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repos: 33.0 gists: 0.0

Name: Materials Virtual Lab

Type: Organization

Bio: The Materials Virtual Lab is dedicated to the application of first principles calculations and informatics to accelerate materials design.

Location: La Jolla, CA

Blog: www.materialsvirtuallab.org

Materials Virtual Lab's Projects

api icon api

New API client for the Materials Project

ceng114 icon ceng114

Repository for CENG114 Probability and Statistics for Engineers

enumlib icon enumlib

Derivative structure enumeration library

garnetdnn icon garnetdnn

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

m3gnet icon m3gnet

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

maml icon maml

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

matcalc icon matcalc

A python library for calculating materials properties from the PES

matgenb icon matgenb

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

matgl icon matgl

Graph deep learning library for materials

megnet icon megnet

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

mlearn icon mlearn

Benchmark Suite for Machine Learning Interatomic Potentials for Materials

monty icon 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.

nano106 icon nano106

Course materials for NANO 106 - Crystallography of Materials

nano266 icon nano266

Repository for UCSD NANO 266 Quantum Mechanical Modelling of Materials

pyhull icon pyhull

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

snap icon snap

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

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