handson_DFT_setup_and_bulk.ipynb

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      "authorship_tag": "ABX9TyN0KAkXztZdV1ZNVBtkmVqp",
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      "name": "python3",
      "display_name": "Python 3"
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      "name": "python"
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
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      "source": [
        "<a href=\"https://colab.research.google.com/github/s-choung/Simulation_tutorials/blob/main/handson_DFT_setup_and_bulk.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "source": [
        "## Density Functional Theory in Catalyst Research\n",
        "\n",
        "The urgent need to combat climate change has increased the focus on renewable energy sources, aiming to reduce reliance on fossil fuels and mitigate environmental harm. Efficient catalysts are essential for accelerating chemical reactions, lowering energy consumption, and improving production efficiency. Density Functional Theory (DFT) allows for the simulation of electron density around atomic nuclei by approximating the Schrödinger equation. This facilitates the prediction of catalyst properties, including active sites, adsorbate interactions, and electronic structures, driving more efficient and predictive catalyst design.\n",
        "\n",
        "*Choung et al., Chemical Engineering Journal 494, 2024, 152757*\n"
      ],
      "metadata": {
        "id": "Bk5Cmvws6UJY"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## The grid-based projector-augmented wave (GPAW) code\n",
        "GPAW is a density-functional theory (DFT) Python code based on the projector-augmented wave (PAW) method and the atomic simulation environment (ASE).  GPAW is open-source Python package for electronic structure calculations. GPAW is based on the projector-augmented wave method and can solve the self-consistent DFT equations using three different wave-function representations, namely real-space grids, plane waves, and numerical atomic orbitals.\n",
        "read more: https://pubs.aip.org/aip/jcp/article/160/9/092503/3269902/GPAW-An-open-Python-package-for-electronic"
      ],
      "metadata": {
        "id": "CzINxNUm6jNc"
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    {
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      "source": [
        "- **`python3-dev`**: Provides header files needed to compile Python extensions for `gpaw`'s high-performance computations.\n",
        "- **`libopenblas-dev`**: Optimized library for linear algebra operations like matrix multiplication, ensuring efficient performance in `gpaw`.\n",
        "- **`liblapack-dev`**: Another essential library for linear algebra tasks such as solving equations and eigenvalue problems.\n",
        "- **`libfftw3-dev`**: Library for Fast Fourier Transform (FFT), used in electronic structure calculations to handle problems in reciprocal space.\n",
        "- **`libxc-dev`**: Provides exchange-correlation functionals required for Density Functional Theory (DFT) calculations in `gpaw`.\n"
      ],
      "metadata": {
        "id": "gzkW7BA9-Ohz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!apt-get update\n",
        "!apt-get install -y python3-dev libopenblas-dev liblapack-dev libfftw3-dev libxc-dev"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "S3Xg9Ezw2x9G",
        "outputId": "af758f7d-e6fe-4918-b77c-2e0a7c9bf689"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "  libfftw3-bin libfftw3-double3 libfftw3-long3 libfftw3-quad3 libfftw3-single3 libxc9\n",
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            "/sbin/ldconfig.real: /usr/local/lib/libtbb.so.12 is not a symbolic link\n",
            "\n",
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            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install gpaw"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UIZDhutO2lK3",
        "outputId": "98133553-7ffa-47c4-c8da-49ff856bf8e9"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting gpaw\n",
            "  Downloading gpaw-24.6.0.tar.gz (2.0 MB)\n",
            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/2.0 MB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[91m━━\u001b[0m\u001b[90m╺\u001b[0m\u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.1/2.0 MB\u001b[0m \u001b[31m3.6 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K     \u001b[91m━━━━━━━━━━━━\u001b[0m\u001b[90m╺\u001b[0m\u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.6/2.0 MB\u001b[0m \u001b[31m9.5 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K     \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[91m╸\u001b[0m \u001b[32m2.0/2.0 MB\u001b[0m \u001b[31m20.2 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.0/2.0 MB\u001b[0m \u001b[31m16.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Collecting ase>=3.23.0 (from gpaw)\n",
            "  Downloading ase-3.23.0-py3-none-any.whl.metadata (3.8 kB)\n",
            "Requirement already satisfied: numpy<2 in /usr/local/lib/python3.10/dist-packages (from gpaw) (1.26.4)\n",
            "Requirement already satisfied: scipy>=1.6.0 in /usr/local/lib/python3.10/dist-packages (from gpaw) (1.13.1)\n",
            "Requirement already satisfied: matplotlib>=3.3.4 in /usr/local/lib/python3.10/dist-packages (from ase>=3.23.0->gpaw) (3.7.1)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.3.4->ase>=3.23.0->gpaw) (1.3.0)\n",
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            "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.3.4->ase>=3.23.0->gpaw) (2.8.2)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.7->matplotlib>=3.3.4->ase>=3.23.0->gpaw) (1.16.0)\n",
            "Downloading ase-3.23.0-py3-none-any.whl (2.9 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.9/2.9 MB\u001b[0m \u001b[31m59.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hBuilding wheels for collected packages: gpaw\n",
            "  Building wheel for gpaw (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for gpaw: filename=gpaw-24.6.0-cp310-cp310-linux_x86_64.whl size=2787035 sha256=14295f653f5304ae9680173a3622d3dcdd2664040f596bb5ac4ba9294c03f475\n",
            "  Stored in directory: /root/.cache/pip/wheels/13/03/25/dc7e7191efd7e13c67490ed6c1de03bcc1674874df1dc6e118\n",
            "Successfully built gpaw\n",
            "Installing collected packages: ase, gpaw\n",
            "Successfully installed ase-3.23.0 gpaw-24.6.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!gpaw test"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WnJ9QX-P1kww",
        "outputId": "4e01a901-6d26-4ec2-eb9f-444d6113b129"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " -------------------------------------------------------------------------------------------------\n",
            "| python-3.10.12    /usr/bin/python3                                                              |\n",
            "| gpaw-24.6.0       /usr/local/lib/python3.10/dist-packages/gpaw/                                 |\n",
            "| ase-3.23.0        /usr/local/lib/python3.10/dist-packages/ase/                                  |\n",
            "| numpy-1.26.4      /usr/local/lib/python3.10/dist-packages/numpy/                                |\n",
            "| scipy-1.13.1      /usr/local/lib/python3.10/dist-packages/scipy/                                |\n",
            "| libxc-5.1.7       yes                                                                           |\n",
            "| _gpaw             /usr/local/lib/python3.10/dist-packages/_gpaw.cpython-310-x86_64-linux-gnu.so |\n",
            "| MPI enabled       yes                                                                           |\n",
            "| OpenMP enabled    no                                                                            |\n",
            "| GPU enabled       no                                                                            |\n",
            "| GPU-aware MPI     no                                                                            |\n",
            "| CUPY              /usr/local/lib/python3.10/dist-packages/gpaw/gpu/cpupy/__init__.py            |\n",
            "| scalapack         no                                                                            |\n",
            "| Elpa              no                                                                            |\n",
            "| FFTW              no                                                                            |\n",
            "| libvdwxc          no                                                                            |\n",
            "| PAW-datasets (1)  /usr/local/share/gpaw-setups                                                  |\n",
            "| PAW-datasets (2)  /usr/share/gpaw-setups                                                        |\n",
            " -------------------------------------------------------------------------------------------------\n",
            "Could not find any atomic PAW-data or pseudopotentials!\n",
            "\n",
            "You need to set the GPAW_SETUP_PATH environment variable to point to\n",
            "the directories where PAW dataset and basis files are stored.  See\n",
            "https://wiki.fysik.dtu.dk/gpaw/install.html#install-paw-datasets\n",
            "for details.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Install Pseudo potential for GPAW calculations\n",
        "\n",
        "A setup is to the PAW method what a pseudo-potential is to the pseudo-potential method.\n",
        "read more: https://gpaw.readthedocs.io/setups/setups.html"
      ],
      "metadata": {
        "id": "Cq920dYk7yz0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!wget https://wiki.fysik.dtu.dk/gpaw-files/gpaw-setups-24.1.0.tar.gz\n",
        "!tar -xzf gpaw-setups-24.1.0.tar.gz"
      ],
      "metadata": {
        "id": "QlycqXtMcu0J",
        "outputId": "18f1dd87-8278-45f3-8085-75a8012ec5c8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2024-09-24 03:01:38--  https://wiki.fysik.dtu.dk/gpaw-files/gpaw-setups-24.1.0.tar.gz\n",
            "Resolving wiki.fysik.dtu.dk (wiki.fysik.dtu.dk)... 130.225.86.27\n",
            "Connecting to wiki.fysik.dtu.dk (wiki.fysik.dtu.dk)|130.225.86.27|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 53598132 (51M) [application/x-gzip]\n",
            "Saving to: ‘gpaw-setups-24.1.0.tar.gz’\n",
            "\n",
            "gpaw-setups-24.1.0. 100%[===================>]  51.11M  16.7MB/s    in 3.1s    \n",
            "\n",
            "2024-09-24 03:01:41 (16.7 MB/s) - ‘gpaw-setups-24.1.0.tar.gz’ saved [53598132/53598132]\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "import gzip\n",
        "import shutil\n",
        "\n",
        "# Define the path to the setup files\n",
        "setup_path = '/content/gpaw-setups-24.1.0'\n",
        "\n",
        "# Uncompress all .gz files in the setup directory\n",
        "for filename in os.listdir(setup_path):\n",
        "    if filename.endswith('.gz'):\n",
        "        filepath = os.path.join(setup_path, filename)\n",
        "        with gzip.open(filepath, 'rb') as f_in:\n",
        "            with open(filepath[:-3], 'wb') as f_out:\n",
        "                shutil.copyfileobj(f_in, f_out)\n",
        "\n",
        "# List the files after uncompressing to ensure the process completed successfully\n",
        "print(\"Files in setup directory after uncompressing:\", os.listdir(setup_path))\n",
        "\n",
        "# Set the GPAW_SETUP_PATH environment variable\n",
        "os.environ['GPAW_SETUP_PATH'] = setup_path\n",
        "\n",
        "# Verify the environment variable\n",
        "print(\"GPAW_SETUP_PATH:\", os.environ['GPAW_SETUP_PATH'])\n",
        "\n"
      ],
      "metadata": {
        "id": "ZOhRvZ2n59zU",
        "outputId": "432b97db-81d8-4b4e-a683-ff4ea9f00419",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Files in setup directory after uncompressing: ['Pd.dzp.basis.gz', 'Ba.RPBE', 'He.PBE', 'Ge.dzp.basis.gz', 'Ge.PBE.gz', 'Pd.10.PBE.gz', 'Pd.RPBE', 'Bi.RPBE', 'Xe.PBE.gz', 'Ni.LDA.gz', 'Ti.RPBE.gz', 'Ge.RPBE.gz', 'Ag.LDA.gz', 'Os.8.GLLBSC', 'I.dzp.basis', 'Kr.LDA.gz', 'Rn.RPBE', 'P.dzp.basis', 'Cd.PBE.gz', 'Ni.GLLBSC', 'F.GLLBSC', 'Tl.revPBE', 'Mg.2.revPBE', 'Ti.revPBE.gz', 'Be.LDA.gz', 'Ca.revPBE', 'Rn.revPBE', 'Ni.dzp.basis', 'I.RPBE', 'Zr.RPBE.gz', 'Y.PBE.gz', 'Be.RPBE', 'W.LDA', 'Mo.RPBE.gz', 'Nb.GLLBSC', 'Cs.RPBE.gz', 'Na.PBE', 'Rb.PBE', 'In.revPBE.gz', 'Y.LDA', 'As.revPBE.gz', 'Nb.dzp.basis.gz', 'Rh.9.PBE.gz', 'Kr.PBE.gz', 'Rb.RPBE', 'Se.LDA.gz', 'Mg.2.dzp.basis', 'Pt.10.dzp.basis.gz', 'Zr.GLLBSC', 'Cr.PBE', 'Br.revPBE.gz', 'Ca.revPBE.gz', 'Ag.11.GLLBSC.gz', 'N.revPBE.gz', 'Mg.2.RPBE.gz', 'Ga.RPBE', 'I.GLLBSC', 'Rb.RPBE.gz', 'Ta.GLLBSC.gz', 'Ne.LDA', 'P.RPBE.gz', 'Li.LDA.gz', 'V.5.LDA', 'Cr.LDA.gz', 'Ir.9.revPBE', 'W.dzp.basis', 'Rh.9.revPBE.gz', 'Ru.LDA', 'Ne.revPBE', 'C.LDA.gz', 'Br.dzp.basis.gz', 'Kr.dzp.basis', 'Sn.dzp.basis.gz', 'Na.GLLBSC', 'Fe.GLLBSC', 'Si.revPBE', 'Te.16.GLLBSC.gz', 'Cd.revPBE', 'Mn.revPBE.gz', 'Au.PBE.gz', 'Y.revPBE.gz', 'Hg.PBE', 'Ru.8.PBE.gz', 'H.dzp.basis', 'Ru.8.dzp.basis', 'Zr.GLLBSC.gz', 'Os.dzp.basis.gz', 'Mn.PBE', 'N.RPBE.gz', 'Ag.11.LDA', 'Pd.10.dzp.basis.gz', 'S.LDA', 'Ru.8.RPBE.gz', 'Nb.5.revPBE.gz', 'In.dzp.basis', 'Sn.dzp.basis', 'Rh.RPBE.gz', 'W.PBE.gz', 'Ru.RPBE.gz', 'Rh.9.dzp.basis.gz', 'Mg.2.GLLBSC.gz', 'Be.PBE', 'Os.GLLBSC.gz', 'Ba.PBE.gz', 'Te.16.GLLBSC', 'Ta.PBE', 'Se.GLLBSC.gz', 'Pb.GLLBSC', 'Fe.revPBE', 'Pt.10.GLLBSC', 'Rb.GLLBSC', 'Rh.9.revPBE', 'Ga.LDA', 'Kr.revPBE', 'Pd.LDA', 'Te.GLLBSC.gz', 'S.revPBE', 'Li.RPBE.gz', 'Cs.LDA.gz', 'Rn.GLLBSC.gz', 'Pb.LDA', 'Na.1.dzp.basis.gz', 'Cu.LDA.gz', 'Ar.RPBE', 'V.5.GLLBSC', 'C.revPBE', 'Kr.GLLBSC.gz', 'Hf.PBE', 'K.RPBE.gz', 'Ar.dzp.basis', 'Bi.LDA', 'Ir.GLLBSC', 'H.GLLBSC', 'Se.RPBE.gz', 'Hf.GLLBSC', 'Co.LDA.gz', 'Bi.PBE', 'Ba.revPBE', 'Au.dzp.basis.gz', 'B.PBE', 'Sn.revPBE.gz', 'Cr.LDA', 'Mo.6.RPBE', 'Sb.GLLBSC.gz', 'Rh.9.dzp.basis', 'Cr.RPBE.gz', 'LICENSE', 'Li.PBE', 'Cs.RPBE', 'In.PBE', 'Cu.RPBE.gz', 'V.dzp.basis.gz', 'I.PBE.gz', 'Bi.revPBE.gz', 'Ni.10.dzp.basis', 'C.GLLBSC.gz', 'Se.RPBE', 'Ir.9.PBE', 'Rn.revPBE.gz', 'Ti.GLLBSC', 'Ti.GLLBSC.gz', 'Os.8.PBE.gz', 'Pd.RPBE.gz', 'Br.GLLBSC', 'Li.GLLBSC.gz', 'Mg.GLLBSC.gz', 'Re.PBE.gz', 'Ar.GLLBSC', 'Bi.PBE.gz', 'Cr.14.LDA.gz', 'Nb.GLLBSC.gz', 'Kr.revPBE.gz', 'B.GLLBSC.gz', 'W.revPBE', 'Ta.PBE.gz', 'Cl.GLLBSC.gz', 'Pd.revPBE.gz', 'Nb.revPBE', 'Zn.GLLBSC.gz', 'Ne.RPBE.gz', 'H.LDA.gz', 'Ni.10.RPBE', 'O.RPBE', 'Os.8.revPBE', 'Ru.RPBE', 'Na.1.LDA', 'Mo.6.PBE', 'B.dzp.basis', 'V.5.revPBE.gz', 'Co.GLLBSC.gz', 'Mo.dzp.basis.gz', 'Al.PBE', 'Te.revPBE.gz', 'Cd.LDA.gz', 'I.RPBE.gz', 'Ru.8.revPBE.gz', 'Pd.10.GLLBSC', 'He.GLLBSC', 'Ta.5.PBE', 'Sr.GLLBSC.gz', 'Hf.revPBE.gz', 'Mn.PBE.gz', 'Y.revPBE', 'Os.8.RPBE.gz', 'Xe.revPBE.gz', 'Ge.LDA', 'P.LDA.gz', 'Si.LDA', 'Li.revPBE.gz', 'Nb.PBE', 'Ta.LDA', 'K.dzp.basis.gz', 'Nb.5.RPBE', 'Rn.dzp.basis', 'N.LDA.gz', 'W.RPBE.gz', 'Pd.10.GLLBSC.gz', 'N.dzp.basis', 'Se.dzp.basis.gz', 'As.LDA.gz', 'Kr.RPBE.gz', 'C.GLLBSC', 'Rh.dzp.basis.gz', 'Mg.2.revPBE.gz', 'V.5.dzp.basis.gz', 'Ru.GLLBSC.gz', 'Mo.6.GLLBSC.gz', 'Zr.revPBE.gz', 'Rh.revPBE', 'Ge.PBE', 'Ag.LDA', 'Ta.LDA.gz', 'V.revPBE', 'K.GLLBSC', 'Sr.RPBE', 'S.PBE', 'Nb.5.LDA', 'Os.LDA', 'Pt.RPBE.gz', 'Cl.PBE.gz', 'Ir.9.LDA.gz', 'Cu.PBE', 'Pt.LDA', 'He.PBE.gz', 'Ru.8.GLLBSC', 'Ag.GLLBSC', 'Mg.PBE', 'Rh.9.LDA.gz', 'Tl.dzp.basis.gz', 'Au.RPBE', 'Be.PBE.gz', 'Na.revPBE', 'Mg.dzp.basis.gz', 'Ta.5.RPBE', 'Hf.dzp.basis.gz', 'Y.dzp.basis.gz', 'Ga.dzp.basis', 'F.RPBE.gz', 'Ta.5.PBE.gz', 'Ga.RPBE.gz', 'Pt.RPBE', 'Ar.PBE.gz', 'Hg.RPBE', 'Ag.11.RPBE.gz', 'Cu.revPBE.gz', 'H.revPBE.gz', 'Cd.PBE', 'Ta.5.revPBE.gz', 'P.PBE', 'Rh.9.GLLBSC.gz', 'Cd.GLLBSC.gz', 'Co.GLLBSC', 'Rh.PBE', 'Ru.revPBE.gz', 'Zn.RPBE.gz', 'Mo.RPBE', 'Mg.RPBE', 'Na.dzp.basis', 'Mg.dzp.basis', 'Ca.dzp.basis', 'Si.revPBE.gz', 'Co.RPBE.gz', 'V.5.LDA.gz', 'Os.8.LDA.gz', 'Ne.PBE', 'Mo.6.dzp.basis', 'Hg.GLLBSC.gz', 'Te.16.PBE.gz', 'F.LDA', 'Pt.PBE', 'Sc.PBE.gz', 'Tl.dzp.basis', 'Zn.PBE', 'O.GLLBSC.gz', 'Ga.GLLBSC', 'In.LDA.gz', 'Na.1.RPBE.gz', 'C.RPBE', 'S.dzp.basis.gz', 'Mn.7.LDA', 'Rn.LDA.gz', 'Os.8.dzp.basis', 'Au.GLLBSC.gz', 'Pd.10.LDA', 'Ba.PBE', 'Cd.dzp.basis', 'Ta.5.GLLBSC', 'Os.RPBE.gz', 'Br.LDA.gz', 'V.5.GLLBSC.gz', 'Ga.PBE.gz', 'Rb.LDA', 'Nb.5.LDA.gz', 'Ag.RPBE', 'Te.16.dzp.basis.gz', 'Co.PBE.gz', 'Br.revPBE', 'Mg.2.dzp.basis.gz', 'Fe.LDA.gz', 'Li.dzp.basis.gz', 'Pt.10.LDA', 'Ir.9.revPBE.gz', 'Ge.GLLBSC', 'Al.dzp.basis.gz', 'Os.8.LDA', 'B.RPBE.gz', 'Ag.11.PBE.gz', 'Li.RPBE', 'F.revPBE.gz', 'Xe.dzp.basis', 'Os.8.GLLBSC.gz', 'Zn.revPBE.gz', 'Pt.GLLBSC.gz', 'Ti.LDA.gz', 'Au.PBE', 'Al.GLLBSC', 'Mo.revPBE.gz', 'Ba.GLLBSC.gz', 'Ti.RPBE', 'W.6.GLLBSC.gz', 'He.LDA', 'Os.8.PBE', 'Y.GLLBSC.gz', 'Mn.dzp.basis', 'Ag.11.dzp.basis.gz', 'F.PBE', 'Mg.GLLBSC', 'Mg.LDA.gz', 'Ir.GLLBSC.gz', 'Sn.RPBE', 'V.5.RPBE.gz', 'H.LDA', 'Li.GLLBSC', 'Pd.revPBE', 'H.PBE', 'S.dzp.basis', 'Ir.dzp.basis.gz', 'Te.LDA.gz', 'Mo.GLLBSC.gz', 'Ga.PBE', 'C.PBE', 'W.6.GLLBSC', 'Zr.PBE', 'Ag.11.GLLBSC', 'Ar.GLLBSC.gz', 'Ta.RPBE', 'Ge.GLLBSC.gz', 'Pd.10.PBE', 'Cs.dzp.basis', 'B.GLLBSC', 'P.PBE.gz', 'Ni.10.dzp.basis.gz', 'H.RPBE.gz', 'Sn.PBE.gz', 'Mn.7.dzp.basis.gz', 'Se.PBE', 'Tl.PBE.gz', 'Cd.RPBE.gz', 'Ru.8.GLLBSC.gz', 'Co.LDA', 'Pd.GLLBSC', 'Ti.dzp.basis.gz', 'Ir.9.GLLBSC', 'Mn.revPBE', 'Al.dzp.basis', 'Cl.dzp.basis', 'Ru.8.dzp.basis.gz', 'Tl.GLLBSC', 'Si.LDA.gz', 'O.dzp.basis.gz', 'Cs.revPBE', 'Mg.2.RPBE', 'Al.revPBE', 'Ca.GLLBSC', 'Nb.5.PBE', 'Se.revPBE', 'Ne.GLLBSC.gz', 'Ni.10.GLLBSC', 'Ti.LDA', 'V.5.PBE.gz', 'Mo.6.PBE.gz', 'Sr.LDA.gz', 'Sb.LDA.gz', 'Ru.8.RPBE', 'Ru.8.LDA', 'Sc.revPBE', 'Pt.PBE.gz', 'Xe.LDA.gz', 'Te.RPBE', 'Mo.revPBE', 'Fe.RPBE.gz', 'Ar.revPBE', 'Si.dzp.basis.gz', 'V.dzp.basis', 'I.GLLBSC.gz', 'Rh.RPBE', 'Mo.6.LDA', 'Pt.GLLBSC', 'Cd.GLLBSC', 'Au.revPBE', 'Sb.GLLBSC', 'Cu.revPBE', 'Hg.RPBE.gz', 'Ta.5.RPBE.gz', 'Bi.RPBE.gz', 'Re.revPBE', 'Br.dzp.basis', 'Zr.dzp.basis.gz', 'Zn.dzp.basis', 'Kr.LDA', 'Si.PBE.gz', 'Be.LDA', 'Ag.GLLBSC.gz', 'Sc.GLLBSC.gz', 'Ag.revPBE', 'K.revPBE.gz', 'Si.RPBE', 'Sb.PBE', 'Nb.5.dzp.basis', 'C.dzp.basis', 'Sn.RPBE.gz', 'Ir.dzp.basis', 'Bi.dzp.basis', 'Hg.dzp.basis', 'Cs.GLLBSC.gz', 'Te.GLLBSC', 'Cd.revPBE.gz', 'Br.RPBE.gz', 'Ar.LDA', 'phi-0.500-1.000-20.000-21-201.pckl', 'W.6.dzp.basis', 'K.GLLBSC.gz', 'Zr.PBE.gz', 'Na.PBE.gz', 'Ca.dzp.basis.gz', 'Na.RPBE', 'K.RPBE', 'C.LDA', 'Be.dzp.basis.gz', 'Mo.dzp.basis', 'Na.1.dzp.basis', 'Bi.LDA.gz', 'Ru.GLLBSC', 'Ru.revPBE', 'V.RPBE', 'Fe.PBE.gz', 'C.dzp.basis.gz', 'Ag.11.PBE', 'F.revPBE', 'Pd.PBE.gz', 'Na.1.GLLBSC.gz', 'Ge.revPBE.gz', 'Kr.RPBE', 'Rh.LDA', 'Al.PBE.gz', 'W.RPBE', 'I.revPBE', 'Au.revPBE.gz', 'O.revPBE', 'Cl.RPBE', 'Hg.LDA', 'Co.revPBE.gz', 'Ba.revPBE.gz', 'Rh.9.RPBE', 'Ag.PBE.gz', 'Co.RPBE', 'Ca.LDA.gz', 'Te.dzp.basis', 'Mg.2.LDA.gz', 'Rn.LDA', 'Hg.PBE.gz', 'Ru.LDA.gz', 'As.dzp.basis.gz', 'W.6.RPBE', 'Rh.9.GLLBSC', 'Rh.revPBE.gz', 'Zr.revPBE', 'Tl.PBE', 'Mo.6.revPBE', 'Ar.revPBE.gz', 'Sr.dzp.basis.gz', 'Sb.revPBE.gz', 'Hf.RPBE.gz', 'Cd.RPBE', 'In.RPBE', 'Ta.5.dzp.basis.gz', 'Pt.dzp.basis.gz', 'Ni.10.LDA.gz', 'Mo.PBE.gz', 'Pd.dzp.basis', 'Mn.RPBE', 'C.RPBE.gz', 'S.GLLBSC', 'Rh.9.PBE', 'Ga.dzp.basis.gz', 'Ca.LDA', 'V.GLLBSC', 'N.LDA', 'Ir.RPBE.gz', 'As.RPBE.gz', 'Xe.RPBE', 'Ca.RPBE.gz', 'He.revPBE.gz', 'Ni.PBE.gz', 'Mg.2.GLLBSC', 'Ga.revPBE.gz', 'Ge.revPBE', 'Pd.10.revPBE.gz', 'Nb.5.GLLBSC', 'Al.RPBE', 'Ag.RPBE.gz', 'Sc.PBE', 'Re.GLLBSC', 'S.RPBE.gz', 'Na.1.revPBE.gz', 'Na.1.LDA.gz', 'In.GLLBSC', 'Ta.revPBE.gz', 'Sb.PBE.gz', 'Os.LDA.gz', 'Cu.dzp.basis', 'Sr.dzp.basis', 'Bi.GLLBSC.gz', 'Mn.7.PBE.gz', 'Ga.GLLBSC.gz', 'N.RPBE', 'Al.LDA', 'V.LDA', 'Ne.RPBE', 'Fe.RPBE', 'P.dzp.basis.gz', 'Pd.10.RPBE', 'Mg.revPBE.gz', 'Ni.revPBE', 'Pb.PBE.gz', 'Ni.GLLBSC.gz', 'Tl.LDA', 'F.GLLBSC.gz', 'Ne.dzp.basis.gz', 'Ir.9.GLLBSC.gz', 'Cd.LDA', 'W.PBE', 'He.LDA.gz', 'P.LDA', 'Ba.dzp.basis', 'Y.RPBE', 'Os.8.revPBE.gz', 'Ru.8.PBE', 'Mn.RPBE.gz', 'Cr.14.LDA', 'Ni.dzp.basis.gz', 'Mg.2.LDA', 'Cu.LDA', 'He.RPBE', 'Br.PBE.gz', 'Ne.LDA.gz', 'Mn.dzp.basis.gz', 'Ni.10.GLLBSC.gz', 'Tl.RPBE.gz', 'Mn.GLLBSC.gz', 'Xe.GLLBSC', 'Sn.GLLBSC.gz', 'Te.LDA', 'Os.revPBE', 'Rb.LDA.gz', 'Zr.LDA', 'Zn.PBE.gz', 'Ta.GLLBSC', 'Ba.dzp.basis.gz', 'Te.16.RPBE', 'H.GLLBSC.gz', 'Cr.14.PBE', 'Hf.dzp.basis', 'Pd.LDA.gz', 'Mo.6.RPBE.gz', 'Ge.dzp.basis', 'Na.1.PBE.gz', 'Cl.revPBE.gz', 'Nb.dzp.basis', 'Sc.dzp.basis.gz', 'Ni.10.revPBE', 'Ag.revPBE.gz', 'Ir.revPBE.gz', 'Na.LDA', 'Sb.revPBE', 'Tl.RPBE', 'Ti.PBE.gz', 'F.LDA.gz', 'Rn.PBE', 'Fe.PBE', 'Sb.LDA', 'Cr.revPBE.gz', 'Zn.LDA.gz', 'Rb.GLLBSC.gz', 'Au.LDA.gz', 'Se.PBE.gz', 'V.revPBE.gz', 'Ni.RPBE', 'Fe.dzp.basis.gz', 'Ne.revPBE.gz', 'Al.RPBE.gz', 'Mn.7.LDA.gz', 'Nb.5.revPBE', 'Se.GLLBSC', 'Mn.7.GLLBSC', 'Nb.5.GLLBSC.gz', 'I.PBE', 'I.LDA', 'Te.16.LDA', 'Xe.RPBE.gz', 'B.PBE.gz', 'V.5.revPBE', 'Mg.RPBE.gz', 'B.LDA.gz', 'In.PBE.gz', 'Sn.LDA', 'K.PBE', 'Hf.GLLBSC.gz', 'Ag.PBE', 'Fe.revPBE.gz', 'Pd.10.dzp.basis', 'Mn.7.revPBE', 'Cu.dzp.basis.gz', 'Nb.LDA.gz', 'Pb.RPBE.gz', 'K.LDA', 'As.dzp.basis', 'Sr.revPBE.gz', 'Sc.RPBE.gz', 'Sn.PBE', 'Hg.revPBE.gz', 'He.dzp.basis.gz', 'In.LDA', 'Y.RPBE.gz', 'Mo.6.revPBE.gz', 'Xe.LDA', 'Te.16.PBE', 'Ne.GLLBSC', 'Zn.LDA', 'Co.revPBE', 'N.PBE.gz', 'Fe.LDA', 'Pb.dzp.basis', 'Ag.11.RPBE', 'O.PBE.gz', 'Si.GLLBSC', 'Ni.LDA', 'Fe.dzp.basis', 'Si.dzp.basis', 'Zn.GLLBSC', 'Sr.PBE.gz', 'N.GLLBSC', 'Cu.GLLBSC', 'P.revPBE', 'Mg.2.PBE', 'Te.16.LDA.gz', 'Cs.PBE.gz', 'Sc.GLLBSC', 'Rh.dzp.basis', 'Ir.9.RPBE', 'F.RPBE', 'Mg.2.PBE.gz', 'Cr.GLLBSC', 'Rn.dzp.basis.gz', 'Hf.LDA.gz', 'As.PBE.gz', 'In.RPBE.gz', 'Cu.PBE.gz', 'Li.LDA', 'Au.RPBE.gz', 'Rh.GLLBSC', 'Ir.9.LDA', 'Sn.LDA.gz', 'Na.1.GLLBSC', 'Pt.10.RPBE', 'Sn.revPBE', 'O.LDA.gz', 'Te.16.dzp.basis', 'Cr.revPBE', 'Cl.PBE', 'Pd.10.revPBE', 'COPYING', 'Ba.RPBE.gz', 'Ir.9.dzp.basis.gz', 'Pb.revPBE', 'Xe.revPBE', 'Li.PBE.gz', 'Ar.PBE', 'H.PBE.gz', 'V.5.PBE', 'He.dzp.basis', 'Pt.10.revPBE', 'S.LDA.gz', 'Xe.GLLBSC.gz', 'Zn.RPBE', 'H.dzp.basis.gz', 'Cl.LDA.gz', 'Re.RPBE', 'H.RPBE', 'Ta.dzp.basis.gz', 'Os.GLLBSC', 'Cr.PBE.gz', 'Rn.GLLBSC', 'Ga.LDA.gz', 'Li.revPBE', 'Ir.9.RPBE.gz', 'Te.PBE.gz', 'Sc.LDA.gz', 'V.5.dzp.basis', 'Sr.revPBE', 'K.dzp.basis', 'Na.revPBE.gz', 'Ge.LDA.gz', 'As.RPBE', 'Ar.RPBE.gz', 'Pt.10.PBE.gz', 'Pb.RPBE', 'Re.LDA', 'Ca.PBE.gz', 'Kr.PBE', 'Au.dzp.basis', 'Mn.7.PBE', 'Ru.dzp.basis.gz', 'Pt.10.dzp.basis', 'phi-0.500-1.000-20.000-21-201.txt', 'Hf.LDA', 'Mn.7.GLLBSC.gz', 'Hf.revPBE', 'Ir.PBE.gz', 'Kr.GLLBSC', 'Ni.PBE', 'S.RPBE', 'Pt.10.revPBE.gz', 'Ag.dzp.basis', 'Rb.revPBE', 'Cl.dzp.basis.gz', 'Ti.dzp.basis', 'Cu.GLLBSC.gz', 'Sc.RPBE', 'Ba.LDA', 'Re.dzp.basis.gz', 'Te.dzp.basis.gz', 'Y.PBE', 'Tl.revPBE.gz', 'V.PBE.gz', 'N.dzp.basis.gz', 'Mo.LDA.gz', 'Pb.PBE', 'Hg.GLLBSC', 'Ar.dzp.basis.gz', 'O.PBE', 'W.6.RPBE.gz', 'W.6.revPBE', 'Os.dzp.basis', 'Ru.8.LDA.gz', 'I.dzp.basis.gz', 'Fe.GLLBSC.gz', 'Bi.GLLBSC', 'Ag.11.revPBE.gz', 'Mo.6.dzp.basis.gz', 'Ti.revPBE', 'Br.RPBE', 'Pb.GLLBSC.gz', 'Ir.9.PBE.gz', 'Au.LDA', 'Cr.RPBE', 'Ne.PBE.gz', 'W.6.PBE.gz', 'Re.RPBE.gz', 'Nb.5.RPBE.gz', 'Pb.dzp.basis.gz', 'As.GLLBSC.gz', 'Te.PBE', 'He.revPBE', 'N.PBE', 'Nb.revPBE.gz', 'Br.LDA', 'Cu.RPBE', 'Rb.dzp.basis.gz', 'Nb.LDA', 'Ir.LDA.gz', 'Mo.6.LDA.gz', 'Ba.LDA.gz', 'Br.GLLBSC.gz', 'Re.PBE', 'Au.GLLBSC', 'Ta.5.revPBE', 'Te.RPBE.gz', 'Ba.GLLBSC', 'K.PBE.gz', 'Nb.RPBE', 'Cr.14.PBE.gz', 'Mg.revPBE', 'Mo.GLLBSC', 'O.revPBE.gz', 'Br.PBE', 'Os.8.dzp.basis.gz', 'Mo.PBE', 'Pt.LDA.gz', 'Hf.PBE.gz', 'O.LDA', 'Si.PBE', 'O.dzp.basis', 'Te.16.revPBE.gz', 'Sr.PBE', 'Os.PBE.gz', 'Re.LDA.gz', 'Cl.revPBE', 'Os.8.RPBE', 'Mg.LDA', 'Zn.revPBE', 'Os.PBE', 'Na.RPBE.gz', 'Re.revPBE.gz', 'Be.RPBE.gz', 'Li.dzp.basis', 'Xe.PBE', 'I.LDA.gz', 'Rh.PBE.gz', 'Ca.PBE', 'Pt.revPBE.gz', 'Ir.revPBE', 'Ru.8.revPBE', 'Pd.10.RPBE.gz', 'Cs.GLLBSC', 'Be.GLLBSC', 'V.5.RPBE', 'Ni.RPBE.gz', 'Te.16.RPBE.gz', 'Ta.5.LDA.gz', 'Y.GLLBSC', 'Bi.revPBE', 'Na.LDA.gz', 'V.RPBE.gz', 'Ag.11.LDA.gz', 'Cl.LDA', 'Zr.dzp.basis', 'Cr.14.dzp.basis', 'Be.GLLBSC.gz', 'Ge.RPBE', 'Cr.dzp.basis.gz', 'P.revPBE.gz', 'In.revPBE', 'C.PBE.gz', 'Rb.PBE.gz', 'Kr.dzp.basis.gz', 'Rn.RPBE.gz', 'Pb.LDA.gz', 'Cl.GLLBSC', 'Rh.9.RPBE.gz', 'W.LDA.gz', 'Ne.dzp.basis', 'Pd.GLLBSC.gz', 'B.revPBE.gz', 'Ru.dzp.basis', 'Bi.dzp.basis.gz', 'B.RPBE', 'Si.RPBE.gz', 'Cr.GLLBSC.gz', 'Pd.PBE', 'Re.dzp.basis', 'Ir.PBE', 'Ta.5.dzp.basis', 'P.GLLBSC', 'Mn.LDA.gz', 'Mg.PBE.gz', 'P.GLLBSC.gz', 'Pt.10.GLLBSC.gz', 'Na.1.PBE', 'W.6.dzp.basis.gz', 'Cr.dzp.basis', 'I.revPBE.gz', 'Hg.dzp.basis.gz', 'F.dzp.basis.gz', 'Sb.RPBE.gz', 'H.revPBE', 'W.6.revPBE.gz', 'Sn.GLLBSC', 'Sc.revPBE.gz', 'Mn.7.RPBE', 'K.revPBE', 'Ta.revPBE', 'Tl.GLLBSC.gz', 'Rh.LDA.gz', 'Pt.revPBE', 'Ag.11.revPBE', 'Te.revPBE', 'Be.revPBE.gz', 'Sb.dzp.basis', 'Cs.LDA', 'Cs.revPBE.gz', 'O.RPBE.gz', 'Na.dzp.basis.gz', 'Al.LDA.gz', 'Rn.PBE.gz', 'Ca.GLLBSC.gz', 'Nb.5.dzp.basis.gz', 'Al.revPBE.gz', 'Ta.RPBE.gz', 'Mn.GLLBSC', 'He.GLLBSC.gz', 'C.revPBE.gz', 'W.6.PBE', 'K.LDA.gz', 'Rb.dzp.basis', 'Co.dzp.basis', 'O.GLLBSC', 'Mn.7.dzp.basis', 'Y.dzp.basis', 'Si.GLLBSC.gz', 'Os.revPBE.gz', 'Ni.10.PBE.gz', 'Ar.LDA.gz', 'Nb.5.PBE.gz', 'P.RPBE', 'Cs.PBE', 'As.PBE', 'F.dzp.basis', 'Ni.10.PBE', 'Zr.RPBE', 'Ni.revPBE.gz', 'V.GLLBSC.gz', 'Pd.10.LDA.gz', 'B.dzp.basis.gz', 'Rh.GLLBSC.gz', 'Pb.revPBE.gz', 'Tl.LDA.gz', 'Ir.9.dzp.basis', 'V.PBE', 'Hf.RPBE', 'Ca.RPBE', 'S.PBE.gz', 'Zr.LDA.gz', 'Hg.revPBE', 'Co.dzp.basis.gz', 'Sr.RPBE.gz', 'Y.LDA.gz', 'Na.1.RPBE', 'N.GLLBSC.gz', 'Xe.dzp.basis.gz', 'As.LDA', 'As.revPBE', 'Ni.10.LDA', 'Se.LDA', 'S.GLLBSC.gz', 'Ir.RPBE', 'Ga.revPBE', 'Sr.GLLBSC', 'Ag.11.dzp.basis', 'W.GLLBSC', 'Rh.9.LDA', 'W.6.LDA.gz', 'Sr.LDA', 'W.6.LDA', 'Ta.5.LDA', 'Pt.dzp.basis', 'Ru.PBE.gz', 'As.GLLBSC', 'In.GLLBSC.gz', 'Se.revPBE.gz', 'Se.dzp.basis', 'W.GLLBSC.gz', 'B.LDA', 'Sc.LDA', 'Zn.dzp.basis.gz', 'Rb.revPBE.gz', 'Nb.PBE.gz', 'Ni.10.revPBE.gz', 'Te.16.revPBE', 'Mo.6.GLLBSC', 'Nb.RPBE.gz', 'Na.1.revPBE', 'Na.GLLBSC.gz', 'Os.RPBE', 'Sc.dzp.basis', 'Co.PBE', 'Mn.LDA', 'Cl.RPBE.gz', 'Ti.PBE', 'Hg.LDA.gz', 'Ta.5.GLLBSC.gz', 'Mn.7.RPBE.gz', 'Ni.10.RPBE.gz', 'Pt.10.RPBE.gz', 'F.PBE.gz', 'Cs.dzp.basis.gz', 'Ru.PBE', 'In.dzp.basis.gz', 'Ta.dzp.basis', 'Mo.LDA', 'W.dzp.basis.gz', 'Be.revPBE', 'S.revPBE.gz', 'W.revPBE.gz', 'Al.GLLBSC.gz', 'B.revPBE', 'Ag.dzp.basis.gz', 'Sb.RPBE', 'Mn.7.revPBE.gz', 'Sb.dzp.basis.gz', 'He.RPBE.gz', 'Pt.10.LDA.gz', 'Ir.LDA', 'Re.GLLBSC.gz', 'V.LDA.gz', 'Cd.dzp.basis.gz', 'Be.dzp.basis', 'Cr.14.dzp.basis.gz', 'Pt.10.PBE', 'N.revPBE']\n",
            "GPAW_SETUP_PATH: /content/gpaw-setups-24.1.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "## Atomic Simulation Environment (ASE)\n",
        "GPAW is well integrated with the Atomic Simulation Environment (ASE), providing a flexible and dynamic user interface"
      ],
      "metadata": {
        "id": "mqU27ehf7qRm"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Import ASE and GPAW and run your calculation\n",
        "from ase import Atoms\n",
        "from gpaw import GPAW\n",
        "\n",
        "# Define the atomic structure\n",
        "d = 0.74\n",
        "a = 6.0\n",
        "\n",
        "h2 = Atoms('H2',\n",
        "              positions=[(0, 0, 0),\n",
        "                         (0, 0, d)],\n",
        "              cell=(a, a, a))\n",
        "h2.center()\n",
        "# Initialize GPAW calculator without specifying the 'setups' parameter\n",
        "calc = GPAW(mode='fd', nbands=2, txt='h2.txt')\n",
        "h2.calc = calc\n",
        "\n",
        "# Run the calculation\n",
        "print(\"Forces on atoms:\", h2.get_forces())\n",
        "print(\"Energies on atoms:\", h2.get_total_energy())\n"
      ],
      "metadata": {
        "id": "H62nbAHQ3gbP",
        "outputId": "3a271cc5-3d9f-48c4-8091-37535c4315ba",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Forces on atoms: [[ 0.          0.         -0.84512566]\n",
            " [ 0.          0.          0.84512566]]\n",
            "Energies on atoms: -6.627349275456466\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Install POVRAY: visualization of atoms\n",
        "\n",
        "The Persistence of Vision Ray Tracer, most commonly acronymed as POV-Ray, is a cross-platform ray-tracing program that generates images from a text-based scene description."
      ],
      "metadata": {
        "id": "x-D3qC5T8dYY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!sudo apt-get install povray  ## visulization program"
      ],
      "metadata": {
        "id": "wCO1NkAB8cDS",
        "outputId": "f002e1d4-ca41-4ea1-b5e9-7684177640f7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Reading package lists... Done\n",
            "Building dependency tree... Done\n",
            "Reading state information... Done\n",
            "The following additional packages will be installed:\n",
            "  fonts-povray libsdl1.2debian povray-includes\n",
            "Suggested packages:\n",
            "  povray-doc povray-examples\n",
            "The following NEW packages will be installed:\n",
            "  fonts-povray libsdl1.2debian povray povray-includes\n",
            "0 upgraded, 4 newly installed, 0 to remove and 49 not upgraded.\n",
            "Need to get 1,792 kB of archives.\n",
            "After this operation, 5,199 kB of additional disk space will be used.\n",
            "Get:1 http://archive.ubuntu.com/ubuntu jammy/universe amd64 fonts-povray all 1:3.7.0.10-1 [70.0 kB]\n",
            "Get:2 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libsdl1.2debian amd64 1.2.15+dfsg2-6 [177 kB]\n",
            "Get:3 http://archive.ubuntu.com/ubuntu jammy/universe amd64 povray amd64 1:3.7.0.10-1 [1,312 kB]\n",
            "Get:4 http://archive.ubuntu.com/ubuntu jammy/universe amd64 povray-includes all 1:3.7.0.10-1 [233 kB]\n",
            "Fetched 1,792 kB in 0s (4,761 kB/s)\n",
            "debconf: unable to initialize frontend: Dialog\n",
            "debconf: (No usable dialog-like program is installed, so the dialog based frontend cannot be used. at /usr/share/perl5/Debconf/FrontEnd/Dialog.pm line 78, <> line 4.)\n",
            "debconf: falling back to frontend: Readline\n",
            "debconf: unable to initialize frontend: Readline\n",
            "debconf: (This frontend requires a controlling tty.)\n",
            "debconf: falling back to frontend: Teletype\n",
            "dpkg-preconfigure: unable to re-open stdin: \n",
            "Selecting previously unselected package fonts-povray.\n",
            "(Reading database ... 123740 files and directories currently installed.)\n",
            "Preparing to unpack .../fonts-povray_1%3a3.7.0.10-1_all.deb ...\n",
            "Unpacking fonts-povray (1:3.7.0.10-1) ...\n",
            "Selecting previously unselected package libsdl1.2debian:amd64.\n",
            "Preparing to unpack .../libsdl1.2debian_1.2.15+dfsg2-6_amd64.deb ...\n",
            "Unpacking libsdl1.2debian:amd64 (1.2.15+dfsg2-6) ...\n",
            "Selecting previously unselected package povray.\n",
            "Preparing to unpack .../povray_1%3a3.7.0.10-1_amd64.deb ...\n",
            "Unpacking povray (1:3.7.0.10-1) ...\n",
            "Selecting previously unselected package povray-includes.\n",
            "Preparing to unpack .../povray-includes_1%3a3.7.0.10-1_all.deb ...\n",
            "Unpacking povray-includes (1:3.7.0.10-1) ...\n",
            "Setting up libsdl1.2debian:amd64 (1.2.15+dfsg2-6) ...\n",
            "Setting up fonts-povray (1:3.7.0.10-1) ...\n",
            "Setting up povray (1:3.7.0.10-1) ...\n",
            "Setting up povray-includes (1:3.7.0.10-1) ...\n",
            "Processing triggers for libc-bin (2.35-0ubuntu3.4) ...\n",
            "/sbin/ldconfig.real: /usr/local/lib/libtbbbind.so.3 is not a symbolic link\n",
            "\n",
            "/sbin/ldconfig.real: /usr/local/lib/libur_adapter_level_zero.so.0 is not a symbolic link\n",
            "\n",
            "/sbin/ldconfig.real: /usr/local/lib/libtbbbind_2_0.so.3 is not a symbolic link\n",
            "\n",
            "/sbin/ldconfig.real: /usr/local/lib/libur_loader.so.0 is not a symbolic link\n",
            "\n",
            "/sbin/ldconfig.real: /usr/local/lib/libtbbmalloc_proxy.so.2 is not a symbolic link\n",
            "\n",
            "/sbin/ldconfig.real: /usr/local/lib/libtbb.so.12 is not a symbolic link\n",
            "\n",
            "/sbin/ldconfig.real: /usr/local/lib/libtbbbind_2_5.so.3 is not a symbolic link\n",
            "\n",
            "/sbin/ldconfig.real: /usr/local/lib/libur_adapter_opencl.so.0 is not a symbolic link\n",
            "\n",
            "/sbin/ldconfig.real: /usr/local/lib/libtbbmalloc.so.2 is not a symbolic link\n",
            "\n",
            "Processing triggers for man-db (2.10.2-1) ...\n",
            "Processing triggers for fontconfig (2.13.1-4.2ubuntu5) ...\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "import shutil\n",
        "from ase.io import write  # Import the write function from ASE\n",
        "from PIL import Image\n",
        "from IPython.display import display  # Import display for Jupyter Notebooks\n",
        "\n",
        "\n",
        "def visual(structure, max_size=(200, 200), stretch_y=1.0, rotation='15z,-60x', png_save_path='./'):\n",
        "    renderer = write('./temp.pov', structure, rotation=rotation)\n",
        "    renderer.render()\n",
        "    image_path = './temp.png'\n",
        "    img = Image.open(image_path)\n",
        "\n",
        "    # Calculate new size with stretch factor\n",
        "    new_size = (max_size[0], int(max_size[1] * stretch_y))\n",
        "    img = img.resize(new_size, Image.LANCZOS)\n",
        "    display(img)\n",
        "\n",
        "    # Move files to output directory\n",
        "    files = ['./temp.ini', './temp.pov', './temp.png']\n",
        "    destination = './output/'\n",
        "\n",
        "    # Ensure destination directory exists\n",
        "    os.makedirs(destination, exist_ok=True)\n",
        "\n",
        "    for file in files:\n",
        "        # Remove the file in the destination directory if it exists\n",
        "        if os.path.isfile(os.path.join(destination, os.path.basename(file))):\n",
        "            os.remove(os.path.join(destination, os.path.basename(file)))\n",
        "\n",
        "        if file == './temp.png':\n",
        "            new_file_name = png_save_path + f'temp.png'\n",
        "        else:\n",
        "            new_file_name = os.path.basename(file)\n",
        "        shutil.move(file, os.path.join(destination, new_file_name))\n"
      ],
      "metadata": {
        "id": "RmmT60Pz85A3"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "visual(h2)"
      ],
      "metadata": {
        "id": "j71FXOke9R0j",
        "outputId": "c6b740a5-08a5-4650-af27-b9c1bd6a7d06",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 217
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<PIL.Image.Image image mode=RGBA size=200x200>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Bulk Calculations"
      ],
      "metadata": {
        "id": "6PWGPwCc86Ug"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "\"\"\"Bulk Al(fcc) test\"\"\"\n",
        "from ase import Atoms\n",
        "from ase.visualize import view\n",
        "from gpaw import GPAW, PW\n",
        "\n",
        "name = 'Al-fcc'\n",
        "a = 4.05  # fcc lattice parameter\n",
        "b = a / 2\n",
        "bulk = Atoms('Al',\n",
        "             cell=[[0, b, b],\n",
        "                   [b, 0, b],\n",
        "                   [b, b, 0]],\n",
        "             pbc=True)\n",
        "\n",
        "k = 4\n",
        "calc = GPAW(mode=PW(300),       # cutoff\n",
        "            kpts=(k, k, k),     # k-points\n",
        "            txt=name + '.txt')  # output file\n",
        "\n",
        "bulk.calc = calc\n",
        "\n",
        "energy = bulk.get_potential_energy()\n",
        "calc.write(name + '.gpw')\n",
        "print('Energy:', energy, 'eV')"
      ],
      "metadata": {
        "id": "Rln_FuTwSx1I",
        "outputId": "c2c01543-cfea-4478-f715-ad6f371b14dc",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Energy: -4.122151616078063 eV\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "visual(bulk)"
      ],
      "metadata": {
        "id": "XRXfsj0k_NVI",
        "outputId": "389b1b4d-895c-4a5a-8b2f-fcb94e272d8f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 217
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<PIL.Image.Image image mode=RGBA size=200x200>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import time\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import pandas as pd\n",
        "from ase import Atoms\n",
        "from gpaw import GPAW, PW\n",
        "\n",
        "# Testing k-points\n",
        "k_values = [2, 4, 6, 8, 10]  # Different k-point grids to test\n",
        "energies_k = []\n",
        "times_k = []\n",
        "\n",
        "a = 4.05  # fcc lattice parameter\n",
        "b = a / 2\n",
        "\n",
        "# Loop over different k-points\n",
        "for k in k_values:\n",
        "    # Define the bulk FCC structure\n",
        "    bulk = Atoms('Al',\n",
        "                 cell=[[0, b, b],\n",
        "                       [b, 0, b],\n",
        "                       [b, b, 0]],\n",
        "                 pbc=True)\n",
        "\n",
        "    # Set up the GPAW calculator\n",
        "    calc = GPAW(mode=PW(300),  # Fixed cutoff energy\n",
        "                kpts=(k, k, k),  # Varying k-points\n",
        "                txt=f'Al-fcc-k{k}.txt')\n",
        "\n",
        "    # Attach the calculator to the bulk structure\n",
        "    bulk.calc = calc\n",
        "\n",
        "    # Start timing\n",
        "    start_time = time.time()\n",
        "\n",
        "    # Calculate the potential energy\n",
        "    energy = bulk.get_potential_energy()\n",
        "\n",
        "    # End timing\n",
        "    end_time = time.time()\n",
        "\n",
        "    # Calculate the elapsed time\n",
        "    elapsed_time = end_time - start_time\n",
        "\n",
        "    # Store the energy and time\n",
        "    energies_k.append(energy)\n",
        "    times_k.append(elapsed_time)\n",
        "\n",
        "    # Save the calculator state\n",
        "    calc.write(f'Al-fcc-k{k}.gpw')\n",
        "    del bulk.calc  # Clean up\n",
        "\n",
        "# Plot k-points vs. energy\n",
        "plt.figure()\n",
        "plt.plot(k_values, energies_k, marker='o', linestyle='-')\n",
        "plt.xlabel('K-points')\n",
        "plt.ylabel('Energy (eV)')\n",
        "plt.title('Energy vs. K-points')\n",
        "plt.grid()\n",
        "plt.show()\n",
        "\n",
        "# Create a DataFrame for the time taken for different k-points\n",
        "time_k_table = pd.DataFrame({'K-points': k_values, 'Time (s)': times_k})\n",
        "print(time_k_table)\n",
        "\n",
        "# Testing plane-wave cutoff energies\n",
        "pw_values = np.linspace(200, 600, 5)  # Different PW values to test\n",
        "energies_pw = []\n",
        "times_pw = []\n",
        "\n",
        "# Loop over different PW cutoff energies\n",
        "for pw in pw_values:\n",
        "    # Define the bulk FCC structure\n",
        "    bulk = Atoms('Al',\n",
        "                 cell=[[0, b, b],\n",
        "                       [b, 0, b],\n",
        "                       [b, b, 0]],\n",
        "                 pbc=True)\n",
        "\n",
        "    # Set up the GPAW calculator\n",
        "    calc = GPAW(mode=PW(pw),  # Varying cutoff energy\n",
        "                kpts=(4, 4, 4),  # Fixed k-points\n",
        "                txt=f'Al-fcc-pw{pw:.0f}.txt')\n",
        "\n",
        "    # Attach the calculator to the bulk structure\n",
        "    bulk.calc = calc\n",
        "\n",
        "    # Start timing\n",
        "    start_time = time.time()\n",
        "\n",
        "    # Calculate the potential energy\n",
        "    energy = bulk.get_potential_energy()\n",
        "\n",
        "    # End timing\n",
        "    end_time = time.time()\n",
        "\n",
        "    # Calculate the elapsed time\n",
        "    elapsed_time = end_time - start_time\n",
        "\n",
        "    # Store the energy and time\n",
        "    energies_pw.append(energy)\n",
        "    times_pw.append(elapsed_time)\n",
        "\n",
        "    # Save the calculator state\n",
        "    calc.write(f'Al-fcc-pw{pw:.0f}.gpw')\n",
        "    del bulk.calc  # Clean up\n",
        "\n",
        "# Plot PW values vs. energy\n",
        "plt.figure()\n",
        "plt.plot(pw_values, energies_pw, marker='o', linestyle='-')\n",
        "plt.xlabel('PW Cutoff (eV)')\n",
        "plt.ylabel('Energy (eV)')\n",
        "plt.title('Energy vs. PW Cutoff')\n",
        "plt.grid()\n",
        "plt.show()\n",
        "\n",
        "# Create a DataFrame for the time taken for different PW values\n",
        "time_pw_table = pd.DataFrame({'PW Cutoff (eV)': pw_values, 'Time (s)': times_pw})\n",
        "print(time_pw_table)\n"
      ],
      "metadata": {
        "id": "_3dnl_kpWufR"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "from ase import Atoms\n",
        "from gpaw import GPAW, PW\n",
        "\n",
        "# Set up values for lattice parameter 'a'\n",
        "a_values = np.linspace(3.8, 4.2, 10)  # Adjust the range and number of points as needed\n",
        "energies = []\n",
        "volumes = []\n",
        "\n",
        "# Loop over each lattice parameter to calculate energy\n",
        "for a in a_values:\n",
        "    b = a / 2\n",
        "    # Define the bulk structure\n",
        "    bulk = Atoms('Al',\n",
        "                 cell=[[0, b, b],\n",
        "                       [b, 0, b],\n",
        "                       [b, b, 0]],\n",
        "                 pbc=True)\n",
        "\n",
        "    # Set up the calculator\n",
        "    k = 4\n",
        "    calc = GPAW(mode=PW(300),       # Plane-wave cutoff\n",
        "                kpts=(k, k, k),     # k-points grid\n",
        "                txt=f'Al-fcc-a{a:.2f}.txt')  # Output file with varying name\n",
        "\n",
        "    # Attach the calculator to the bulk structure\n",
        "    bulk.calc = calc\n",
        "\n",
        "    # Calculate the potential energy\n",
        "    energy = bulk.get_potential_energy()\n",
        "    volume = bulk.get_volume()\n",
        "\n",
        "    # Store the energy and volume\n",
        "    energies.append(energy)\n",
        "    volumes.append(volume)\n",
        "\n",
        "    # Clean up the calculator\n",
        "    calc.write(f'Al-fcc-a{a:.2f}.gpw')\n",
        "    del bulk.calc  # Free memory\n",
        "\n",
        "# Plot EOS: Energy vs. Volume\n",
        "plt.figure()\n",
        "plt.plot(volumes, energies, marker='o', linestyle='-')\n",
        "plt.xlabel('Volume (Å³)')\n",
        "plt.ylabel('Energy (eV)')\n",
        "plt.title('Equation of State for Al (FCC)')\n",
        "plt.grid()\n",
        "plt.show()\n"
      ],
      "metadata": {
        "id": "M2Nq8JlgUT5h"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "slab"
      ],
      "metadata": {
        "id": "0SDUKPS1YZ42"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import time  # Import the time module\n",
        "from ase.build import fcc100\n",
        "from gpaw import GPAW\n",
        "\n",
        "# Initialize the parameters\n",
        "k = 1\n",
        "N = 4\n",
        "size = 2\n",
        "# Create the slab\n",
        "fcc = fcc100('Al', (size, size, N), a=4, vacuum=7.5)\n",
        "fcc.center(axis=2)\n",
        "\n",
        "# Set up the GPAW calculator\n",
        "calc = GPAW(mode='fd',\n",
        "            nbands=N * 3 * size**2,\n",
        "            kpts=(k, k, 1),\n",
        "            h=0.25,\n",
        "            txt='slab-%d.txt' % N)\n",
        "\n",
        "# Attach the calculator to the slab\n",
        "fcc.calc = calc\n",
        "\n",
        "# Start timing\n",
        "start_time = time.time()\n",
        "\n",
        "# Run the calculation to get the potential energy\n",
        "e = fcc.get_potential_energy()\n",
        "\n",
        "# End timing\n",
        "end_time = time.time()\n",
        "\n",
        "# Calculate the elapsed time\n",
        "elapsed_time = end_time - start_time\n",
        "\n",
        "# Save the calculator state\n",
        "calc.write('slab-%d.gpw' % N)\n",
        "\n",
        "# Print the energy and the elapsed time\n",
        "print(f'Potential Energy: {e} eV')\n",
        "print(f'Time taken: {elapsed_time:.2f} seconds')\n"
      ],
      "metadata": {
        "id": "FDTqLjs-Tbn1"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}