFVvxaJ/bpOW6PVmYBrDSbTISnYNim3fCtKd5wp/wJbDlR63seWEfHG4og4/e7PjoP9T55vwaMGFMpQoMl31wiY0tjjw9PWjsHBitixl8LbxX0+Z9DopnIRCpHXrKDKcnK21wuYQYHPYUd9iR2KcDmdqm+FwCojTqVGQ27/DY4b0NWJk/0QZSktySDW6PolYGn37wz9Y4Vq5MT0xDmdaZ+yw5YR8IY5XSojVYnpOP5RWN6L4xHnpd4sCo7HF9aHhm6NVsoUT8b3B19k6gGvGTpmlKXThpLXlJEIaTpQZTtxPZk2jDYlxOuk2c5IeL96cL1PJSCn82XxLEARpZte/75yAX761Ez+cqWPLCflEbL01J7vei74+Uolbl3/r98wx6poxVr7LlDRbx49wEuoZO44IazlR5IBY97nh4okVbxMvShTd/AknlkYb6qyuwWmZyQbE6lxrm1htbDmhnrOLu7+2fkQVxz+dqm7ign5BYJRxJ3lxQGysn906QOjCSdtUYoaToHE/mWIoqWE4ITfSIkfNth5fEMRPtv0SYxGn0yCu9Q2n2c6WE+o58fdNq3FdBPqb4qBVq9DicKKirrmrh1IPuf9Nx8vUcmJ3OKUZMP6OOQFCtxCbWFaGkyCq8dJywnBC7sTfA0GA1BrSnZJ2U87ZckL+sLdrPtdq1DC3DtDuzZYK1Ka+pe1vOkGmcNLitj5Jb8KJpbGlmyMDo61bJyQ/LugUWQ2GE+pOrFaDOJ3r17enn0xK2i3Wx5YT8oejdQsPrVvfvhh4ve1US76rcRvoLtcYiha3gfL+DIgNdbeOwG6d4GM4oZ7w9Y+//WJ9bDkhf7RvOQHaAm8pw0lAuP9Ni2MpQk0MJ2oV/FpnxWRwzSgM3YBY1//qCBkQq/zZOlI4cTXzJTKcUCuTXoeKWqvX6cROp4DTtc3SpwkAOHK2HkBbOGHLCfnD26wI8Xfq4Jk6j7V37HY7qq2ugZURsIt9rzmdgmujzdYPBq6tJKxIM8ZKtzXbHB7XALtMg4zFbh1/N5MVPzydq7N2ux6TRq1CemJcr1Z35SJsIcCWE+qJrlpO7npjOz7/4azXx7W1nLjedNhyQr5oCydtFy3xd2r99xVY/31Fu0do8WbJVhQ9MDlipnn6a9E/t2F/eS02Lp0CQRAw5Y9fwNJoQ5oxFl/8agqaWhy48o9feIwj62rhzWDyd3VYkfj+9F2JBZf978Zuj79t4gA8c32uXz8LcO/W8fspFIXhhMJWZ+HE6RSkVWBjtGq4/60O65eAUWYTACBO2/pJjS0n5APxk7z7mJNLBqdicJ94lJ1v6nC81e7EscoGlFuaonpzUpvDia+OVMIpAPvLa2B3CFKrZ2W9FQfP1OJ8g63DAHfZwkkvphEDQH5WEob0NXbb1ecUBNgcAoqPn/fr54jE14ndOkHEdU6oJ0x67326FXXNaHE4oVWrcOCpmZ1+WmXLCfnDW7dOcnwMNjw4pcOxNpsNk579L842q1Ba3RjV4aTc0iRNdy2tboTN4Rk6Sqobcb6hYyuo7C0nvejW+eyByd0et+eUBXNe+arXY1McHBAbfF2tc5JkCP4GShQeOms5EadzZibru2xGF1tOrGw5IR94aznpSmqc6/hoX0HWvf4l1Y0dWhRKqpq8vkayhxM/W056KlCzesThdZHSdajIlpP23TqCILBbhzroNJy0mzLcGbHlpJktJ+QDR2tzf0+bz9NiXf9H+zRjz3DSBHvr65hmjEVlvRUl1Y1e1wRxyDVbpxeb/vlCfB9rsjnQYnf6/fMcTracBFWL3Slt+AS4LjwNLQ7phWc4IZG4d0X7dU7aL7bWGXF2AFtOyBdibwRbTnzTvuVE/P6yIakAXF093l4jubYE6M2+Or5IiGu7pvWm9aQtnPS6SIqguHBS22xr971dStMxGrW08BaRydB1y0l34UQc6MaWE/KFuAhbT5vPU+Nc/0f7Giju9S+papC6XycNSQMAnKxu8BpOZJtKHKJuHY1ahYS43m8SKM7WiZRuHcVd6cX1TMQLh8Mp4HSNa7+KRL2uV/PAKbJ0163DlhMKBl/HnKTFsuUE8Kz/ebdNOMVwUlFrhdXe8YOC3LN1/B0Q64ukTj5o+YIDYoNMbKLvkxArJVYxYYvN+ERA5+GktKdjTthyQn5wOHz7hCq2nFgabSFbLVSJvO071C8xFv1NcTB2sX9OpA+IBQKzSWCkbfynuKt9TXPbwFer3YlzdVa8sP6gdBuRSPx9KLc04br/+8p1oyCgst7VDTggtbsBsWw5Id85fGw+j9UAqfExqGpowfxXt0q/d95Mv7Avfnnl0ICUUw6V9VY89MEeVNY3Y6BahdTj1fjzhmOw2h2obXa1lAzvl4CDFXUAXK2bKpUKWSkGHDhdCwAYkZ6AH87USc8p14BYWy/XOfFFIGbsOCNs4z/FhRPxwpISH4PEOB3O1VlR3tqtM6SvUc6ikcKkm/SIj9GgocWB3aUWj/sGphqQGNd1mJUWYWPLCfnAIXXr9PwqkGtOxBeHKj0uut7sOWXBnZcPlrocw826vaexoXVl5n0qNWq/PIFtJ6ql+4f2NeLiwSlSOMk1JwEARmeapHAyZXhfj9dJrgGxta1DDAwxwb9MBiKciL+XkTL0QXHh5FTrCotZKQY8PHMEdpyshiC4Nl6aMDBF5tKRkhhjtVh33xU4fLbjG35eZlK3j5cWYWPLCfnA28Z/3XnxpjzsLqvrchO7e9/eiYYWB06dbwrbD2In3bpunIIKO0osAIAHpw/DyIxEjM5KgjFWi2kX9oNKBYxvfU9/4toczMrtD41KhfGDkvGTywbipaLDeHtbiWwDYtuWJNAH/WcFpOWE65wEl/gLkZ1igEmvw5Uj+slcIlKyAamGbrtvOsOWE/KHw8cBsQCQEKfF1BF9uzxmQGo8DpyuRUl1Q9iGk/aDfutau3Jm5/XH4D5tdbpiWB+P4/QxGkx2u61vggaD0lx/13K1nPR0YH0gJAYknETWxn+K650qbW05CcUvBEW3tuXr2XJCPWd3BGcPk+zW9zxvA0fDhbcZSSoVYE72vfVB3FhRrpaTng6sD4TAdusEpEiyU144qW7r1iEKJmmLdi/TF4k6I35C9aXlpCfEFsCS6o6bB4YDQRCkC/qlF7R1wWeY9IjV+j6GRtP68soxINbhFKQhBqH4oByYbh2ucxI0TgGoaujZTAui3hJH4bfYndICRkTdsfu4CFtPiR/IwnU9lOqGFjS0OKBSAZcMagsn/o7Z0LROO3E4Qv+3WVHr2jxUp1GhvylcxpwwnARNS+sH2CSDrtuZFkS95T4jwtviT0Te+DPmpCfET+jhupKsGKr6J8Z5jJnxt+VBHDshR8uJWJfMZENILvYBWeek9S0sUmbrKDKccLwJhYL7+gVWDoqlHgrWmJMBbi0n4diS577hZpbbGBO/w0nrn6ccA2LFcT+hGl4QkDEnETYgVlGzdcobVEgBwwmFhk6jhkatgsMpYOW2k7jr8sFB3+SLwl+wWk7MSXqoVa7daV/ecKTbfcSG9DUqZjbjkbN1eGLNfgCu9+9Mt3Di7wVezgGxbTN1gt+lA7SFk6qGFvx989EePWZgajyuzkmXvndG2MZ/igon9tbfwUFp8fIWhKJGYpwW5xtt+MOnBzEoNR6zcvvLXSRSuLYVYgMbZGO0amQmG1BS3YgXiw716DGbfjUF2anyv1/+8q2dsDS6PvUPTItHfKwWiToBtTaV3+/nUsuJjN06ofqgnBIfA7XKNf7t/xX+0OPHffbAZKkLTXydAt2iJxdFhZOkGOC2i7OwcGK23EWhKPH7uXn4+b93AADKLOE5S4JCy9eN/3zx7A2jsGpnOQR0fUHefOgcKutbcLiiXvZwYnc4ceRsPQBgZk46FozPAgAsuMCJhMzhyDWb/HpeqeVEhgGxoQ4nCXE6/H5uLr49Xt39wQA2/nAW5xttKLO0Ldgnvkzs1gmCzHgBT1xzIXQ6Doal0Jg5Kh0LJ2bjzW9ORvWmbNRzvm7854vLh/bB5UP7dHvcL1buQOHeMzipgMGzp2uaYXcKiNGo8ZcfjYFarYLNZkNOsoCCyYP9HqAp54DYUK5xIpo/fgDmjx/Qo2MX/H0rvjlW7fGeJXXrREjPdIRUg8h/gRiMRtHDn+XrAy1LQTN7xDJkpugD2qUg14DYeqtdWtJCqetteXvPkrp1IqTlhOGEoh7DCfnCEaR1TnyRneLqylHCmigng9QFIteAWDFsJSt4SQtvU48dToYToohiMjCcUM+JffvBGHPSUwMUtGBbsMZnyDUgNtTjTfzh7QOV+DJF5SJsN9xwA5KTkzFv3jyv90+ZMgUjRoxAfn4+8vPz0dTEAYakfGw5IV8ooeXEfcE2uTbGEwUvnMgzIFaO8Sa+kt6zGt1aTqK5W+e+++7DG2+80eUxH3zwAXbt2oVdu3ZBrw/NHHGi3mA4IV+IF0utjCMP+yfFQaNWwWp34ly9VbZyAMG7mIsDYkPdcnKyKjxbThzRvM7JlClT8MUXXwSpKETyCMTS0RQ9HNKAWPnKoNOokZEUh9LqJnx38jxyM7uerpuoD974CbHlJDvA+6GJLVOhHHPSbHNg67EqAMoOJ4leu3XkH6gdSAGfSnzrrbdCo9Fg4cKFeOCBBzo9rri42OvtNlt0XSDE+rLe8onXuf6Ya5psaGlpCereFEqqdyhFUr3Fjf/gdHZbn2DWOytJj9LqJty98rtuj9VpVHj/pxcjJyMxoGWobbJJi6+lG3Ud6tubegtOBwDA4ej+dQ6EBqsd05d9iXP1rpk6GaYYn39uqH7PjTGuZGxpbJF+lvh7KTgdIf87C8bPC2g4WblyJcxmM2pqajBnzhwMHz4cs2fP9uk5ioqKAlmksMF6y8fqAAAtbA4Bq9auQ6zvu7v7TAn1lkMk1LuqWgNAhe++2wHr8Z59qg9GvQeqVPhOo4ajm22h7AJgcwCvF36FqRmBbYU41QAAWhh1AjZ9vr7D/b2p9/E613PX1TegsLDQ7+fx5eedq3ddEs0GAWf2fwsfFmv1EOzf8xOtr03F+VrptbFYXL+X27dvR8OR8Nubqb2AhhOz2QwAMJlMuPnmm1FcXNxpOBk/frzX26dPnx5Vi7DZbDYUFRWx3jISBAG/3v4Z7E4BE6+4Ev1NcUH7WUqqdyhFUr3/dnwr0FCHiRePx+VD0ro8Npj1LgDwux4c90LRYfxt83EY0weioODCgJbh0/0VwJ7dGJKehIKCi6XbA1Hv3adqsGzft4jV61FQcEWgityp1btPA/v2YuKgZLz5E+/Xp+6E6vf8eGUDXtr3FVqgQ0HBDADAX459DTTWY+LFEzDpgtSg/WxvbDYbVqxYEdDnDFg4sdvtsFgsSEtLQ0tLC9atW4dFixb5/Dw6nS7s37z8wXrLy6TXoaqhBY12ISTlUUq9Qy0S6i0OgYj1oS5y1ntgmmt581OW5oCXobzGNRg3OzXe63P3pt6xrY9zCgjJa9dWF2Ovf16wz3dqgmuySb3VDpVaA61GLf1exmi1Yf83Bvg4W2fatGm46aabUFhYiMzMTGzduhUFBQUoLy+H1WrFjBkzkJeXh4suugijRo3qdMoxkdJ4m5pH5I1dAVOJfSGtiVIV+DVRgrkmSKgHxEp1CfDA3mAQB8QCQG2zHUCUb/z32WefdbjNvS9wx44dvS8RkQy8jX4n8sapgEXYfCFO8T11vgkOpxDQUFUSxDVBxHKGah0XMbwpeX0TkU6jRnyMBg0tDtQ02ZASHyP9XoZLaO4OV4glAtc6oZ4Lt5aT/qY4aNUqtDicqKhtDuhzB7flxPV/yFtOwiCcAB3fsyJtnROGEyIwnFDPORSwCJsvtBo1MpNdYxQCudy93eFE2XnXKuDBCSeu1zcULSfNNgfOtAa3cAkn7Vt7ufEfUQRiOKGesofh1vRZQdiL53RNM+xOATEaNdITAz/DTVwh1hGCFWJPtYYsY6wWyYbwGEza/j3LqYDdsgMp4IuwEYUjhhPqKbH5PFxaToC21oCXig5h5bclnR7XLyEWL87PhzG2+0uDuGx9Zoo+KIMwNZrgD4h9e1sJ3i0uRb3VNag0K8UQ1EUYA0l8z/rDpz9gxZfHpW0MIqXlhOGECAwn1HOOMFwmfHRmElZ+W4LTNc04XdP1uJPPD1Tgunxzt88Z7DEa0t46QQwnL6w/hEq3vYnyzF1vA6AkQ/oasf77Cpw63yS1/GjUKvRNjJW5ZIHBcEIEhhPqubYxJ+ETTm4cm4mBafGoa+789/v1r09gy+FKqUWkO8EOJ+ogD4htsNqlYPKXH41BfKwWEwamBOVnBcP904bh0gvSYLU7pNsGpsWjb0LwFpEMJYYTInAqMfWcPQz79jVqFSYM6vrCu7+8FlsOV/Z4XEqww4l7t5nTKQS866j0vKv8SQYdCnL7B/S5QyFGq8ZlQ7teoTichU+nKVEQseWEesoRhuGkJwb4OGi2NIhrnABt3TpAcAbFiuuahMvsnGjDcEKEtnBSy3BC3RAvlOHUrdMTYsgorW7q0fEngz3mROMWToLQtRPMBeSo9xhOiACYDG0tJ0IIpi5SeBIEIeJbTsprmtBi73qr45omGyytWz2EpOUkCOGkNMwWXYs2DCdEaGs5sTkENNkc3RxN0cr9IhlOU4l7Is0YA71OA0EATp3vumtHvLCnxsf0aNqxP9xf3mAMig23FWGjTWT9dRH5KT5GI30S5rgT6oz7RTLCsglUKlWPx52UhmCTvPYDYgON4UTZOFuHCK43ZpNeh+qGFtQ02dDfpJe7SKRAkdxyArjCxsGKOry//RQOVdR1elzxifOu44N4YXfvNQtEy8mxc/X4/MBZCHA9V2kQl96n3mM4IWolhZNGtpyQd+6zRiJtzAkADEqLBwB8svc0Ptl7utvjB6bGB60sKpUKGrUKDqcg7RvTG/e9swt7y2o8bovRqtHfFBnrgkQahhOiVlzrhLojLsAGRN5sHQBYfOlANLU40NBi7/bYhFgtfjRxQFDLo1Gp4IDQ6wGxTqcgtQTNzu2PWJ2r1Wvq8L7QaiKvBSwSMJwQteJaJ9QdsXtBpUJQ9pORW0aSHk9fP0ruYkjUagCO3s/WOVdvhdXuhEatwrIF+dAxkCgezxBRK4YT6o40jThCNldTOnFcT2/DiTj4NSMpjsEkTPAsEbUy6V0NiVyIjTpjd7rW/4jE8SZKJL7MvR0QK64Gm50SvDEyFFgMJ0St2HJC3WnNJhE53kSJxPEgvR0Qy9Vgww/DCVGrJH0MAIYT6hxbTkJL3dp9FqhuHU4bDh8MJ0St2HJC3YnUpeuVSmyhYjiJPpytQ9RKnEp8rt6KU+cbkajXITFOJ3OpSEnsUjjh57pQ0PgRTlrsTpyta/a47SR3IA47DCdErcSWk31ltbjsfzciRqPGqiWTMDIjUeaSkVKIF0mOOQkNMQP2dECs3eHEzGWbcayywev9DCfhg/GfqFVupgkj0hMQq1VDrQJaHE7sPmWRu1ikIOzWCS1xKnFPB8SeOt8kBZNYrdrj36xR6dLu46R8bDkhamWM1eLT+68AADzw7i58uLOM40/Ig/gJXqthOAkFaSqxo2fhRBxbMqyfEev/Z3KwikUhwJYTIi+4lD15w0XYQsvXlhMOfI0cDCdEXnDmDnnDqcShpfZxQGwp1zOJGAwnRF4wnJA34iJsDCehIa4039Nwwlk5kYPhhMgLMZxwKXtyJ7accMxJaGh83FuH3TqRg+GEyIskA1tOqCOOOQktjQ976wiCIHXrZKcynIQ7hhMiL9itQ97YOZU4pHwZEGtptKHOagcAZCYznIQ7TiUm8oLhhLxpW4SNn+tCQd3NmJM//vcgthypBABYbQ4AQL/EWMTpNCEpHwUPwwmRF+5jTpxOQZo1QNGNi7CFVlfL11saW/DKxiMdbs81JwW7WBQCDCdEXojrnDgFoL7Fzj12CIBbywkHxIZEVwNixcGvKfExeH5eHgDX1ONx2cmhKyAFDcMJkRdxOg1itWpY7U7UNNoYTghA25gTNQfEhoSYAbsKJ4PT4nHVhf1CWSwKAXacEnWC406oPYc4lZjdOiEhtZx4GRDLacORjeGEqBNc64Tac3ARtpDSdLErMVeDjWwMJ0SdEMOJheGEWjm4CFtIiSHQ2UW3DltOIpNP4eSGG25AcnIy5s2b5/X+bdu2IScnB0OGDMFTTz0VkAISyYXdOtRe2zon/FwXCj0ZEDuAC65FJJ/+wu677z688cYbnd6/ZMkSvP322zh48CAKCwuxd+/eXheQSC4MJ9Re2wqxMhckSnQ2INbmcKLc0gyALSeRyqfZOlOmTMEXX3zh9b7y8nLY7Xbk5bmmdC1YsABr165Fbm5urwtJJAdxOvGL6w/h6pH9MLiPUeYSkdzYchJa4uu8du9pCGgLKHXNdjicAmK1avRNiJWreBREAZtKXF5eDrPZLH1vNpuxadOmTo8vLi72ervNFl2fUsX6st7Kk2pw/Xm0OJy4/92d+M/PJvb6OcOh3sEQKfW2triWR1erhB7VJVLq7atA1VvVGkh2l1qwu9TS4f6BqQbY7fZe/YxAivbzHUiKW+ekqKhI7iLIgvVWnqQW4IIEDY7WqXC8ogaFhYUBe24l1zuYwr3eu0+qAahxrrwUhYUne/y4cK+3v3pb77JTrtcbAJJiBAw1tbWeqABMSA3s32WgROv5DqSAhZOMjAyUlZVJ35eVlSEjI6PT48ePH+/19unTp0Oni54Fr2w2G4qKilhvhbrc0oQpL2xBs1ONWbOuhqqXi2+FS70DLVLq/dWq/UB5GfJHDkPBlMHdHh8p9fZVoOr97cffY+vZUwCAGXlZeOa6kYEqYlBE8/lesWJFQJ8zoOFEo9Fgz549yMnJwTvvvIPXXnvN5+fR6XRRdVJFrLcypSa4/rc5BDiggT5AG4opvd7BEu71rrO6NpdLMcb6VI9wr7e/eltvnabt721gmjFsXsNoPd+B5NOormnTpuGmm25CYWEhMjMzsXXrVhQUFKC8vBwA8Morr+CWW27BsGHDMHPmTA6GpbBnjNVKay1w1g6JvwPiTC4KLveBx9mcMhxVfGo5+eyzzzrc5t7fN3HiROzfv7/3pSJSCJVKhcQ4Lc432lDTZEO6KU7uIpGMxHCSyHASEhq3j8+cMhxdOB+OqBtc74REbDkJLavdKX3NZeqjC8MJUTcYTkhU08hwEkriQmsAX/Now3BC1I1EhhOCa5XSOqtrTQ1eKEOjzNIkdxFIJgwnRN1gywkBnrtTM5yEht3h7P4gikgMJ0TdYDghoO38G2I00Gn41hkKz92YhwEpBvzttrFyF4VCTHErxBIpjRhOahlOohoHw4be2OxkbH5oqtzFIBkw/hN1gy0nBDCcEIUSwwlRN5IMDCfENU6IQonhhKgbbDkhgC0nRKHEcELUDU4lJqDt/CcxnBAFHcMJUTfYckJA24BotpwQBR/DCVE3GE4IYLcOUSgxnBB1Q7wYtdiduO6VL3HL37/BvrIamUtFoSaFEwPDCVGwMZwQdcMYq0V6oms34t2narD1WBXeLS6VuVQUamw5IQodLsJG1A2VSoXVv5yEfWU1+OzAWby9rQQWdvFEHU4lJgodtpwQ9UC/xDhcdWE/jM1OBsDxJ9GILSdEocNwQuQDDo6NXgwnRKHDcELkA+6zE50cTgF1zXYADCdEocBwQuQDLmUfneqa2843wwlR8DGcEPnAvVtHEASZS0OhIoZRQ4wGOg3fNomCjX9lRD4Qw4nDKaDeape5NBQqHG9CFFoMJ0Q+iNNpEKN1/dmwayd6MJwQhRbDCZGPOGMn+nCNE6LQYjgh8hHDSfSxNLLlhCiUGE6IfMTpxNGH3TpEocVwQuQjtpxEn1qGE6KQYjgh8hHDSfRhywlRaDGcEPmI4ST6MJwQhRbDCZGPEhlOoo54rsUVgokouBhOiHzU1nLCRdiiBacSE4UWwwmRj8Rw8n15DVrsTplLQ6HAbh2i0GI4IfKReIE6eq4BM5dtht3BgBLpGE6IQovhhMhHY7OTMSgtHgBwrLIB1Q0tMpeIgsnhFFDX7OrCYzghCg2GEyIfpcTHYOPSKdLgSA6MjWx1zW3nl+GEKDQYToj8xCnF0UE8v4YYDXQavmUShQL/0oj8xHASHTjehCj0GE6I/MRwEh0YTohCz+dwsnbtWgwfPhxDhw7F8uXLO9w/ZcoUjBgxAvn5+cjPz0dTU1NACkqkNFyMLTpwjROi0NP6crDdbscDDzyAjRs3wmQyYezYsbjhhhuQmprqcdwHH3yAUaNGBbSgRErDlpPowJYTotDzqeVk27ZtyMnJgdlshtFoxKxZs7B+/fpglY1I0RhOogPDCVHo+dRyUl5eDrPZLH1vNptRVlbW4bhbb70VGo0GCxcuxAMPPOD1uYqLi73ebrNF1xu9WF/WO/wYY1zZ3tJg7XE9IqHe/gjnep+vtwIAEmI1Ppc/nOvdG6x3dNY7kHwKJz2xcuVKmM1m1NTUYM6cORg+fDhmz57d48cXFRUFukhhgfUOPyUVKgAaHD5ZhsLCUp8eG8717o1wrPe+o2oAalSUHkNh4VG/niMc6x0IrDf5y6dwkpGR4dFSUlZWhgkTJngcI7asmEwm3HzzzSguLvYaTsaPH+/1Z0yfPh06XfQ0n9psNhQVFbHeYUi17wzePbYHcYkpKCiY0P0DEBn19kc413vdO7uBsxUYl5eDgokDfHpsONe7N1jv6Kv3ihUrAvqcPoWTCRMmYN++fSgrK4PJZMK6devw+OOPS/fb7XZYLBakpaWhpaUF69atw6JFi3wqkE6ni6qTKmK9w09qgh4AUNts97kO4Vzv3gjHetdZXUvXpxjj/C57ONY7EFhv8pdP4USr1eKFF17A1KlT4XQ68dBDDyE1NRUFBQVYvnw5TCYTZsyYAZvNBofDgWuvvRbz5s0LVtmJZMUBsdHB0sgBsUSh5vOYkzlz5mDOnDketxUWFkpf79ixo/elIgoDDCfRgeucEIUeV4gl8pN4sWq2OdFsc8hcGgoWTiUmCj2GEyI/JcRqoVK5vq5l60lEcjgF1DW7xpyIu1ATUfAxnBD5Sa1WITGOXTuRrK657byy5YQodBhOiHpBvGD99YujHhcyigxi6DTEaKDT8O2SKFT410bUC30SYgEAH+4sw+tfnZC3MBRwHG9CJA+GE6Je+HXBCOnrMgt34I40DCdE8mA4IeqFsdkp+N2cHAAcdxKJOI2YSB4MJ0S9xPVOIhdbTojkwXBC1EsMJ5GL4YRIHgwnRL1kMjCcRCqGEyJ5MJwQ9RJbTiJXLcMJkSwYToh6Sbxw1TXb4XAKMpeGAoktJ0TyYDgh6iX3CxcXYossDCdE8mA4IeolnUYNQ4wGALt2Ig3DCZE8GE6IAoDjTiIT1zkhkgfDCVEAMJxEpppGtpwQyYHhhCgAEhlOIo7TKaDOagfAcEIUagwnRAHAlpPIU9dsh9A6+YrhhCi0GE6IAoDhJPKI51Kv0yBGy7dKolDiXxxRADCcRB5LUwsAtpoQyYHhhCgAxAtYLcNJxBCDZpKB4YQo1BhOiAKALSeRh9OIieTDcEIUAGI4Kdx7Bi+sPyhzaSgQuAAbkXwYTogCYEhfo/T1yxuOoKF1CiqFL4YTIvkwnBAFwCizCWvvuUz6nt074Y/hhEg+DCdEATLKbEJqfAwAhpNIUMtwQiQbhhOiAOLA2MjBlhMi+TCcEAUQl7GPHAwnRPJhOCEKILacRA6GEyL5MJwQBZC4YBcXYwt/XOeESD4MJ0QBxJaTyFHTyJYTIrkwnBAFEMNJZHA6BdS1rlXDcEIUegwnRAHEcBIZ6prtEATX1wwnRKHHcEIUQJytExnE86fXaRCj5dskUajxr44ogNhyEhk4U4dIXgwnRAHEcBIZGE6I5MVwQhRA4sWMU4nDG8MJkbwYTogCSLyYWRptEMQRlRR2uMYJkbx8Didr167F8OHDMXToUCxfvrzD/du2bUNOTg6GDBmCp556KiCFJAoXYjixOwU0tjhkLg35iy0nRPLyKZzY7XY88MAD2LBhA3bu3Innn38eVVVVHscsWbIEb7/9Ng4ePIjCwkLs3bs3oAUmUjJDjAZatQoAx52EM/HciSv+ElFoaX05WGwVMZvNAIBZs2Zh/fr1uOWWWwAA5eXlsNvtyMvLAwAsWLAAa9euRW5uboCLTaRMKpUKSQYdKutbcPhsPZztunbsdjuqrUCZpQlabfSEl3Cr9+maJgBsOSGSi0/hpLy8XAomAGA2m1FWVtbl/Zs2bfL6XMXFxV5vt9mU/8YVSGJ9We/IkRinRWV9Cxb9Y1snR2jxu++2hLRMyhB+9TbGqHv1OxrJv+ddYb2js96B5FM4CYWioiK5iyAL1jtyjNCrcEqtBsfDhrd4HWAv24fCwn29fq5I/D3vCdab/OVTOMnIyPBoKSkrK8OECRO6vD8jI8Prc40fP97r7dOnT4dOFz1NqTabDUVFRax3BCno4r5IrndXWG/WOxpEc71XrFgR0Of0KZxMmDAB+/btQ1lZGUwmE9atW4fHH39cuj8jIwMajQZ79uxBTk4O3nnnHbz22ms+FUin00XVSRWx3tGF9Y4urHd0idZ6B5JPs3W0Wi1eeOEFTJ06Ffn5+XjwwQeRmpqKgoIClJeXAwBeeeUV3HLLLRg2bBhmzpzJwbBERETkE5/HnMyZMwdz5szxuK2wsFD6euLEidi/f3/vS0ZERERRiSvEEhERkaIwnBAREZGiMJwQERGRojCcEBERkaIwnBAREZGiMJwQERGRojCcEBERkaIwnBAREZGiMJwQERGRojCcEBERkaIwnBAREZGiMJwQERGRoqgEQRDkLgQAFBcXY/78+Rg1apTcRQkpi8UCAEhKSpK1HKHGeifJWo5QY72TZC1HqLHeSbKWI9QsFgtOnTqFY8eOBew5fd6VOJjeffddjB8/Xu5ihFRxcTEAsN5RgvVmvaMB6x2d9Q4kdusQERGRojCcEBERkaIwnBAREZGiKGZALBERERHAlhMiIiJSGIYTIiIiUhSGEyIiIlIUhhMiIiJSlJCHkyVLlqBfv34YN26cx+1Hjx7FuHHjMGTIEPz85z+Ht3G6lZWVmDp1KoYOHYq5c+eiubk5VMUOmLq6OuTn50v/TCYTli1b1uG4J598EpmZmdJxW7ZsCX1hA2zKlCkYMWKEVKempqYOx0TCOXbX2NiIWbNmYcSIEcjJycHLL7/s9bhIOt9r167F8OHDMXToUCxfvrzD/du2bUNOTg6GDBmCp556SoYSBl5paSmmTJmCkSNHIi8vD++//36HYxYvXozBgwdL5/jo0aMylDTwBg4ciLy8POTn52Pq1Kkd7u/Je3u4OXjwoMf7uF6vx6pVqzyOiaTzfcMNNyA5ORnz5s2TbuvJ33Gvzr0QYl9++aWwfft2YezYsR6333jjjcLHH3/c4Wt3Dz74oPDyyy93+DpcOZ1OYcCAAcKxY8c63PfEE0+Eff3amzx5srB3794uj4m0c9zQ0CB88cUXgiAIQl1dnTB8+HDh8OHDHY6LlPNts9mEoUOHCqdOnRLq6uqEYcOGCZWVlR7HjBs3Tti9e7dgt9uFiy++WNizZ49MpQ2c8vJyYefOnYIgCMLp06eFjIwMob6+3uOYRYsWeX1fC3fZ2dlCXV1dp/f35L09nNXV1QmpqakRfb43btworFmzRrjxxhul23ryd9ybcx/ylpNJkyYhNTW1fUDC119/jdmzZwMAbrvtNnz88ccdHrtmzRosXLiwy2PCydatW5Geno5BgwbJXRTFiLRzbDAYMHnyZACA0WjE8OHDcfr0aZlLFTzipymz2Qyj0YhZs2Zh/fr10v3l5eWw2+3Iy8uDRqPBggULsHbtWhlLHBj9+/dHfn4+ACA9PR1paWmorq6Wt1AK0NP39nC2Zs0aXHXVVYiPj5e7KEEzZcoUJCQkSN/35O+4t+deEWNOqqqqkJKSApVKBQAwm80oKyvrcFxNTQ1MJlOXx4ST9957D/Pnz+/0/hdffBF5eXm4++67UV9fH8KSBc+tt96Kiy66CC+++KLX+yPtHLsrLS3Fnj17MGbMGK/3R8L5Li8vh9lslr5vfw67uz8S7NixAw6HA1lZWR3uW7p0KUaPHo1HH30UDodDhtIFnkqlwuTJkzF+/HisXLnS476evreHs67exyPxfAM9+zvu7bkPysZ/+fn5sNvtHW5fv349MjIygvEjFae710AQBPznP//B1q1bvT7+7rvvxuOPPw4AeOihh/C73/0Ozz//fFDLHAhd1XvlypUwm82oqanBnDlzMHz4cClVh7vuzrfVasX8+fPx/PPPe/2EFa7nmzxVV1fj9ttvx2uvvdbhvt///vdIT0+H1WrFokWL8Le//Q1LliyRoZSB9eWXX8JsNuP06dOYNm0acnNzkZeXJ3exQqK2thZff/013nnnnQ73Rer5DpWghJNdu3b5dHxqaiqqq6shCAJUKhXKysq8hhiTySR9su7sGKXo7jX48ssvkZ2djczMTK/39+vXT/r6Jz/5Sdj8Uvfk3JtMJtx8880oLi7uEE7C6Ry766regiDg9ttvR0FBgceAMnfher7by8jI8Ph0VFZWhgkTJnR5f7ic4+5YrVZcf/31eOSRR3DppZd2uL9///4AgLi4ONx+++1eB82GI/ETdP/+/VFQUIDvvvtOCic9fW8PV6tXr8bVV1+NuLi4DvdF6vkGevZ33Ntzr4huHZVKhYkTJ+KTTz4BAKxcuRLXXntth+OuueYavPnmmwCAf//7316PCRfddem4j0tYvXo1cnJyQlGsoLHb7aisrAQAtLS0YN26dV7rFEnnWPToo4/CYDDgN7/5TafHRMr5njBhAvbt24eysjLU19dj3bp1mDFjhnR/RkYGNBoN9uzZA4fDgXfeeScizrEgCFi8eDGuvPJKacxUe+I5djqdWLNmTdieY3cNDQ2oq6sDANTX12PDhg0e9erpe3u46up9PBLPt6gnf8e9Pvd+D9/106JFi4T09HRBp9MJZrNZeO+99wRBEIRDhw4JY8aMEQYPHizcddddgsPhEARBEB5//HFh9erVgiAIwtmzZ4UrrrhCuOCCC4TrrrtOaGxsDHXxA8LhcAhms1koLy/3uN29rrfddpswatQoITc3V7jxxhuFqqoqOYoaMPX19cKYMWOE3NxcYeTIkcLDDz8sOJ1OQRAi8xyLSktLBQDCyJEjhdGjRwujR48WPv30U0EQIvd8r169Whg6dKhwwQUXCK+++qogCIIwa9YsoaysTBAEQdi6daswcuRIYfDgwcITTzwhY0kDZ8uWLYJKpZLO8ejRo4U9e/YId9xxh1BcXCwIgiBMnTpVyM3NFXJycoQ77rhDaG5ulrnUvXf06FEhLy9PyMvLE3JycoRly5YJgiB41Luz9/ZwZ7FYhL59+wpWq1W6LVLP91VXXSWkpaUJer1eMJvNwtdff93p33Ggzj03/iMiIiJFUUS3DhEREZGI4YSIiIgUheGEiIiIFIXhhIiIiBSF4YSIiIgUheGEiIiIFIXhhChKabVaj23f33jjDbmLBMC1PXt5eXmn9y9evLhDWV944QUsXboURUVF+O1vfxvsIhJRkDGcEEWppKQk7Nq1S/p3++239/o5e7u52a5du6DX67tc5nr+/Pl47733PG579913MX/+fEyfPh2ffvopmpqaelUOIpIXwwkReUhLS8PSpUuRm5uLq666Cg0NDQCAo0ePYsaMGRg3bhyuvPJKnDhxAoBrO/X7778f48aNw5tvvonVq1dj2LBhGD9+PO644w4sXboUR44c8dhv5vPPP/e6z9Bbb72F6667Tvr+v//9Ly655BJcdNFFuO2229DS0oJp06bhu+++Q01NDQDgxIkTqKqqwvjx4wEAV1xxBdatWxesl4eIQoDhhChKWSwWj26djRs3AnBtdT5z5kzs3bsXZrMZH374IQDgF7/4BV599VVs374dv/nNb/CrX/1Kei6dToft27dj/vz5uPfee7FhwwZs3boVR48eBQAMGTIEOp0Ohw4dAgC88cYbWLRoUYcyffPNNxgzZgwAoLKyEs8//zw2bNiAnTt3YvDgwXjttdeg0+kwe/ZsrFq1CoBrf5Obb75Zeo4xY8bg66+/DvwLRkQhE5RdiYlI+cRunfaMRiOmTZsGABg7dixOnDiB+vp6bNmyBddffz0A10Z38fHx0mNuuukmAMDBgwcxYsQIabftG2+8ESdPngTQNlbk0UcfxZdffokVK1Z0+NlnzpxBnz59ALiCyp49e3DJJZcAcO36K+5iPX/+fCxbtgyLFi3Ce++9h+XLl0vP0adPH4+NFIko/DCcEJGH2NhY6WuNRgOHwwGn04l+/fp5DTMAYDAYALhCS2duuukmXHzxxRg2bBjmzJkDrbbj209cXByam5sBuHZznT17Nv75z392OG7q1Kn48Y9/jO+++w719fXIz8+X7mtuboZer+9JVYlIoditQ0TdSkxMRL9+/fDxxx8DcA183bdvX4fjRowYgR9++AFlZWVwOBxSlxDgapGZMGECHnnkEa9dOuLjjxw5AgC45JJLsHHjRqnlpba2FsePHwfgCk3XXnstfvzjH3t06QDAkSNHcOGFF/a+0kQkG4YToijVfszJSy+91OXxb731Fl5++WWMHj0aubm5+Pzzzzsco9frsWzZMkydOhUTJ05EZmYmEhMTpfsXLFiAtLQ0j5YOdzNnzsSmTZsAuLpnXnvtNdx4443Iy8vDFVdcIQUVwNW1s2fPHsyfP9/jOTZv3oxZs2b19GUgIgVSCV21wxIR+ai+vh5GoxEOhwNz587FXXfdhWuuuQYA8OSTTyI5ORn33Xdfp4+dNWsWNm/eDJVK5fPPrqysxK233or169f3qg5EJC+GEyIKqOeffx4rV66E1WrFtGnT8Oc//xkqlQqzZs1CZWUlNm7cCKPR2OnjCwsLMWbMGKSnp/v8s3fu3AmVStVpywwRhQeGEyIiIlIUjjkhIiIiRWE4ISIiIkVhOCEiIiJFYTghIiIiRWE4ISIiIkVhOCEiIiJFYTghIiIiRWE4ISIiIkVhOCEiIiJF+f/flHDyleJIlgAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import torch\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "output = \"./negf_output_k20\"\n",
+    "results_path = os.path.join(output, 'negf.out.pth')\n",
+    "if os.path.exists(results_path) is False:\n",
+    "    raise FileNotFoundError(f\"Results file {results_path} not found. Please check if the NEGF calculation was successful.\")\n",
+    "negf_out = torch.load(results_path,weights_only=False)\n",
+    "\n",
+    "plt.plot(negf_out['uni_grid'], negf_out['T_avg'])\n",
+    "plt.xlabel('Energy (eV)')\n",
+    "plt.title('Total Transmission kmesh=[1,20,1]')\n",
+    "plt.xlim(-10,10)\n",
+    "plt.grid()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "23fa774f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Increase k-point sampling for better accuracy\n",
+    "negf_json['task_options'][\"stru_options\"]['kmesh'] = [1,70,1]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b49850ab",
+   "metadata": {},
+   "source": [
+    "Considering the computing cost, we don't recommend you to run the cell from scratch(more than 40 mins in a 32-core CPU). We have prepared the self-energies files and you can directly load it with `use_saved_se`=True. However, it also takes ~20 mins in a 32-core CPU."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "31e78258",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "DPNEGF INFO    ------ k-point for NEGF -----\n",
+      "DPNEGF INFO    Gamma Center: False\n",
+      "DPNEGF INFO    Time Reversal: True\n",
+      "DPNEGF INFO    k-points Num: 35\n",
+      "DPNEGF INFO    --------------------------------\n",
+      "DPNEGF INFO    The AtomicData_options is:\n",
+      "               {\n",
+      "                   \"r_max\": {\n",
+      "                       \"B-B\": 4.82,\n",
+      "                       \"B-N\": 4.640000000000001,\n",
+      "                       \"N-B\": 4.640000000000001,\n",
+      "                       \"N-N\": 4.45\n",
+      "                   },\n",
+      "                   \"er_max\": null,\n",
+      "                   \"oer_max\": 6.3\n",
+      "               }\n",
+      "DPNEGF INFO    The structure is sorted lexicographically in this version!\n",
+      "DPNEGF INFO    Lead principal layers translational equivalence error (on average): 3.803219e-09 (threshold: 1.000000e-05)\n",
+      "DPNEGF INFO    Lead principal layers translational equivalence error (on average): 2.120221e-09 (threshold: 1.000000e-05)\n",
+      "DPNEGF INFO    The coupling width of lead_L is 54.\n",
+      "DPNEGF WARNING WARNING, the lead's hamiltonian attained from diffferent methods have slight differences   RMSE = 0.0000001.\n",
+      "DPNEGF INFO    The coupling width of lead_R is 54.\n",
+      "DPNEGF WARNING WARNING, the lead's hamiltonian attained from diffferent methods have slight differences   RMSE = 0.0000003.\n",
+      "DPNEGF INFO    The Hamiltonian is block tridiagonalized into 5 subblocks.\n",
+      "DPNEGF INFO       the number of elements in subblocks: 43092\n",
+      "DPNEGF INFO                   occupation of subblocks: 51.953125 %\n",
+      "DPNEGF INFO    --------------------------------------------------------------------------------\n",
+      "DPNEGF INFO    The Hamiltonian has been initialized by model.\n",
+      "DPNEGF INFO    ================================================================================\n",
+      "DPNEGF INFO    -------------Fermi level calculation-------------\n",
+      "DPNEGF WARNING No doping detected in lead_L, fixed_charge = 0\n",
+      "DPNEGF WARNING No doping detected in lead_R, fixed_charge = 0\n",
+      "DPNEGF INFO    Number of electrons in lead_L: {'B': 3, 'N': 5}\n",
+      "DPNEGF INFO    Number of electrons in lead_R: {'B': 3, 'N': 5}\n",
+      "DPNEGF INFO    -----Calculating Fermi level for lead_L-----\n",
+      "DPNEGF INFO    KPOINTS  kmesh sampling: 535 kpoints\n",
+      "DPNEGF INFO    Getting eigenvalues from the model.\n",
+      "DPNEGF INFO    Calculating Fermi energy in the case of spin-degeneracy.\n",
+      "DPNEGF INFO    Fermi energy converged after 3 iterations.\n",
+      "DPNEGF INFO    q_cal: 128.00000000000006, total_electrons: 128.0, diff q: 5.684341886080802e-14\n",
+      "DPNEGF INFO    Estimated E_fermi: -2.8707102673203666 based on the valence electrons setting nel_atom : {'B': 3, 'N': 5} .\n",
+      "DPNEGF INFO    -----Calculating Fermi level for lead_R-----\n",
+      "DPNEGF INFO    KPOINTS  kmesh sampling: 535 kpoints\n",
+      "DPNEGF INFO    Getting eigenvalues from the model.\n",
+      "DPNEGF INFO    Calculating Fermi energy in the case of spin-degeneracy.\n",
+      "DPNEGF INFO    Fermi energy converged after 3 iterations.\n",
+      "DPNEGF INFO    q_cal: 128.00000000000006, total_electrons: 128.0, diff q: 5.684341886080802e-14\n",
+      "DPNEGF INFO    Estimated E_fermi: -2.870709075227471 based on the valence electrons setting nel_atom : {'B': 3, 'N': 5} .\n",
+      "DPNEGF INFO    -------------------------------------------------\n",
+      "DPNEGF INFO    Zero bias case detected.\n",
+      "DPNEGF INFO    Fermi level for lead_L: -2.8707102673203666\n",
+      "DPNEGF INFO    Fermi level for lead_R: -2.870709075227471\n",
+      "DPNEGF INFO    Electrochemical potential for lead_L: -2.8707102673203666\n",
+      "DPNEGF INFO    Electrochemical potential for lead_R: -2.870709075227471\n",
+      "DPNEGF INFO    Reference energy E_ref: -2.8707102673203666\n",
+      "DPNEGF INFO    =================================================\n",
+      "\n",
+      "DPNEGF INFO    ------Self-energy calculation------\n",
+      "DPNEGF INFO    Using saved self-energy from ./negf_output_k70/self_energy\n",
+      "DPNEGF INFO    Ensure the saved self-energy is consistent with the current calculation setting!\n",
+      "DPNEGF INFO    -----------------------------------\n",
+      "\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.0071,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.0214,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.0357,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.0500,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.0643,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.0786,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.0929,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.1071,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.1214,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.1357,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.1500,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.1643,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.1786,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.1929,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.2071,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.2214,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.2357,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.2500,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.2643,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.2786,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.2929,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.3071,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.3214,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.3357,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.3500,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.3643,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.3786,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.3929,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.4071,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.4214,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.4357,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.4500,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.4643,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.4786,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,0.4929,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "output = \"./negf_output_k70\"  \n",
+    "os.makedirs(output, exist_ok=True)\n",
+    "\n",
+    "negf = NEGF(\n",
+    "    model=model,\n",
+    "    structure=structure,\n",
+    "    results_path=output,\n",
+    "    use_saved_se=True, # whether to use the saved self-energy  \n",
+    "    se_info_display=False,\n",
+    "    **negf_json['task_options']\n",
+    ")\n",
+    "   \n",
+    "negf.compute()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dfea2116",
+   "metadata": {},
+   "source": [
+    "The transmissions resulted from DFT-NEGF and DPNEGF match very well."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "11fbd9d1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import torch\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "\n",
+    "output = \"./negf_output_k70\"\n",
+    "results_path = os.path.join(output, 'negf.out.pth')\n",
+    "if os.path.exists(results_path) is False:\n",
+    "    raise FileNotFoundError(f\"Results file {results_path} not found. Please check if the NEGF calculation was successful.\")\n",
+    "negf_out = torch.load(results_path,weights_only=False)\n",
+    "\n",
+    "\n",
+    "data = np.loadtxt('./siesta.TBT.AVTRANS_Left-Right', comments=\"#\")\n",
+    "E_tbt = data[:, 0]   # eV\n",
+    "T_tbt = data[:, 1]   # G0\n",
+    "\n",
+    "energy_shift = 0.65 # arising from the different Fermi level algorithm; for semiconductor, the Fermi level is arbitrary in the gap.\n",
+    "\n",
+    "plt.plot(negf_out['uni_grid'] , negf_out['T_avg'],label='DPNEGF')\n",
+    "plt.plot(E_tbt + energy_shift, T_tbt,'--', label=r'DFT-NEGF')\n",
+    "plt.xlabel('Energy (eV)')\n",
+    "plt.title('Total Transmission kmesh=[1,70,1]')\n",
+    "plt.xlim(-10,10)\n",
+    "plt.ylim(0,4)\n",
+    "plt.grid()\n",
+    "plt.legend(loc='upper center')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "939bb098",
+   "metadata": {},
+   "source": [
+    "The transmission spectrum of hBN clearly shows a wide plateau of zero transmission around the Fermi level. This feature directly corresponds to the band gap observed in the previously calculated electronic band structure."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "05e286ca",
+   "metadata": {},
+   "source": [
+    "## 3. Quantum Transport in MoS<sub>2</sub>\n",
+    "\n",
+    "DPNEGF can perform NEGF calculations using electronic structures from any DFT software. For codes without NEGF support (e.g., plane-wave DFT such as VASP), DeePTB extracts the electronic outputs and converts them into NEGF-ready Hamiltonians. Compared with Wannierization, DeePTB offers a faster and more transferable way to construct Hamiltonians.\n",
+    "\n",
+    "Here, we use the MoS<sub>2</sub> band structure from ABACUS and compute the corresponding transmission spectrum, demonstrating how DPNEGF enables NEGF analysis even when the original DFT code does not provide it."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "56cc32bb",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "DPNEGF INFO    ================================================================================\n",
+      "DPNEGF INFO                                      Version Info                                  \n",
+      "DPNEGF INFO    --------------------------------------------------------------------------------\n",
+      "DPNEGF INFO    DPNEGF               : 0.1.1.dev148+0e0863a\n",
+      "DPNEGF INFO    DeePTB               : 2.2.1.dev17+024a5fe\n",
+      "DPNEGF INFO    ================================================================================\n",
+      "\n",
+      "DPNEGF INFO    The ['overlap_param'] are frozen!\n",
+      "DPNEGF INFO    The ['overlap_param'] are frozen!\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "MoS2_orth.vasp\tMoS2_unit_rlx.vasp\tPOSCAR\tband_plot_api\textra_baseline\tnegf.json\tnegf_output\torth_ckpt_r_max_5.3_sk.json\tstru_negf.xyz\ttrain\n",
+      "Atoms(symbols='MoS2', pbc=True, cell=[[3.1911949999999996, 0.0, 0.0], [-1.595598, 2.763656, 0.0], [-0.0, -0.0, 18.12711]], momenta=...)\n"
+     ]
+    }
+   ],
+   "source": [
+    "import os\n",
+    "from pathlib import Path\n",
+    "from dptb.nn.build import build_model\n",
+    "from ase.io import read\n",
+    "from dpnegf.utils.loggers import set_log_handles\n",
+    "import logging\n",
+    "from pathlib import Path\n",
+    "\n",
+    "\n",
+    "workdir='../../examples/MoS2'\n",
+    "wd = Path(workdir)\n",
+    "if not wd.is_dir():\n",
+    "    raise FileNotFoundError(f\"Workdir '{wd}' not found. Please adjust 'workdir'.\")\n",
+    "os.chdir(wd)\n",
+    "print(\"\\t\".join(sorted(os.listdir(\".\"))))\n",
+    "\n",
+    "results_path = 'band_plot_api'\n",
+    "log_path = os.path.join(results_path, 'log')\n",
+    "log_level = logging.INFO\n",
+    "set_log_handles(log_level, Path(log_path) if log_path else None)\n",
+    "\n",
+    "\n",
+    "model =  \"./train/train_out/checkpoint/nnsk.best.pth\" # the model for demonstration\n",
+    "model = build_model(model)\n",
+    "\n",
+    "# read the structure\n",
+    "structure =  \"./train/data/POSCAR\" \n",
+    "atoms = read(structure)\n",
+    "print(atoms)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "c18dbecf",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "DPNEGF WARNING eig_solver is not set, using default 'torch'.\n",
+      "DPNEGF INFO    KPOINTS  klist: 91 kpoints\n",
+      "DPNEGF INFO    The eigenvalues are already in data. will use them.\n",
+      "DPNEGF INFO    Calculating Fermi energy in the case of spin-degeneracy.\n",
+      "DPNEGF INFO    Fermi energy converged after 3 iterations.\n",
+      "DPNEGF INFO    q_cal: 18.0, total_electrons: 18.0, diff q: 0.0\n",
+      "DPNEGF INFO    Estimated E_fermi: -3.256112973973428 based on the valence electrons setting nel_atom : {'Mo': 6, 'S': 6} .\n",
+      "DPNEGF INFO    No Fermi energy provided, using estimated value: -3.2561 eV\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x560 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from dptb.postprocess.bandstructure.band import Band\n",
+    "\n",
+    "\n",
+    "task_options = {\n",
+    "        \"task\": \"band\",\n",
+    "        \"kline_type\":\"abacus\",\n",
+    "        \"kpath\":[\n",
+    "            [0, 0, 0, 30],\n",
+    "            [0.5, 0, 0, 30],\n",
+    "            [0.3333333, 0.3333333, 0, 30],\n",
+    "            [0, 0, 0, 1]\n",
+    "        ],\n",
+    "        \"klabels\":[\"G\", \"M\", \"K\", \"G\"],\n",
+    "        \"emin\":-15,\n",
+    "        \"emax\":5,\n",
+    "        \"nel_atom\":{\"Mo\":6,\"S\":6},\n",
+    "        \"ref_band\": \"./train/data/kpath.0/eigenvalues.npy\"\n",
+    "\n",
+    "       }\n",
+    "\n",
+    "\n",
+    "\n",
+    "band = Band(model, results_path)\n",
+    "AtomicData_options = { \"pbc\": True}\n",
+    "band.get_bands(data = atoms, \n",
+    "               kpath_kwargs = task_options,\n",
+    "               AtomicData_options = AtomicData_options)\n",
+    "band.band_plot(emin = task_options['emin'],\n",
+    "               emax = task_options['emax'],\n",
+    "               ref_band = task_options['ref_band'],)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "a7e93b3a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "try:\n",
+    "    from dpnegf.runner.NEGF import NEGF\n",
+    "except ImportError as e:\n",
+    "    raise ImportError(\"dpnegf not found. Please install firstly.\") from e\n",
+    "\n",
+    "import json\n",
+    "negf_input_file =  \"negf.json\" \n",
+    "structure =  \"stru_negf.xyz\" \n",
+    "\n",
+    "with open(negf_input_file, \"r\") as f:\n",
+    "    negf_json = json.load(f)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "77f83787",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "DPNEGF INFO    The AtomicData_options is:\n",
+      "               {\n",
+      "                   \"r_max\": {\n",
+      "                       \"S-S\": 6.26,\n",
+      "                       \"S-Mo\": 6.449999999999999,\n",
+      "                       \"Mo-S\": 6.449999999999999,\n",
+      "                       \"Mo-Mo\": 6.630000000000001\n",
+      "                   },\n",
+      "                   \"er_max\": null,\n",
+      "                   \"oer_max\": 6.3\n",
+      "               }\n"
+     ]
+    }
+   ],
+   "source": [
+    "AtomicData_options = NEGF.update_atomicdata_options(model)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "36423f15",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Increase k-point sampling for better accuracy\n",
+    "negf_json['task_options'][\"stru_options\"]['kmesh'] = [1,1,1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "a7e5e72a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "DPNEGF INFO    ------ k-point for NEGF -----\n",
+      "DPNEGF INFO    Gamma Center: False\n",
+      "DPNEGF INFO    Time Reversal: True\n",
+      "DPNEGF INFO    k-points Num: 1\n",
+      "DPNEGF INFO    k-points: [[-0. -0. -0.]]\n",
+      "DPNEGF INFO    k-points weights: [1.]\n",
+      "DPNEGF INFO    --------------------------------\n",
+      "DPNEGF INFO    The AtomicData_options is:\n",
+      "               {\n",
+      "                   \"r_max\": {\n",
+      "                       \"S-S\": 6.26,\n",
+      "                       \"S-Mo\": 6.449999999999999,\n",
+      "                       \"Mo-S\": 6.449999999999999,\n",
+      "                       \"Mo-Mo\": 6.630000000000001\n",
+      "                   },\n",
+      "                   \"er_max\": null,\n",
+      "                   \"oer_max\": 6.3\n",
+      "               }\n",
+      "DPNEGF INFO    The structure is sorted lexicographically in this version!\n",
+      "DPNEGF INFO    Lead principal layers translational equivalence error (on average): 2.849356e-09 (threshold: 1.000000e-05)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "DPNEGF INFO    Lead principal layers translational equivalence error (on average): 4.413665e-09 (threshold: 1.000000e-05)\n",
+      "DPNEGF INFO    The coupling width of lead_L is 54.\n",
+      "DPNEGF WARNING WARNING, the lead's hamiltonian attained from diffferent methods have slight differences   RMSE = 0.0000001.\n",
+      "DPNEGF INFO    The coupling width of lead_R is 54.\n",
+      "DPNEGF INFO    The Hamiltonian is block tridiagonalized into 3 subblocks.\n",
+      "DPNEGF INFO       the number of elements in subblocks: 34992\n",
+      "DPNEGF INFO                   occupation of subblocks: 75.0 %\n",
+      "DPNEGF INFO    --------------------------------------------------------------------------------\n",
+      "DPNEGF INFO    The Hamiltonian has been initialized by model.\n",
+      "DPNEGF INFO    ================================================================================\n",
+      "DPNEGF INFO    -------------Fermi level calculation-------------\n",
+      "DPNEGF WARNING No doping detected in lead_L, fixed_charge = 0\n",
+      "DPNEGF WARNING No doping detected in lead_R, fixed_charge = 0\n",
+      "DPNEGF INFO    Number of electrons in lead_L: {'Mo': 6, 'S': 6}\n",
+      "DPNEGF INFO    Number of electrons in lead_R: {'Mo': 6, 'S': 6}\n",
+      "DPNEGF INFO    -----Calculating Fermi level for lead_L-----\n",
+      "DPNEGF INFO    KPOINTS  kmesh sampling: 535 kpoints\n",
+      "DPNEGF INFO    Getting eigenvalues from the model.\n",
+      "DPNEGF INFO    Calculating Fermi energy in the case of spin-degeneracy.\n",
+      "DPNEGF INFO    Fermi energy converged after 3 iterations.\n",
+      "DPNEGF INFO    q_cal: 144.00000000000003, total_electrons: 144.0, diff q: 2.842170943040401e-14\n",
+      "DPNEGF INFO    Estimated E_fermi: -3.2348815338761527 based on the valence electrons setting nel_atom : {'Mo': 6, 'S': 6} .\n",
+      "DPNEGF INFO    -----Calculating Fermi level for lead_R-----\n",
+      "DPNEGF INFO    KPOINTS  kmesh sampling: 535 kpoints\n",
+      "DPNEGF INFO    Getting eigenvalues from the model.\n",
+      "DPNEGF INFO    Calculating Fermi energy in the case of spin-degeneracy.\n",
+      "DPNEGF INFO    Fermi energy converged after 3 iterations.\n",
+      "DPNEGF INFO    q_cal: 144.00000000000003, total_electrons: 144.0, diff q: 2.842170943040401e-14\n",
+      "DPNEGF INFO    Estimated E_fermi: -3.234879864946099 based on the valence electrons setting nel_atom : {'Mo': 6, 'S': 6} .\n",
+      "DPNEGF INFO    -------------------------------------------------\n",
+      "DPNEGF INFO    Zero bias case detected.\n",
+      "DPNEGF INFO    Fermi level for lead_L: -3.2348815338761527\n",
+      "DPNEGF INFO    Fermi level for lead_R: -3.234879864946099\n",
+      "DPNEGF INFO    Electrochemical potential for lead_L: -3.2348815338761527\n",
+      "DPNEGF INFO    Electrochemical potential for lead_R: -3.234879864946099\n",
+      "DPNEGF INFO    Reference energy E_ref: -3.2348815338761527\n",
+      "DPNEGF INFO    =================================================\n",
+      "\n",
+      "DPNEGF INFO    ------Self-energy calculation------\n",
+      "DPNEGF INFO    Calculating self-energy and saving to ./negf_output/self_energy\n",
+      "DPNEGF INFO    Merging 400 tmp self energy files into ./negf_output/self_energy/self_energy_leadL.h5\n",
+      "DPNEGF INFO    Merge complete.\n",
+      "DPNEGF INFO    Merging 400 tmp self energy files into ./negf_output/self_energy/self_energy_leadR.h5\n",
+      "DPNEGF INFO    Merge complete.\n",
+      "DPNEGF INFO    -----------------------------------\n",
+      "\n",
+      "DPNEGF INFO    Properties computation at k = [-0.0000,-0.0000,-0.0000]\n",
+      "DPNEGF INFO    computing green's function at e = -10.000\n",
+      "DPNEGF INFO    computing green's function at e = -7.995\n",
+      "DPNEGF INFO    computing green's function at e = -5.990\n",
+      "DPNEGF INFO    computing green's function at e = -3.985\n",
+      "DPNEGF INFO    computing green's function at e = -1.980\n",
+      "DPNEGF INFO    computing green's function at e = 0.025\n",
+      "DPNEGF INFO    computing green's function at e = 2.030\n",
+      "DPNEGF INFO    computing green's function at e = 4.035\n",
+      "DPNEGF INFO    computing green's function at e = 6.040\n",
+      "DPNEGF INFO    computing green's function at e = 8.045\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import shutil\n",
+    "output = \"./negf_output\"  \n",
+    "if os.path.isdir(output):\n",
+    "    shutil.rmtree(output, ignore_errors=True)\n",
+    "os.makedirs(output, exist_ok=True)\n",
+    "\n",
+    "negf = NEGF(\n",
+    "    model=model,\n",
+    "    structure=structure,\n",
+    "    results_path=output,\n",
+    "    use_saved_se=False, # whether to use the saved self-energy  \n",
+    "    se_info_display=False,\n",
+    "    **negf_json['task_options']\n",
+    ")\n",
+    "   \n",
+    "negf.compute()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "a659a576",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import torch\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "output = \"./negf_output\"\n",
+    "results_path = os.path.join(output, 'negf.out.pth')\n",
+    "if os.path.exists(results_path) is False:\n",
+    "    raise FileNotFoundError(f\"Results file {results_path} not found. Please check if the NEGF calculation was successful.\")\n",
+    "negf_out = torch.load(results_path,weights_only=False)\n",
+    "\n",
+    "plt.plot(negf_out['uni_grid'], negf_out['T_avg'])\n",
+    "plt.xlabel('Energy (eV)')\n",
+    "plt.title('Total Transmission kmesh=[1,1,1]')\n",
+    "# plt.xlim(-5,5)\n",
+    "plt.grid()\n",
     "plt.show()"
    ]
   }
diff --git a/examples/MoS2/MoS2_orth.vasp b/examples/MoS2/MoS2_orth.vasp
new file mode 100644
index 0000000..208c63e
--- /dev/null
+++ b/examples/MoS2/MoS2_orth.vasp
@@ -0,0 +1,14 @@
+MoS2
+1.0
+        3.1912000179         0.0000000000         0.0000000000
+        0.0000000000         18.1270999908         0.0000000000
+        0.0000000000         0.0000000000         5.5272998810
+   Mo    S
+    2    4
+Cartesian
+              0.000000000         9.063549995     0.000000000
+              1.595600009         9.063549995     2.763649940
+              0.000000000        10.633718911     1.842414899
+              1.595600009        10.633718911     4.606064675
+              0.000000000         7.493380540     1.842414899
+              1.595600009         7.493380540     4.606064675
diff --git a/examples/MoS2/POSCAR b/examples/MoS2/POSCAR
new file mode 100644
index 0000000..a660d6a
--- /dev/null
+++ b/examples/MoS2/POSCAR
@@ -0,0 +1,11 @@
+Mo S 
+ 1.0000000000000000
+     3.1911949999999996    0.0000000000000000    0.0000000000000000
+    -1.5955980000000001    2.7636560000000001    0.0000000000000000
+    -0.0000000000000000   -0.0000000000000000   18.1271099999999983
+ Mo  S  
+   1   2
+Cartesian
+  0.0000000000000000  0.0000000000000000  9.0635549999999991
+  1.5955989289309997  0.9212177454480001 10.6337615224199986
+  1.5955989289309997  0.9212177454480001  7.4933484775799997
diff --git a/examples/MoS2/extra_baseline/MoS_spds.json b/examples/MoS2/extra_baseline/MoS_spds.json
new file mode 100644
index 0000000..d0d44e5
--- /dev/null
+++ b/examples/MoS2/extra_baseline/MoS_spds.json
@@ -0,0 +1,16 @@
+{
+    "common_options": {
+        "basis": {
+            "Mo": [
+                "5s",
+                "5p",
+                "4d"
+            ],
+            "S": [
+                "3s",
+                "3p",
+                "d*"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/examples/MoS2/extra_baseline/input_templete.json b/examples/MoS2/extra_baseline/input_templete.json
new file mode 100644
index 0000000..f2f63de
--- /dev/null
+++ b/examples/MoS2/extra_baseline/input_templete.json
@@ -0,0 +1,93 @@
+{
+    "common_options": {
+        "basis": {
+            "Mo": [
+                "5s",
+                "5p",
+                "4d"
+            ],
+            "S": [
+                "3s",
+                "3p",
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+        "dtype": "float32",
+        "overlap": true,
+        "seed": 3982377700
+    },
+    "train_options": {
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+        "batch_size": 1,
+        "optimizer": {
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+        "lr_scheduler": {
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+            "gamma": 0.999
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+        "validation_freq": 10,
+        "display_freq": 100,
+        "ref_batch_size": 1,
+        "val_batch_size": 1,
+        "max_ckpt": 4
+    },
+    "model_options": {
+        "nnsk": {
+            "onsite": {
+                "method": "uniform"
+            },
+            "hopping": {
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+                    "Mo-Mo": 6.03
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+                "w": 0.2
+            },
+            "soc": {},
+            "freeze": [
+                "overlap"
+            ],
+            "push": false,
+            "std": 0.01,
+            "atomic_radius": "cov"
+        }
+    },
+    "data_options": {
+        "train": {
+            "root": "path/to/dataset",
+            "prefix": "prexfix_for_dataset",
+            "get_eigenvalues": true,
+            "type": "DefaultDataset",
+            "get_Hamiltonian": false
+        },
+        "validation": {
+            "root": "path/to/dataset",
+            "prefix": "prexfix_for_dataset",
+            "get_eigenvalues": true,
+            "type": "DefaultDataset",
+            "get_Hamiltonian": false
+        },
+        "reference": {
+            "root": "path/to/dataset",
+            "prefix": "prexfix_for_dataset",
+            "get_eigenvalues": true,
+            "type": "DefaultDataset",
+            "get_Hamiltonian": false
+        }
+    }
+}
\ No newline at end of file
diff --git a/examples/MoS2/extra_baseline/mos_spd_model/sktb.json b/examples/MoS2/extra_baseline/mos_spd_model/sktb.json
new file mode 100644
index 0000000..ff343ed
--- /dev/null
+++ b/examples/MoS2/extra_baseline/mos_spd_model/sktb.json
@@ -0,0 +1,613 @@
+{
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+                0.2855844497680664,
+                -0.29568928480148315,
+                -0.09054512530565262,
+                -0.00012949848314747214
+            ],
+            "Mo-Mo-5p-5p-1": [
+                0.06098540499806404,
+                -0.09257694333791733,
+                0.0671587809920311,
+                0.07819833606481552,
+                -0.05804581940174103,
+                -0.07767686992883682
+            ],
+            "Mo-Mo-5p-4d-0": [
+                0.10616137832403183,
+                -0.06820579618215561,
+                -0.112816721200943,
+                0.263591468334198,
+                -0.039669960737228394,
+                0.00016058619075920433
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+            "Mo-Mo-5p-4d-1": [
+                -0.03334859758615494,
+                0.05897671729326248,
+                -0.04391886666417122,
+                -0.09189578145742416,
+                0.06572780758142471,
+                0.4689989387989044
+            ],
+            "Mo-Mo-4d-4d-0": [
+                0.04318046569824219,
+                -0.06273791193962097,
+                0.02221568487584591,
+                0.12817028164863586,
+                -0.0670974925160408,
+                -0.26892781257629395
+            ],
+            "Mo-Mo-4d-4d-1": [
+                -0.018212802708148956,
+                0.047572970390319824,
+                -0.06813198328018188,
+                -0.00668715825304389,
+                0.03690977394580841,
+                -0.1563439965248108
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+            "Mo-Mo-4d-4d-2": [
+                0.0020285143982619047,
+                -0.005656082183122635,
+                0.017163410782814026,
+                -0.03754601627588272,
+                0.012646774761378765,
+                -0.01699698343873024
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/examples/MoS2/negf.json b/examples/MoS2/negf.json
new file mode 100644
index 0000000..efa5199
--- /dev/null
+++ b/examples/MoS2/negf.json
@@ -0,0 +1,52 @@
+{   
+    "structure":"./struct_negf.xyz",
+	"task_options":
+        {
+            "task": "negf",
+            "scf": false,
+            "block_tridiagonal": true,
+            "ele_T": 300,
+            "unit": "eV",
+            "stru_options":{
+                "gamma_center": false,
+                "time_reversal_symmetry": true,
+                "nel_atom": {"Mo":6,"S":6},
+                "kmesh":[1,1,1],
+                "pbc":[true, false, false],
+                "device":{
+                    "id":"24-48",
+                    "sort": true
+                },
+                "lead_L":{
+                    "id":"0-24",
+                    "voltage":0.0,
+                    "kmesh_lead_Ef":[50,1,20],
+                    "useBloch": false
+                },
+                "lead_R":{
+                    "id":"48-72",
+                    "voltage":0.0,
+                    "kmesh_lead_Ef":[50,1,20],
+                    "useBloch": false
+                }
+            },
+            "density_options": {
+            "method": "Fiori",
+            "integrate_way": "direct"
+            },
+            "poisson_options": {
+            "solver": "fmm",
+            "err": 1e-5
+            },
+            "sgf_solver": "Sancho-Rubio",
+            "espacing": 0.05,
+            "emin": -10,
+            "emax": 10,
+            "eta_lead":1e-5,
+            "eta_device":0.0,
+            "out_dos": true,
+            "out_tc": true,
+            "out_ldos": true,
+            "out_current_nscf": false
+    }
+}
diff --git a/examples/MoS2/orth_ckpt_r_max_5.3_sk.json b/examples/MoS2/orth_ckpt_r_max_5.3_sk.json
new file mode 100644
index 0000000..7869bac
--- /dev/null
+++ b/examples/MoS2/orth_ckpt_r_max_5.3_sk.json
@@ -0,0 +1,507 @@
+{
+    "version": 2,
+    "unit": "eV",
+    "model_options": {
+        "nnsk": {
+            "onsite": {
+                "method": "uniform"
+            },
+            "hopping": {
+                "method": "poly2pow",
+                "rs": 5.9,
+                "w": 0.2
+            },
+            "soc": {},
+            "freeze": false,
+            "push": false,
+            "std": 0.01
+        }
+    },
+    "common_options": {
+        "basis": {
+            "Mo": [
+                "5s",
+                "5p",
+                "4d"
+            ],
+            "S": [
+                "3s",
+                "3p",
+                "d*"
+            ],
+            "W": [
+                "6s",
+                "6p",
+                "5d"
+            ]
+        },
+        "dtype": "float32",
+        "device": "cpu",
+        "overlap": false
+    },
+    "model_params": {
+        "onsite": {
+            "S-3s-0": [
+                -1.5336246490478516
+            ],
+            "S-3p-0": [
+                -2.8460683822631836
+            ],
+            "S-d*-0": [
+                7.979972839355469
+            ],
+            "Mo-5s-0": [
+                6.611484050750732
+            ],
+            "Mo-5p-0": [
+                8.999218940734863
+            ],
+            "Mo-4d-0": [
+                -3.058488607406616
+            ],
+            "W-6s-0": [
+                6.305646896362305
+            ],
+            "W-6p-0": [
+                5.503738880157471
+            ],
+            "W-5d-0": [
+                -1.4621284008026123
+            ]
+        },
+        "hopping": {
+            "S-S-3s-3s-0": [
+                -3.381199598312378,
+                3.750392198562622,
+                -0.9542747139930725,
+                -3.687988519668579
+            ],
+            "S-S-3s-3p-0": [
+                7.536603927612305,
+                -1.4939329624176025,
+                10.275971412658691,
+                -9.438465118408203
+            ],
+            "S-S-3s-d*-0": [
+                0.022247064858675003,
+                -7.985495090484619,
+                7.861386775970459,
+                -4.330418586730957
+            ],
+            "S-S-3p-3p-0": [
+                2.2604639530181885,
+                11.91923999786377,
+                -1.9490504264831543,
+                5.5246500968933105
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+                1.3564902544021606,
+                -0.20222687721252441,
+                1.493829369544983
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+            "S-S-3p-d*-0": [
+                0.06640829890966415,
+                6.22664213180542,
+                -2.0282275676727295,
+                -4.1582159996032715
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+            "S-S-3p-d*-1": [
+                -4.869969367980957,
+                -5.19409704208374,
+                2.0388128757476807,
+                -5.4342041015625
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+                -1.4264990091323853,
+                1.387017846107483,
+                1.755661964416504
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+            "S-S-d*-d*-1": [
+                1.2270694971084595,
+                3.251298189163208,
+                -1.0603923797607422,
+                1.669547438621521
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+            "S-S-d*-d*-2": [
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+                0.2337898463010788,
+                0.4579122066497803,
+                -0.0002807382261380553
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+                2.92494535446167,
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+                -5.328996658325195,
+                3.0383248329162598,
+                -3.4947774410247803
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+                -0.42727574706077576,
+                -4.941512107849121
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+                1.2560112476348877,
+                3.1574862003326416
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+                5.136835098266602,
+                0.1503341794013977,
+                6.29614782333374
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+            "Mo-S-5p-3p-0": [
+                0.44232532382011414,
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+                -4.091493606567383,
+                -3.1395556926727295
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+            "Mo-S-5p-3p-1": [
+                -1.123295783996582,
+                -2.6107842922210693,
+                1.0792241096496582,
+                4.4189348220825195
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+                1.7313252687454224,
+                2.9471049308776855,
+                -1.2205541133880615,
+                0.25976648926734924
+            ],
+            "Mo-S-4d-3p-0": [
+                -4.805062770843506,
+                -5.032190799713135,
+                2.9662532806396484,
+                7.389599323272705
+            ],
+            "Mo-S-5p-d*-1": [
+                -2.6449592113494873,
+                -2.520565986633301,
+                1.9865821599960327,
+                1.1694449186325073
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+            "Mo-S-4d-3p-1": [
+                1.5480694770812988,
+                -2.2313544750213623,
+                0.746772289276123,
+                -1.1558287143707275
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+            "Mo-S-4d-d*-0": [
+                1.978737711906433,
+                1.2456148862838745,
+                0.48462408781051636,
+                2.325913906097412
+            ],
+            "Mo-S-4d-d*-1": [
+                -2.4461586475372314,
+                0.5702215433120728,
+                0.08457184582948685,
+                -0.4567333459854126
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+            "Mo-S-4d-d*-2": [
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+                0.47956469655036926,
+                -0.009094683453440666,
+                0.48226988315582275
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+            "Mo-Mo-5s-5s-0": [
+                -2.2808072566986084,
+                -3.8277132511138916,
+                1.7294433116912842,
+                -2.9419000148773193
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+            "Mo-Mo-5s-5p-0": [
+                0.925851047039032,
+                -1.9320732355117798,
+                2.8604490756988525,
+                -4.279796600341797
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+            "Mo-Mo-5s-4d-0": [
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+                2.9340767860412598,
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+            "Mo-Mo-5p-5p-0": [
+                -2.9864747524261475,
+                0.925573468208313,
+                -5.338494777679443,
+                -3.535318374633789
+            ],
+            "Mo-Mo-5p-5p-1": [
+                -0.6893712878227234,
+                -0.8342631459236145,
+                2.810356616973877,
+                0.0004784934571944177
+            ],
+            "Mo-Mo-5p-4d-0": [
+                0.17527063190937042,
+                -3.8216195106506348,
+                0.013025217689573765,
+                2.395954132080078
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+            "Mo-Mo-5p-4d-1": [
+                0.435280978679657,
+                0.9832556843757629,
+                -2.9232735633850098,
+                -1.5402857065200806
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+            "Mo-Mo-4d-4d-0": [
+                -2.1493546962738037,
+                -1.6637847423553467,
+                3.121760606765747,
+                3.4172966480255127
+            ],
+            "Mo-Mo-4d-4d-1": [
+                2.280841827392578,
+                -2.325227975845337,
+                -0.039111506193876266,
+                -0.3169719874858856
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+            "Mo-Mo-4d-4d-2": [
+                -0.12325769662857056,
+                0.8185058236122131,
+                -0.44520142674446106,
+                -0.04864808917045593
+            ],
+            "W-S-6s-3s-0": [
+                2.868190288543701,
+                7.786489963531494,
+                -4.355151653289795,
+                6.625162601470947
+            ],
+            "W-S-6s-3p-0": [
+                2.513493537902832,
+                6.113368034362793,
+                -5.58524227142334,
+                -5.309149742126465
+            ],
+            "W-S-6p-3s-0": [
+                2.7337286472320557,
+                11.37115478515625,
+                0.9116961359977722,
+                -5.340160846710205
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+            "W-S-6s-d*-0": [
+                0.03326620161533356,
+                0.2178598940372467,
+                -4.687047004699707,
+                -4.2935638427734375
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+            "W-S-5d-3s-0": [
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+                3.399794340133667,
+                -0.9445475339889526,
+                -2.190114974975586
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+            "W-S-6p-3p-0": [
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+            "W-S-6p-3p-1": [
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+                0.45103901624679565,
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+                3.7068276405334473
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+            "W-S-5d-d*-2": [
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+                -0.9681077599525452,
+                -2.3585283756256104
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+            "W-Mo-6s-5s-0": [
+                2.245046377182007,
+                4.065178394317627,
+                -2.067430019378662,
+                -2.9039440155029297
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+            "W-Mo-6s-5p-0": [
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+                1.678234338760376,
+                -0.2636052072048187,
+                -2.6080000400543213
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+            "W-Mo-6p-5s-0": [
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+            "W-Mo-6s-4d-0": [
+                1.0892280340194702,
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+                -0.5302347540855408,
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+            "W-Mo-5d-5s-0": [
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+            "W-Mo-6p-5p-0": [
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+                -3.383216142654419,
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+            "W-Mo-6p-4d-0": [
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+            "W-Mo-5d-5p-0": [
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+            "W-Mo-5d-4d-0": [
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+                -2.8396944999694824,
+                0.645610511302948,
+                -1.1992454528808594
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+            "W-Mo-5d-4d-1": [
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+                -0.19148768484592438,
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+            "W-Mo-5d-4d-2": [
+                -0.22874504327774048,
+                -1.0336724519729614,
+                0.9890119433403015,
+                -0.9379357099533081
+            ],
+            "W-W-6s-6s-0": [
+                -2.2545535564422607,
+                -4.427914142608643,
+                2.07528018951416,
+                -2.971905469894409
+            ],
+            "W-W-6s-6p-0": [
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+                -3.157747507095337,
+                4.026793479919434,
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+            "W-W-6s-5d-0": [
+                -0.266499787569046,
+                3.5014395713806152,
+                -0.8820341229438782,
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+            "W-W-6p-6p-0": [
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+                7.511961460113525,
+                0.4108518064022064
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+            "W-W-6p-6p-1": [
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+                2.2595105171203613,
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+            "W-W-6p-5d-0": [
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+            "W-W-6p-5d-1": [
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+                -1.6153699159622192,
+                -0.5241134762763977,
+                0.06113520637154579
+            ],
+            "W-W-5d-5d-0": [
+                -2.524566173553467,
+                -2.5317535400390625,
+                3.79988694190979,
+                -2.6386475563049316
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+            "W-W-5d-5d-1": [
+                1.8926671743392944,
+                1.9054099321365356,
+                -3.579899311065674,
+                -2.416670083999634
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+            "W-W-5d-5d-2": [
+                -0.13492710888385773,
+                1.091915249824524,
+                -0.7278991937637329,
+                -0.11346512287855148
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/examples/MoS2/stru_negf.xyz b/examples/MoS2/stru_negf.xyz
new file mode 100644
index 0000000..b13151e
--- /dev/null
+++ b/examples/MoS2/stru_negf.xyz
@@ -0,0 +1,74 @@
+72
+Lattice="3.1912000179 0.0 0.0 0.0 18.1270999908 0.0 0.0 0.0 66.327598572" Properties=species:S:1:pos:R:3 pbc="T T T"
+Mo       0.00000000       9.06355000      11.05459976
+S        0.00000000       7.49338054      12.89701466
+S        0.00000000      10.63371891      12.89701466
+Mo       1.59560001       9.06355000      13.81824970
+S        1.59560001       7.49338054      15.66066444
+S        1.59560001      10.63371891      15.66066444
+Mo       0.00000000       9.06355000      16.58189964
+S        0.00000000       7.49338054      18.42431454
+S        0.00000000      10.63371891      18.42431454
+Mo       1.59560001       9.06355000      19.34554958
+S        1.59560001       7.49338054      21.18796432
+S        1.59560001      10.63371891      21.18796432
+Mo       0.00000000       9.06355000       0.00000000
+S        0.00000000       7.49338054       1.84241490
+S        0.00000000      10.63371891       1.84241490
+Mo       1.59560001       9.06355000       2.76364994
+S        1.59560001       7.49338054       4.60606467
+S        1.59560001      10.63371891       4.60606467
+Mo       0.00000000       9.06355000       5.52729988
+S        0.00000000       7.49338054       7.36971478
+S        0.00000000      10.63371891       7.36971478
+Mo       1.59560001       9.06355000       8.29094982
+S        1.59560001       7.49338054      10.13336456
+S        1.59560001      10.63371891      10.13336456
+Mo       0.00000000       9.06355000      22.10919952
+S        0.00000000       7.49338054      23.95161442
+S        0.00000000      10.63371891      23.95161442
+Mo       1.59560001       9.06355000      24.87284946
+S        1.59560001       7.49338054      26.71526420
+S        1.59560001      10.63371891      26.71526420
+Mo       0.00000000       9.06355000      27.63649941
+S        0.00000000       7.49338054      29.47891430
+S        0.00000000      10.63371891      29.47891430
+Mo       1.59560001       9.06355000      30.40014935
+S        1.59560001       7.49338054      32.24256408
+S        1.59560001      10.63371891      32.24256408
+Mo       0.00000000       9.06355000      33.16379929
+S        0.00000000       7.49338054      35.00621418
+S        0.00000000      10.63371891      35.00621418
+Mo       1.59560001       9.06355000      35.92744923
+S        1.59560001       7.49338054      37.76986396
+S        1.59560001      10.63371891      37.76986396
+Mo       0.00000000       9.06355000      38.69109917
+S        0.00000000       7.49338054      40.53351407
+S        0.00000000      10.63371891      40.53351407
+Mo       1.59560001       9.06355000      41.45474911
+S        1.59560001       7.49338054      43.29716384
+S        1.59560001      10.63371891      43.29716384
+Mo       0.00000000       9.06355000      44.21839905
+S        0.00000000       7.49338054      46.06081395
+S        0.00000000      10.63371891      46.06081395
+Mo       1.59560001       9.06355000      46.98204899
+S        1.59560001       7.49338054      48.82446372
+S        1.59560001      10.63371891      48.82446372
+Mo       0.00000000       9.06355000      49.74569893
+S        0.00000000       7.49338054      51.58811383
+S        0.00000000      10.63371891      51.58811383
+Mo       1.59560001       9.06355000      52.50934887
+S        1.59560001       7.49338054      54.35176360
+S        1.59560001      10.63371891      54.35176360
+Mo       0.00000000       9.06355000      55.27299881
+S        0.00000000       7.49338054      57.11541371
+S        0.00000000      10.63371891      57.11541371
+Mo       1.59560001       9.06355000      58.03664875
+S        1.59560001       7.49338054      59.87906349
+S        1.59560001      10.63371891      59.87906349
+Mo       0.00000000       9.06355000      60.80029869
+S        0.00000000       7.49338054      62.64271359
+S        0.00000000      10.63371891      62.64271359
+Mo       1.59560001       9.06355000      63.56394863
+S        1.59560001       7.49338054      65.40636337
+S        1.59560001      10.63371891      65.40636337
diff --git a/examples/MoS2/train/data/POSCAR b/examples/MoS2/train/data/POSCAR
new file mode 100644
index 0000000..4641269
--- /dev/null
+++ b/examples/MoS2/train/data/POSCAR
@@ -0,0 +1,16 @@
+Mo S 
+ 1.0000000000000000
+     3.1911949999999996    0.0000000000000000    0.0000000000000000
+    -1.5955980000000001    2.7636560000000001    0.0000000000000000
+    -0.0000000000000000   -0.0000000000000000   18.1271099999999983
+ Mo  S  
+   1   2
+Selective dynamics
+Cartesian
+  0.0000000000000000  0.0000000000000000  9.0635549999999991   T   T   T
+  1.5955989289309997  0.9212177454480001 10.6337615224199986   T   T   T
+  1.5955989289309997  0.9212177454480001  7.4933484775799997   T   T   T
+Cartesian
+  0.0000000000000000  0.0000000000000000  0.0000000000000000
+  0.0000000000000000  0.0000000000000000  0.0000000000000000
+  0.0000000000000000  0.0000000000000000  0.0000000000000000
diff --git a/examples/MoS2/train/data/kpath.0/eigenvalues.npy b/examples/MoS2/train/data/kpath.0/eigenvalues.npy
new file mode 100644
index 0000000..e5950b5
Binary files /dev/null and b/examples/MoS2/train/data/kpath.0/eigenvalues.npy differ
diff --git a/examples/MoS2/train/data/kpath.0/info.json b/examples/MoS2/train/data/kpath.0/info.json
new file mode 100644
index 0000000..af330ee
--- /dev/null
+++ b/examples/MoS2/train/data/kpath.0/info.json
@@ -0,0 +1,12 @@
+{
+    "nframes": 1,
+    "natoms": 3,
+    "pos_type": "ase",
+    "pbc": true,
+    "bandinfo": {
+        "band_min": 0,
+        "band_max": 14,
+        "emin": 0.0,
+        "emax": 20.0
+    }
+}
diff --git a/examples/MoS2/train/data/kpath.0/kpoints.npy b/examples/MoS2/train/data/kpath.0/kpoints.npy
new file mode 100644
index 0000000..02728ac
Binary files /dev/null and b/examples/MoS2/train/data/kpath.0/kpoints.npy differ
diff --git a/examples/MoS2/train/data/kpath.0/xdat.traj b/examples/MoS2/train/data/kpath.0/xdat.traj
new file mode 100644
index 0000000..d56e9ad
Binary files /dev/null and b/examples/MoS2/train/data/kpath.0/xdat.traj differ
diff --git a/examples/hBN/train/input.json b/examples/MoS2/train/input.json
similarity index 78%
rename from examples/hBN/train/input.json
rename to examples/MoS2/train/input.json
index eb04861..0a35beb 100644
--- a/examples/hBN/train/input.json
+++ b/examples/MoS2/train/input.json
@@ -1,14 +1,14 @@
 {
     "common_options": {
         "basis": {
-            "B": [
-                "2s",
-                "2p",
-                "d*"
+            "Mo": [
+                "5s",
+                "5p",
+                "4d"
             ],
-            "N": [
-                "2s",
-                "2p",
+            "S": [
+                "3s",
+                "3p",
                 "d*"
             ]
         },
@@ -18,15 +18,15 @@
         "seed": 3982377700
     },
     "train_options": {
-        "num_epoch": 5000,
+        "num_epoch": 3000,
         "batch_size": 1,
         "optimizer": {
-            "lr": 0.01,
+            "lr": 0.006,
             "type": "Adam"
         },
         "lr_scheduler": {
             "type": "exp",
-            "gamma": 0.9995
+            "gamma": 0.999
         },
         "loss_options": {
             "train": {
@@ -49,12 +49,12 @@
                 "method": "strain"
             },
             "hopping": {
-                "method": "poly2pow",
+                "method": "poly4pow",
                 "rs": {
-                    "B-B": 4.22,
-                    "B-N": 4.04,
-                    "N-B": 4.04,
-                    "N-N": 3.85
+                    "S-S": 5.66,
+                    "S-Mo": 5.85,
+                    "Mo-S": 5.85,
+                    "Mo-Mo": 6.03
                 },
                 "w": 0.2
             },
diff --git a/examples/MoS2/train/train_out/checkpoint/nnsk.best.pth b/examples/MoS2/train/train_out/checkpoint/nnsk.best.pth
new file mode 120000
index 0000000..1932f49
--- /dev/null
+++ b/examples/MoS2/train/train_out/checkpoint/nnsk.best.pth
@@ -0,0 +1 @@
+/personal/DeepTB/dptb_Zjj/dpnegf/examples/MoS2/train/train_out/checkpoint/nnsk.ep3000.pth
\ No newline at end of file
diff --git a/examples/MoS2/train/train_out/checkpoint/nnsk.ep3000.pth b/examples/MoS2/train/train_out/checkpoint/nnsk.ep3000.pth
new file mode 100644
index 0000000..1a64c73
Binary files /dev/null and b/examples/MoS2/train/train_out/checkpoint/nnsk.ep3000.pth differ
diff --git a/examples/graphene/negf.json b/examples/graphene/negf.json
index afc353a..e04d965 100644
--- a/examples/graphene/negf.json
+++ b/examples/graphene/negf.json
@@ -1,5 +1,5 @@
 {   
-    "structure":"./struct.xyz",
+    "structure":"./struct_negf.xyz",
 	"task_options":
         {
             "task": "negf",
diff --git a/examples/hBN/negf.json b/examples/hBN/negf.json
new file mode 100644
index 0000000..3cbef14
--- /dev/null
+++ b/examples/hBN/negf.json
@@ -0,0 +1,53 @@
+{   
+    "structure":"./struct_negf.xyz",
+	"task_options":
+        {
+            "task": "negf",
+            "scf": false,
+            "block_tridiagonal": true,
+            "ele_T": 300,
+            "unit": "eV",
+            "stru_options":{
+                "gamma_center": false,
+                "time_reversal_symmetry": true,
+                "nel_atom": {"B": 3,
+                             "N": 5},
+                "kmesh":[1,1,1],
+                "pbc":[false, true, false],
+                "device":{
+                    "id":"32-64",
+                    "sort": true
+                },
+                "lead_L":{
+                    "id":"0-32",
+                    "voltage":0.0,
+                    "kmesh_lead_Ef":[1,50,20],
+                    "useBloch": false
+                },
+                "lead_R":{
+                    "id":"64-96",
+                    "voltage":0.0,
+                    "kmesh_lead_Ef":[1,50,20],
+                    "useBloch": false
+                }
+            },
+            "density_options": {
+            "method": "Fiori",
+            "integrate_way": "direct"
+            },
+            "poisson_options": {
+            "solver": "fmm",
+            "err": 1e-5
+            },
+            "sgf_solver": "Sancho-Rubio",
+            "espacing": 0.05,
+            "emin": -10,
+            "emax": 10,
+            "eta_lead":1e-5,
+            "eta_device":0.0,
+            "out_dos": true,
+            "out_tc": true,
+            "out_ldos": true,
+            "out_current_nscf": false
+    }
+}
diff --git a/examples/hBN/siesta.TBT.AVTRANS_Left-Right b/examples/hBN/siesta.TBT.AVTRANS_Left-Right
new file mode 100644
index 0000000..19bf7d0
--- /dev/null
+++ b/examples/hBN/siesta.TBT.AVTRANS_Left-Right
@@ -0,0 +1,378 @@
+# Transmission, k-averaged
+# Date: 2025-09-26
+#   E [eV]           T [G0]
+ -14.95998   0.96316325E-11
+ -14.87998   0.96082826E-11
+ -14.79998   0.95852399E-11
+ -14.71998   0.95626464E-11
+ -14.63998   0.95406852E-11
+ -14.55998   0.95195967E-11
+ -14.47998   0.94997013E-11
+ -14.39998   0.94814359E-11
+ -14.31998   0.94654050E-11
+ -14.23998   0.94524599E-11
+ -14.15998   0.94438206E-11
+ -14.07998   0.94412667E-11
+ -13.99999   0.94474433E-11
+ -13.91999   0.94663606E-11
+ -13.83999   0.95042260E-11
+ -13.75999   0.95708691E-11
+ -13.67999   0.96822349E-11
+ -13.59999   0.98648777E-11
+ -13.51999   0.10164308E-10
+ -13.43999   0.10661029E-10
+ -13.35999   0.11502510E-10
+ -13.27999   0.12969704E-10
+ -13.19999   0.15622149E-10
+ -13.11999   0.20632313E-10
+ -13.03999   0.30606619E-10
+ -12.95999   0.51759034E-10
+ -12.87999   0.10021236E-09
+ -12.79999   0.22244096E-09
+ -12.71999   0.57188751E-09
+ -12.63999   0.17577346E-08
+ -12.55999   0.69498847E-08
+ -12.47999   0.42116115E-07
+ -12.39999   0.70375271E-06
+ -12.31999   0.27884219E+00
+ -12.23999   0.66938322E+00
+ -12.15999   0.95318628E+00
+ -12.07999   0.11518230E+01
+ -11.99999   0.12972488E+01
+ -11.91999   0.14402506E+01
+ -11.83999   0.15830374E+01
+ -11.75999   0.17256939E+01
+ -11.67999   0.18682249E+01
+ -11.59999   0.20103134E+01
+ -11.51999   0.21248099E+01
+ -11.43999   0.23643475E+01
+ -11.35999   0.17835260E+01
+ -11.27999   0.16931951E+01
+ -11.19999   0.16409654E+01
+ -11.11999   0.16123763E+01
+ -11.03999   0.15573088E+01
+ -10.95999   0.15270593E+01
+ -10.87999   0.14984862E+01
+ -10.79999   0.14424545E+01
+ -10.71999   0.14697008E+01
+ -10.63999   0.14382380E+01
+ -10.55999   0.15265281E+01
+ -10.47999   0.16684613E+01
+ -10.39999   0.16698800E+01
+ -10.31999   0.16990327E+01
+ -10.23999   0.18111700E+01
+ -10.15999   0.18406595E+01
+ -10.07999   0.18976595E+01
+  -9.99999   0.19263438E+01
+  -9.91999   0.19546158E+01
+  -9.83999   0.20081013E+01
+  -9.75999   0.19842414E+01
+  -9.67999   0.20410667E+01
+  -9.59999   0.20696698E+01
+  -9.51999   0.21266026E+01
+  -9.43999   0.21551909E+01
+  -9.35999   0.22119434E+01
+  -9.27999   0.22376292E+01
+  -9.19999   0.22408074E+01
+  -9.11999   0.22694647E+01
+  -9.03999   0.23262701E+01
+  -8.95999   0.23548179E+01
+  -8.87999   0.24054992E+01
+  -8.79999   0.23836466E+01
+  -8.71999   0.24403528E+01
+  -8.63999   0.24690702E+01
+  -8.55999   0.27088458E+01
+  -8.47999   0.27942200E+01
+  -8.39999   0.29103940E+01
+  -8.31999   0.30066418E+01
+  -8.23999   0.31098935E+01
+  -8.15999   0.31393712E+01
+  -8.07999   0.32523167E+01
+  -7.99999   0.33102963E+01
+  -7.91999   0.34221830E+01
+  -7.83999   0.34794556E+01
+  -7.75999   0.35090936E+01
+  -7.67999   0.35666227E+01
+  -7.59999   0.36452072E+01
+  -7.51999   0.34378143E+01
+  -7.43999   0.33235062E+01
+  -7.35999   0.32666648E+01
+  -7.27999   0.32085770E+01
+  -7.19999   0.31528986E+01
+  -7.11999   0.30959236E+01
+  -7.03999   0.30677771E+01
+  -6.95999   0.30382601E+01
+  -6.87999   0.30027485E+01
+  -6.79999   0.29274740E+01
+  -6.71999   0.29248295E+01
+  -6.63999   0.28862447E+01
+  -6.55999   0.28395654E+01
+  -6.47999   0.28393450E+01
+  -6.39999   0.27822880E+01
+  -6.31999   0.27759322E+01
+  -6.23999   0.27253880E+01
+  -6.15999   0.26685930E+01
+  -6.07999   0.26682690E+01
+  -5.99999   0.26396096E+01
+  -5.91999   0.26098613E+01
+  -5.83999   0.25542010E+01
+  -5.75999   0.25256135E+01
+  -5.67999   0.24969520E+01
+  -5.59999   0.24683118E+01
+  -5.51999   0.24376245E+01
+  -5.43999   0.23827131E+01
+  -5.35999   0.23257294E+01
+  -5.27999   0.22969762E+01
+  -5.19999   0.22398542E+01
+  -5.11999   0.21892754E+01
+  -5.03999   0.21368373E+01
+  -4.95999   0.20384796E+01
+  -4.87999   0.19536198E+01
+  -4.79999   0.16696495E+01
+  -4.71999   0.16980047E+01
+  -4.64000   0.17264769E+01
+  -4.56000   0.17549488E+01
+  -4.48000   0.18109492E+01
+  -4.40000   0.18400191E+01
+  -4.32000   0.18963698E+01
+  -4.24000   0.17392580E+01
+  -4.16000   0.15110169E+01
+  -4.08000   0.13401109E+01
+  -4.00000   0.11693604E+01
+  -3.92000   0.10551427E+01
+  -3.84000   0.94100400E+00
+  -3.76000   0.82688006E+00
+  -3.68000   0.71274498E+00
+  -3.60000   0.59856328E+00
+  -3.52000   0.48426366E+00
+  -3.44000   0.34191137E+00
+  -3.36000   0.85961436E-01
+  -3.28000   0.17821837E-06
+  -3.20000   0.10977499E-07
+  -3.12000   0.18218886E-08
+  -3.04000   0.47481324E-09
+  -2.96000   0.16329557E-09
+  -2.88000   0.68581183E-10
+  -2.80000   0.33786603E-10
+  -2.72000   0.19058943E-10
+  -2.64000   0.12086647E-10
+  -2.56000   0.84677484E-11
+  -2.48000   0.64370955E-11
+  -2.40000   0.52178186E-11
+  -2.32000   0.44404604E-11
+  -2.24000   0.39173952E-11
+  -2.16000   0.35478165E-11
+  -2.08000   0.32748584E-11
+  -2.00000   0.30650567E-11
+  -1.92000   0.28979842E-11
+  -1.84000   0.27607773E-11
+  -1.76000   0.26451251E-11
+  -1.68000   0.25455537E-11
+  -1.60000   0.24584189E-11
+  -1.52000   0.23812994E-11
+  -1.44000   0.23126255E-11
+  -1.36000   0.22514518E-11
+  -1.28000   0.21973205E-11
+  -1.20000   0.21501885E-11
+  -1.12000   0.21103993E-11
+  -1.04000   0.20786948E-11
+  -0.96000   0.20562662E-11
+  -0.88000   0.20448465E-11
+  -0.80000   0.20468602E-11
+  -0.72000   0.20656459E-11
+  -0.64000   0.21057869E-11
+  -0.56000   0.21735985E-11
+  -0.48000   0.22778532E-11
+  -0.40000   0.24308703E-11
+  -0.32000   0.26501799E-11
+  -0.24000   0.29611027E-11
+  -0.16000   0.34008264E-11
+  -0.08000   0.40249777E-11
+   0.00000   0.49184520E-11
+   0.08000   0.62137016E-11
+   0.16000   0.81224479E-11
+   0.24000   0.10992325E-10
+   0.32000   0.15411433E-10
+   0.40000   0.22408606E-10
+   0.48000   0.33853443E-10
+   0.56000   0.53294936E-10
+   0.64000   0.87821423E-10
+   0.72000   0.15247221E-09
+   0.80000   0.28159658E-09
+   0.88000   0.56131089E-09
+   0.96000   0.12361013E-08
+   1.04000   0.31372476E-08
+   1.12000   0.10081158E-07
+   1.20000   0.55072941E-07
+   1.28000   0.28696824E-05
+   1.36000   0.31226111E+00
+   1.44000   0.64041248E+00
+   1.52000   0.19217300E+01
+   1.60000   0.18676250E+01
+   1.68000   0.18397129E+01
+   1.76000   0.18116527E+01
+   1.84000   0.17830088E+01
+   1.92000   0.17548377E+01
+   2.00000   0.17265518E+01
+   2.08000   0.16981821E+01
+   2.16000   0.16697637E+01
+   2.24000   0.16694713E+01
+   2.32000   0.16412205E+01
+   2.40000   0.16127996E+01
+   2.48000   0.16125310E+01
+   2.56000   0.15842448E+01
+   2.64000   0.15558005E+01
+   2.72000   0.15556471E+01
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diff --git a/examples/hBN/stru_negf.xyz b/examples/hBN/stru_negf.xyz
new file mode 100644
index 0000000..fa9a500
--- /dev/null
+++ b/examples/hBN/stru_negf.xyz
@@ -0,0 +1,122 @@
+120
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diff --git a/examples/hBN/train/train_out/checkpoint/nnsk.best.pth b/examples/hBN/train/train_out/checkpoint/nnsk.best.pth
new file mode 120000
index 0000000..7946b29
--- /dev/null
+++ b/examples/hBN/train/train_out/checkpoint/nnsk.best.pth
@@ -0,0 +1 @@
+/personal/DeepTB/dptb_Zjj/dpnegf/examples/hBN/train/train_out/checkpoint/nnsk.ep3000.pth
\ No newline at end of file
diff --git a/examples/hBN/train/train_out/checkpoint/nnsk.ep3000.pth b/examples/hBN/train/train_out/checkpoint/nnsk.ep3000.pth
new file mode 100644
index 0000000..7954d21
Binary files /dev/null and b/examples/hBN/train/train_out/checkpoint/nnsk.ep3000.pth differ