Yangxinsix / painn-sli
This is the source code for paper "Neural Network Potentials for Accelerated Metadynamics of Oxygen Reduction Kinetics at Au-Water Interfaces"
☆21Updated 9 months ago
Alternatives and similar repositories for painn-sli:
Users that are interested in painn-sli are comparing it to the libraries listed below
- A flexible workflow for on-the-fly learning of interatomic potential models.☆26Updated 10 months ago
- Machine-Learning-Based Interatomic Potentials for Catalysis: an Universal Catalytic Large Atomic Model☆31Updated 2 months ago
- Calculate Spectrum Based on Fast Fourier Transform (FFT) of the Velocity Autocorrelation Function (VACF).☆25Updated last year
- Metadynamics code on the G-space.☆14Updated 3 years ago
- Advanced ASE Transition State Tools for ABACUS and Deep-Potential☆26Updated last week
- Global Optimizer for Clusters, Interfaces, and Adsorbates☆23Updated last week
- ☆24Updated 11 months ago
- SIMPLE-NN(SNU Interatomic Machine-learning PotentiaL packagE – version Neural Network)☆47Updated 3 years ago
- ☆66Updated last year
- GRACE models and gracemaker (as implemented in TensorPotential package)☆50Updated last week
- A lightweight python package for reading and writing VASP ML_AB files☆35Updated 3 weeks ago
- A molecular simulation package integrating MLFFs in MOFs for DAC☆24Updated last week
- A... M... L...☆48Updated 3 years ago
- ASE interface for fully constant potential with VASP☆31Updated 5 months ago
- LASP python library including scripts and auto-NNtrain workflow☆19Updated last year
- Some tutorial-style examples for validating machine-learned interatomic potentials☆32Updated last year
- Quick Uncertainty and Entropy via STructural Similarity☆33Updated last week
- Wyckoff Inorganic Crystal Generator Framework☆21Updated 2 weeks ago
- Code for automated fitting of machine learned interatomic potentials.☆71Updated this week
- Clean, Uniform and Refined with Automatic Tracking from Experimental Database (CURATED) COFs☆34Updated last year
- Deep Modeling for Molecular Simulation 2023, four-day in-person workshop, July 11-14, 2023☆19Updated last year
- Active Learning for Machine Learning Potentials☆51Updated 10 months ago
- MD2D: a python module for accurate determination of diffusion coefficient from molecular dynamics☆21Updated 2 years ago
- ☆10Updated this week
- ☆36Updated 5 months ago
- updated constant potential plugin for LAMMPS☆39Updated 2 years ago
- ☆61Updated this week
- Molecular dynamics package designed for the SIESTA DFT code.☆14Updated last month