Alternatives and similar repositories for QMOF:

Users that are interested in QMOF are comparing it to the libraries listed below

• BingqingCheng / ASAP
  ASAP is a package that can quickly analyze and visualize datasets of crystal or molecular structures.
  ☆145Updated 8 months ago
• ACEsuit / mace-mp
  MACE-MP models
  ☆81Updated this week
• ICAMS / calphy
  A Python library and command line interface for automated free energy calculations
  ☆76Updated 3 months ago
• Sangwon91 / PORMAKE
  Python library for the construction of porous materials using topology and building blocks.
  ☆63Updated 3 months ago
• Eipgen / Neural-Network-Models-for-Chemistry
  A collection of Nerual Network Models for chemistry
  ☆117Updated last week
• zadorlab / sella
  A Python software package for saddle point optimization and minimization of atomic systems.
  ☆91Updated 5 months ago
• MaterSim / PyXtal_FF
  Machine Learning Interatomic Potential Predictions
  ☆89Updated last year
• BingqingCheng / cace
  ☆61Updated last week
• atomisticnet / tools-and-data
  A collection of tools and databases for atomistic machine learning
  ☆48Updated 3 years ago
• hjkgrp / molSimplify
  molSimplify code
  ☆183Updated this week
• hsulab / GDPy
  Generating Deep Potential with Python
  ☆65Updated this week
• snurr-group / mofid
  A system for rapid identification and analysis of metal-organic frameworks
  ☆51Updated 3 months ago
• by256 / icsg3d
  3-D Inorganic Crystal Structure Generation and Property Prediction via Representation Learning (JCIM 2020)
  ☆41Updated 2 years ago
• tobacco-mofs / tobacco_3.0
  ☆53Updated 3 years ago
• orlandoacevedo / IL
  Ionic liquid force field parameters (OPLS-2009IL and OPLS-VSIL)
  ☆58Updated 7 months ago
• hackingmaterials / robocrystallographer
  Automatic generation of crystal structure descriptions.
  ☆112Updated 2 months ago
• SUNCAT-Center / CatKit
  General purpose tools for high-throughput catalysis
  ☆91Updated 8 months ago
• PV-Lab / FTCP
  FTCP code
  ☆33Updated last year
• bytedance / bamboo
  BAMBOO (Bytedance AI Molecular BOOster) is an AI-driven machine learning force field designed for precise and efficient electrolyte simu…
  ☆52Updated 2 months ago
• mir-group / pair_allegro
  LAMMPS pair style for Allegro deep learning interatomic potentials with parallelization support
  ☆41Updated 5 months ago
• CompRhys / roost
  Representation Learning from Stoichiometry
  ☆58Updated 2 years ago
• MaginnGroup / PyLAT
  ☆108Updated 2 years ago
• jhrmnn / pyberny
  Molecular structure optimizer
  ☆115Updated 2 years ago
• txie-93 / gdynet
  Unsupervised learning of atomic scale dynamics from molecular dynamics.
  ☆81Updated 3 years ago
• hernanchavezthielemann / GRO2LAM
  Gromacs to Lammps simulation converter
  ☆74Updated last year
• peterbjorgensen / DeepDFT
  Official implementation of DeepDFT model
  ☆71Updated 2 years ago
• ulissigroup / finetuna
  Active Learning for Machine Learning Potentials
  ☆52Updated 10 months ago
• OUnke / SpookyNet
  Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"
  ☆71Updated 2 years ago
• materialsproject / matbench
  Matbench: Benchmarks for materials science property prediction
  ☆147Updated 7 months ago
• ulissigroup / GASpy
  ☆67Updated 4 years ago