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Merge pull request #249 from Exabyte-io/dev
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‎other/experiments/mtrsm/README.md‎

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## Usage
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### With standalone scripts
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Install dependencies (using pyenv):
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```bash
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pyenv local 3.10.13
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python -m venv .venv-3.10.13
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source .venv-3.10.13/bin/activate
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pip install mattersim
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```
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Run the script(s):
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```bash
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source .venv-3.10.13/bin/activate
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python <script_name.py>
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```
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### With JupyterLab
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Install dependencies:
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```bash
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pyenv local 3.10.13
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python -m venv .venv-3.10.13
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source .venv-3.10.13/bin/activate
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pip install "mat3ra-api-examples[forcefields]"
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```
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As below. With `pyenv`.
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```bash
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pyenv local 3.10.13
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python -m venv .venv-3.10.13
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source .venv-3.10.13/bin/activate
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pip install mattersim
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```
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See the included notebook.

‎other/experiments/mtrsm/calculate_energy_for_vacancy_mattersim.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "ba05a8b053f7ed1f",
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"metadata": {},
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"source": [
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"# Calculate Vacancy Formation Energy in Silicon using MatterSim Potential\n",
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"\n",
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"This notebook demonstrates how to compute the vacancy formation energy in silicon using the MatterSim potential within the Mat3ra framework.\n",
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"\n",
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"## Methodology\n",
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"\n",
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"The vacancy formation energy is calculated using the following approach:\n",
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"\n",
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"1. **Create pristine supercell**: Build a silicon supercell from the unit cell and relax it using MatterSim potential\n",
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"2. **Create vacancy**: Remove a single atom from the center of the supercell\n",
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"3. **Relax vacancy structure**: Optimize the geometry of the defective supercell\n",
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"4. **Calculate formation energy**: Compute the energy difference according to the formula:\n",
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" \n",
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" E_formation = E_vacancy - (N_vacancy/N_bulk) × E_bulk\n",
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" \n",
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" where:\n",
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" - E_vacancy: Total energy of the supercell with vacancy\n",
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" - E_bulk: Total energy of the pristine supercell\n",
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" - N_vacancy: Number of atoms in vacancy supercell\n",
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" - N_bulk: Number of atoms in pristine supercell"
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]
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},
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{
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"cell_type": "code",
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"id": "39067e0f5d2c0ffb",
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"metadata": {},
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"source": [
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"# Install required packages if not already installed\n",
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"# INFO: if not installed correctly, clear environment and run `pip install .[forcefields]` in the terminal\n",
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"try:\n",
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" import mattersim\n",
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"except ImportError:\n",
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" import subprocess, sys\n",
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" subprocess.run([sys.executable, \"-m\", \"pip\", \"install\", \".[forcefields]\", \"--quiet\"], check=False)\n",
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" import mattersim"
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],
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"id": "ad71b3bcdb13e36a",
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"metadata": {},
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"source": [
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"## 1. Prepare materials\n",
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"### 1.1. Load material data"
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]
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},
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{
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"cell_type": "code",
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"id": "2819d078b48216b9",
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"metadata": {},
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"source": [
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"from mat3ra.standata.materials import Materials\n",
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"from mat3ra.made.material import Material\n",
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"\n",
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"material = Material.create(Materials.get_by_name_first_match(\"Si\"))"
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],
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"id": "f011303e40ab0ee5",
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"metadata": {},
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"source": [
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"### 1.2. Add vacancy to material"
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]
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},
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{
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"cell_type": "code",
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"id": "b7e53d295d59fe89",
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"metadata": {},
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"source": [
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"from mat3ra.made.tools.helpers import create_vacancy, create_supercell\n",
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"\n",
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"supercell = create_supercell(material, scaling_factor=[2,2,2])\n",
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"material_with_vacancy = create_vacancy(supercell, coordinate=[0.5, 0.5, 0.5], placement_method=\"closest_site\")"
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],
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"id": "45c3dade8bcd52b3",
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"metadata": {},
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"source": [
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"## 1.3. Visualize materials"
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]
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},
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{
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"cell_type": "code",
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"id": "4b91a2ae59c983a3",
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"metadata": {},
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"source": [
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"from utils.visualize import visualize_materials\n",
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"\n",
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"visualize_materials([material, supercell, material_with_vacancy], rotation=\"-90x,-90y\")"
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],
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"id": "8ce27a1c8864c29f",
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"metadata": {},
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"source": [
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"## 2. Setup calculation\n",
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"### 2.1. Convert to ASE atoms"
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]
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},
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{
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"cell_type": "code",
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"id": "62b389e5458ce7c2",
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"metadata": {},
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"source": [
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"from mat3ra.made.tools.convert import to_ase\n",
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"\n",
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"material_atoms = to_ase(material)\n",
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"material_with_vacancy_atoms = to_ase(material_with_vacancy)"
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],
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"id": "c4c3b2a928a369ad",
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"metadata": {},
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"source": [
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"### 2.2. Setup MatterSim calculator"
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]
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},
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{
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"cell_type": "code",
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"id": "361cd269cb3e2db4",
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"metadata": {},
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"source": [
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"from mattersim.forcefield.potential import MatterSimCalculator\n",
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"from mattersim.applications.relax import Relaxer\n",
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"\n",
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"material_atoms.calc = MatterSimCalculator()\n",
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"material_with_vacancy_atoms.calc = MatterSimCalculator()\n"
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],
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"id": "8119275fe9ffb1d8",
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"metadata": {},
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"source": [
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"### 2.3. Relax structures"
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]
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},
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{
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"cell_type": "code",
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"id": "48cbd2f29d0cbd2c",
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"metadata": {},
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"source": [
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"relaxer = Relaxer(optimizer=\"BFGS\", constrain_symmetry=True)\n",
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"relaxer.relax(material_atoms, steps=500) # In-place relaxation\n",
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"relaxer.relax(material_with_vacancy_atoms, steps=500) # In-place relaxation\n"
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],
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"id": "116af57af6793bb",
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"metadata": {},
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"source": [
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"### 2.4. Visualize relaxed structures"
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]
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},
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{
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"cell_type": "code",
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"id": "6426cc56c5d51eef",
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"metadata": {},
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"source": [
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"from mat3ra.made.tools.convert import from_ase\n",
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"\n",
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"relaxed_material = Material.create(from_ase(material_atoms))\n",
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"relaxed_material_with_vacancy = Material.create(from_ase(material_with_vacancy_atoms))\n",
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"\n",
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"visualize_materials([relaxed_material, supercell, relaxed_material_with_vacancy], rotation=\"-90x,-90y\")"
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],
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"id": "7754f5d01964b082",
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"metadata": {},
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"source": [
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"## 3. Calculate vacancy formation energy\n",
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"\n",
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"### 3.1. Get energies and atom counts"
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]
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},
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{
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"cell_type": "code",
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"id": "2f4694776e7d1430",
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"metadata": {},
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"source": [
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"energy_bulk = material_atoms.get_potential_energy()\n",
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"n_atoms_bulk = len(material_atoms)\n",
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"energy_vacancy = material_with_vacancy_atoms.get_potential_energy()\n",
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"n_atoms_vac = len(material_with_vacancy_atoms)"
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],
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"id": "baae670f86c9b639",
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"metadata": {},
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"source": [
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"### 3.2. Calculate vacancy formation energy"
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]
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},
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{
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"cell_type": "code",
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"id": "430936d099f5b816",
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"metadata": {},
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"source": [
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"e_vacancy = energy_vacancy - (n_atoms_vac / n_atoms_bulk * energy_bulk)\n",
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"print(f\"Vacancy formation energy: {e_vacancy:.4f} eV\")\n"
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],
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"outputs": [],
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"execution_count": null
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},
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{
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"metadata": {},
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"cell_type": "code",
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"source": "",
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"id": "fa73a94409748e1c",
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"outputs": [],
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"execution_count": null
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

‎other/experiments/mtrsm/minimal_test.py‎

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import torch
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from loguru import logger
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from ase.build import bulk
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from ase.units import GPa
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from mattersim.forcefield import MatterSimCalculator
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device = "cuda" if torch.cuda.is_available() else "cpu"
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logger.info(f"Running MatterSim on {device}")
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si = bulk("Si", "diamond", a=5.43)
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si.calc = MatterSimCalculator(device=device)
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logger.info(f"Energy (eV) = {si.get_potential_energy()}")
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logger.info(f"Energy per atom (eV/atom) = {si.get_potential_energy()/len(si)}")
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logger.info(f"Forces of first atom (eV/A) = {si.get_forces()[0]}")
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logger.info(f"Stress[0][0] (eV/A^3) = {si.get_stress(voigt=False)[0][0]}")
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logger.info(f"Stress[0][0] (GPa) = {si.get_stress(voigt=False)[0][0] / GPa}")

‎other/experiments/mtrsm/phonon_dispersion.py‎

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import numpy as np
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from ase.build import bulk
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from ase.units import GPa
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from ase.visualize import view
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from mattersim.forcefield.potential import MatterSimCalculator
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from mattersim.applications.phonon import PhononWorkflow
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# initialize the structure of silicon
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si = bulk("Si")
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# attach the calculator to the atoms object
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si.calc = MatterSimCalculator()
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ph = PhononWorkflow(
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atoms=si,
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find_prim = False,
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work_dir = "./tmp/phonon_si_example",
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amplitude = 0.01,
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supercell_matrix = np.diag([4,4,4]),
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)
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has_imag, phonons = ph.run()
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print(f"Has imaginary phonon: {has_imag}")
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print(f"Phonon frequencies: {phonons}")
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‎other/experiments/mtrsm/structure_optimization.py‎

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import numpy as np
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from ase.build import bulk
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from ase.units import GPa
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from mattersim.forcefield.potential import MatterSimCalculator
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from mattersim.applications.relax import Relaxer
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# initialize the structure of silicon
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si = bulk("Si", "diamond", a=5.43)
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# perturb the structure
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si.positions += 0.1 * np.random.randn(len(si), 3)
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# attach the calculator to the atoms object
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si.calc = MatterSimCalculator()
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# initialize the relaxation object
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relaxer = Relaxer(
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optimizer="BFGS", # the optimization method
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filter="ExpCellFilter", # filter to apply to the cell
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constrain_symmetry=True, # whether to constrain the symmetry
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)
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relaxed_structure = relaxer.relax(si, steps=500)

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