#计算机科学#Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
#计算机科学#A deep learning package for many-body potential energy representation and molecular dynamics
Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Pro...
Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards a wide range of property cons...
#计算机科学#NequIP is a code for building E(3)-equivariant interatomic potentials
FiPy is a Finite Volume PDE solver written in Python
#计算机科学#Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals
Density-functional toolkit
#Awesome#Curated list of known efforts in materials informatics, i.e. in modern materials science
#计算机科学#DScribe is a python package for creating machine learning descriptors for atomistic systems.
#计算机科学#Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.
#计算机科学#MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
#计算机科学#Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials
#学习与技能提升#Graph deep learning library for materials
A list of databases, datasets and books/handbooks where you can find materials properties for machine learning applications.
Cross platform, open source application for the processing, visualization, and analysis of 3D tomography data
CALPHAD tools for designing thermodynamic models, calculating phase diagrams and investigating phase equilibria.
#计算机科学#Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.