BingqingCheng / ASAP
ASAP is a package that can quickly analyze and visualize datasets of crystal or molecular structures.
☆145Updated 9 months ago
Alternatives and similar repositories for ASAP:
Users that are interested in ASAP are comparing it to the libraries listed below
- Machine Learning Interatomic Potential Predictions☆90Updated last year
- ☆108Updated 2 years ago
- A Python library and command line interface for automated free energy calculations☆75Updated this week
- MACE foundation models (MP, OMAT, Matpes)☆97Updated 3 weeks ago
- A collection of Nerual Network Models for chemistry☆121Updated 3 weeks ago
- Generating Deep Potential with Python☆66Updated this week
- Tool to build force field input files for molecular simulation☆168Updated 2 months ago
- A Python software package for saddle point optimization and minimization of atomic systems.☆96Updated 6 months ago
- Software for generating machine-learning interatomic potentials for LAMMPS☆163Updated last week
- The QMOF Database: A database of quantum-mechanical properties for metal-organic frameworks.☆143Updated 2 months ago
- i-PI: a universal force engine☆256Updated last week
- molSimplify code☆186Updated last week
- Gromacs to Lammps simulation converter☆78Updated last year
- Benchmark Suite for Machine Learning Interatomic Potentials for Materials☆106Updated 3 years ago
- Ionic liquid force field parameters (OPLS-2009IL and OPLS-VSIL)☆61Updated 8 months ago
- Python Cp2k interface☆94Updated 2 years ago
- ☆57Updated 4 months ago
- General purpose tools for high-throughput catalysis☆92Updated 9 months ago
- cp2k postprocessing tools☆66Updated 2 months ago
- AI-enhanced computational chemistry☆79Updated 3 weeks ago
- A unified framework for machine learning collective variables for enhanced sampling simulations☆104Updated last week
- ☆67Updated 4 years ago
- UF3: a python library for generating ultra-fast interatomic potentials☆65Updated 6 months ago
- A scalable and versatile library to generate representations for atomic-scale learning☆80Updated last year
- The course materials for "Machine Learning in Chemistry 101"☆76Updated 4 years ago
- A Python package for estimating diffusion properties from molecular dynamics simulations.☆65Updated 3 weeks ago
- A collection of tools and databases for atomistic machine learning☆48Updated 3 years ago
- BAMBOO (Bytedance AI Molecular BOOster) is an AI-driven machine learning force field designed for precise and efficient electrolyte simu…☆75Updated 3 months ago
- Atomic interaction potentials based on artificial neural networks☆118Updated 2 weeks ago
- ☆71Updated 2 weeks ago