learningmatter-mit / atom_by_atomLinks
Atom-by-atom design of metal oxide catalysts for the oxygen evolution reaction with Machine Learning
☆10Updated 2 years ago
Alternatives and similar repositories for atom_by_atom
Users that are interested in atom_by_atom are comparing it to the libraries listed below
Sorting:
- A unified platform for fine-tuning atomistic foundation models in chemistry and materials science☆65Updated last week
- Active Learning for Machine Learning Potentials☆62Updated last week
- ☆65Updated 4 years ago
- ☆72Updated 2 years ago
- Python package to interact with high-dimensional representations of the chemical elements☆46Updated this week
- GRACE models and gracemaker (as implemented in TensorPotential package)☆76Updated last week
- Particle-mesh based calculations of long-range interactions in PyTorch☆64Updated last month
- Automated creation and manipulation of Chemical Reaction Networks (CRNs) in heterogeneous catalysis, allowing the evaluation of species a…☆39Updated last week
- A package for Covalent Organic Frameworks structure assembly based on specific building block, topology and functional groups based on th…☆59Updated last month
- Heat capacity predictor for porous materials☆12Updated last year
- Python library for the construction of porous materials using topology and building blocks.☆79Updated 6 months ago
- PACMOF is a small and easy to use python library that uses machine Learning to quickly estimate partial atomic charges in metal-organic …☆17Updated last year
- Online resource for a practical course in machine learning for materials research at Imperial College London (MATE70026)☆97Updated last month
- Compiled binaries and sources of LAMMPS, redistributed by AdvanceSoft Corp.☆61Updated 4 months ago
- Pynta - an automated workflow for reaction path exploration on metallic surfaces☆40Updated 3 weeks ago
- Code for automated fitting of machine learned interatomic potentials.☆131Updated 2 weeks ago
- Zeolite Simulation Environment☆22Updated last month
- A... M... L...☆53Updated 3 years ago
- Strategies for the Construction of Neural-Network Based Machine-Learning Potentials (MLPs)☆28Updated 4 years ago
- GPU Monte Carlo Simulation Code with a taste of RASPA☆72Updated last week
- train and use graph-based ML models of potential energy surfaces☆114Updated this week
- Clean, Uniform and Refined with Automatic Tracking from Experimental Database (CURATED) COFs☆44Updated 2 years ago
- ☆64Updated 3 weeks ago
- PhaseForge is a framework for high-throughput alloy phase diagram prediction using machine learning interatomic potentials (MLIPs) integr…☆54Updated 3 weeks ago
- ☆107Updated this week
- LAMMPS pair styles for NequIP and Allegro deep learning interatomic potentials☆58Updated 2 months ago
- A python library for calculating materials properties from the PES☆125Updated this week
- MLP training for molecular systems☆54Updated last week
- PoreBlazer (v4.0) source code, examples, and geometric properties of porous materials calculated for the subset of 12,000 structures from…☆53Updated last year
- SIMPLE-NN(SNU Interatomic Machine-learning PotentiaL packagE – version Neural Network)☆48Updated 3 years ago