abhijeetgangan / a2c_aseLinks
An ASE-friendly implementation of the amorphous-to-crystalline (a2c) workflow.
☆17Updated 3 months ago
Alternatives and similar repositories for a2c_ase
Users that are interested in a2c_ase are comparing it to the libraries listed below
Sorting:
- dataset augmentation for atomistic machine learning☆22Updated last month
- Vote on whether you think predicted crystal structures could be synthesised☆18Updated last year
- Reproduction of CGCNN for predicting material properties☆23Updated last week
- Alchemical machine learning interatomic potentials☆32Updated last year
- A collection of simulation recipes for the atomic-scale modeling of materials and molecules☆33Updated last week
- Adds Orb Model functionality to LAMMPS via Python wrapping☆15Updated 9 months ago
- Calculation of vibrational spectra with quantum nuclear motion☆12Updated last year
- ☆29Updated 6 months ago
- ☆33Updated last month
- Modulated automation of cluster expansion based on atomate2 and Jobflow☆12Updated this week
- Tools for machine learnt interatomic potentials☆42Updated last week
- Benchmarking foundation Machine Learning Potentials with Lattice Thermal Conductivity from Anharmonic Phonons☆16Updated last year
- A high-performance software package for training and evaluating machine-learned XC functionals using the CIDER framework☆18Updated last month
- JAX implementation of the NequIP neural network interatomic potential☆13Updated 5 months ago
- dftio is to assist machine learning communities to transcript DFT output into a format that is easy to read or used by machine learning m…☆13Updated last month
- ☆40Updated last month
- A collection of files related to machine learning force fields☆23Updated 2 years ago
- A molecular simulation package integrating MLFFs in MOFs for DAC☆41Updated 3 months ago
- Official repository for the paper "Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials".☆21Updated last year
- DiffSyn: A Generative Diffusion Approach to Materials Synthesis Planning (Nature Computational Science, under proof)☆16Updated 3 weeks ago
- WhereWulff: A semi-autonomous workflow for systematic catalyst surface reactivity under reaction conditions☆32Updated last year
- ☆11Updated last year
- ☆27Updated last year
- Train, fine-tune, and manipulate machine learning models for atomistic systems☆52Updated this week
- Cross-platform Optimizer for ML Interatomic Potentials☆23Updated 4 months ago
- ⚛ download and manipulate atomistic datasets☆48Updated last month
- Atomistic machine learning models you can use everywhere for everything☆33Updated this week
- `quansino` is a modular package based on the Atomic Simulation Environment (ASE) for quickly building custom Monte Carlo algorithms☆29Updated last week
- Tutorial files to work with ML for the charge density in molecules and solids☆12Updated 2 years ago
- A program to automatically generate volcano plots for catalysis.☆15Updated last year