usnistgov / chipsff
Evaluation of universal machine learning force-fields https://arxiv.org/abs/2412.10516
☆30Updated 3 weeks ago
Alternatives and similar repositories for chipsff:
Users that are interested in chipsff are comparing it to the libraries listed below
- A collection of files related to machine learning force fields☆21Updated last year
- A molecular simulation package integrating MLFFs in MOFs for DAC☆24Updated 2 months ago
- Fair and transparent benchmark of machine-learned interatomic potentials (MLIPs), beyond basic error metrics☆56Updated 2 weeks ago
- Benchmarking foundation Machine Learning Potentials with Lattice Thermal Conductivity from Anharmonic Phonons☆15Updated 4 months ago
- Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned interatomic potentials (MLIP…☆70Updated last week
- A python package to deconstruct MOFs into building units, compute porosity, remove unbound guests and compute cheminfomatic data of build…☆18Updated 3 months ago
- ⚛ download and manipulate atomistic datasets☆40Updated 2 months ago
- Quick Uncertainty and Entropy via STructural Similarity☆33Updated last month
- Python package to interact with high-dimensional representations of the chemical elements☆40Updated last week
- Compute neighbor lists for atomistic systems☆39Updated 2 weeks ago
- GRACE models and gracemaker (as implemented in TensorPotential package)☆41Updated 3 weeks ago
- Software for evaluating pareto-optimal synthesis pathways☆25Updated 8 months ago
- A cookbook with recipes for atomic-scale modeling of materials and molecules☆18Updated this week
- Vote on whether you think predicted crystal structures could be synthesised☆17Updated 7 months ago
- A fully featured ASE calculator for xTB☆16Updated 4 months ago
- A unified platform for fine-tuning atomistic foundation models in chemistry and materials science☆18Updated this week
- Alchemical machine learning interatomic potentials☆14Updated 3 months ago
- SLMat: ServerLess Materials Design Toolkit, Preprint: https://doi.org/10.26434/chemrxiv-2024-fqq27☆19Updated last month
- WhereWulff: A semi-autonomous workflow for systematic catalyst surface reactivity under reaction conditions☆31Updated 10 months ago
- Force-field-enhanced Neural Networks optimized library☆28Updated this week
- MACE_Osaka24 models☆14Updated 2 months ago
- ☆20Updated 11 months ago
- Collection of tutorials to use the MACE machine learning force field.☆43Updated 5 months ago
- Tutorial exercises for the OPTIMADE API☆15Updated last year
- ☆24Updated 10 months ago
- A software for automating materials science computations☆30Updated last month
- Adds Orb Model functionality to LAMMPS via Python wrapping☆13Updated 4 months ago
- ☆10Updated last week
- Some tutorial-style examples for validating machine-learned interatomic potentials☆31Updated last year