materialsvirtuallab/flamyngo

Stars
15
Rank 1,371,379 (Top 28 %)
Language
Python
License
BSD 3-Clause "New...
Created almost 9 years ago
Updated 4 months ago

materialsvirtuallab/flamyngo

materialsvirtuallab

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Flask frontend for MongoDB

megnet

Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals

Jupyter Notebook

maml

Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.

Jupyter Notebook

matgl

Graph deep learning library for materials

m3gnet

Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.

matgenb

Jupyter notebooks demonstrating the utilization of open-source codes for the study of materials science.

Jupyter Notebook

mlearn

Benchmark Suite for Machine Learning Interatomic Potentials for Materials

pyhull

Pyhull is a Python wrapper to Qhull (http://www.qhull.org/) for the computation of the convex hull, Delaunay triangulation and Voronoi diagram.

pymatgen-analysis-diffusion

This add-on to pymatgen provides tools for analyzing diffusion in materials.

monty

This repository implements supplementary useful functions for Python that are not part of the standard library. Examples include useful utilities like transparent support for zipped files etc.

matcalc

A python library for calculating materials properties from the PES

nano281

Data Science for Materials Science

Jupyter Notebook

snap

Repository for spectral neighbor analysis potential (SNAP) model development.

garnetdnn

This repo implements a web application utilizing a deep neural network to predict the formation energies and stability of garnet crystals.

nano106

Course materials for NANO 106 - Crystallography of Materials

Jupyter Notebook

nano266

Repository for UCSD NANO 266 Quantum Mechanical Modelling of Materials

veidt

Veidt is a deep learning library for materials science.

materials.sh

Data-driven-First-Principles-Methods-for-the-Study-and-Design-of-Alkali-Superionic-Conductors

Jupyter notebooks and data for our Chemistry of Materials article "Data-driven First Principles Methods for the Study and Design of Alkali Superionic Conductors"

Jupyter Notebook

matgenie

Web interface to pymatgen

materialsvirtuallab.github.io

A guide to the Materials Virtual Lab

ceng114

Repository for CENG114 Probability and Statistics for Engineers

Jupyter Notebook

thematerialsapp

An Android Application for the Materials Project