whu-maple / ml-for-band-structure-predictionLinks
The PyTorch implementation of ML framework for predicting band structure, taking an example of graphene nanoribbon systems.
☆11Updated 3 years ago
Alternatives and similar repositories for ml-for-band-structure-prediction
Users that are interested in ml-for-band-structure-prediction are comparing it to the libraries listed below
Sorting:
- Topological analysis for Li local space, site, pathway in crystal structures☆13Updated 6 years ago
- ☆14Updated 2 years ago
- Code repository for a tutorial based on the "Direct prediction of phonon density of states with Euclidean neural networks"☆31Updated 2 years ago
- The thermal conductivity of a molecular dynamics system is calculated using the Green-Kubo fluctuation Dissipation Theorem☆14Updated 4 years ago
- Unsupervised identification and analysis of ion-hopping events in solid state electrolytes.☆14Updated last month
- Graph neural network prediction of electronic Hamiltonians in atomic orbital representation with many body messages☆27Updated 3 months ago
- Random symmetric initialization of crystals☆25Updated 8 years ago
- Python scripts to postprocess Quantum Espresso calclations.☆20Updated 5 years ago
- MaterialsCoord: infrastructure to benchmark crystal structure coordination algorithms☆19Updated 2 years ago
- Analysing molecular dynamics simulations of crystalline materials using site occupations☆18Updated this week
- A collection of tips, scripts, tools and files to improve your workflow, or simply help you start with ab initio Molecular Dynamics (AIMD…☆27Updated 2 years ago
- The FPTE package is a collection of tools for finite pressure temperature elastic constants calculation. Features include, but are not l…☆17Updated last year
- Reproduction of CGCNN for predicting material properties☆23Updated 2 weeks ago
- Tutorial exercises for the OPTIMADE API☆17Updated 2 years ago
- Phonons from ML force fields☆23Updated 6 months ago
- Active learning workflow developed as a part of the upcoming article "Machine Learning Inter-Atomic Potentials Generation Driven by Activ…☆28Updated 4 years ago
- ☆17Updated 8 months ago
- ☆22Updated 2 years ago
- A Benchmarking Framework for Crystal GNNs☆20Updated 2 years ago
- A flexible workflow for on-the-fly learning of interatomic potential models.☆31Updated this week
- VASP Integrated Supporting Environment☆27Updated 2 months ago
- Useful scripts in Computaional Material Science.☆18Updated 3 weeks ago
- SPINNER (Structure Prediction of Inorganic crystals using Neural Network potentials with Evolutionary and Random searches)☆15Updated last year
- SLABCC: Total energy correction code for charged periodic slab models. Project is currently maintained at https://codeberg.org/meisam/sla…☆17Updated 11 months ago
- A simple BASH script for extraction of infared intensities from DFPT calculation output by VASP code.☆26Updated last year
- Cross-platform Optimizer for ML Interatomic Potentials☆23Updated 4 months ago
- ☆21Updated last year
- DeepH-dock seamlessly integrates deep learning with first-principles calculations. It serves as a modular and extensible bridge, function…☆24Updated this week
- ☆40Updated last month
- Allen-Feldman thermal conductivity compatible to GULP implementation☆21Updated 9 months ago