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98 public repositories
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Python Materials Genomics (pymatgen) is a robust materials analysis code that defines core object representations for structures and molecules with support for many electronic structure codes. It is currently the core analysis code powering the Materials Project.
Updated
Mar 23, 2022
HTML
Deep learning for molecules and materials book
Updated
Mar 23, 2022
Jupyter Notebook
Curated list of known efforts in materials informatics
JARVIS-Tools: an open-source software package for data-driven atomistic materials design
Updated
Mar 12, 2022
Python
Fork this repo for a quick start. If "Project Timeline" or "License" appeared on your nav bar, Look Below!
Updated
Oct 1, 2020
JavaScript
ChemML is a machine learning and informatics program suite for the chemical and materials sciences.
Updated
Feb 21, 2022
Python
Data Analysis program and framework for materials science data analytics, based on the managing framework SIMPL framework.
Open-source library for analyzing the results produced by ABINIT
Updated
Feb 28, 2022
Python
A machine learning environment for atomic-scale modeling in surface science and catalysis.
Updated
Jul 7, 2020
Python
A list of databases, datasets and books/handbooks where you can find materials properties for machine learning applications.
Catalyst Micro-kinetic Analysis Package for automated creation of micro-kinetic models used in catalyst screening
Updated
Jul 23, 2021
Python
General purpose tools for high-throughput catalysis
Updated
Jan 31, 2022
Python
A Highly Opinionated List of Open Source Materials Informatics Resources
Predict materials properties using only the composition information!
Updated
Mar 6, 2022
Python
Python package to aid materials design
Updated
Nov 4, 2021
Python
Autonomous characterization of molecular compounds from small datasets without descriptors
Updated
Apr 1, 2020
Jupyter Notebook
Pytorch implementation of the paper "Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules"
Updated
Mar 31, 2021
Jupyter Notebook
Positive and Unlabeled Materials Machine Learning (pumml) is a code that uses semi-supervised machine learning to classify materials from only positive and unlabeled examples.
Updated
Nov 20, 2020
Python
Materials informatics framework for ab initio data repositories
Updated
Feb 4, 2022
Python
Python Topological Materials (pytopomat) is a code for easy, high-throughput analysis of topological materials.
Updated
May 17, 2021
Python
A toolkit for visualizations in materials informatics.
Updated
Mar 21, 2022
Python
A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.
Updated
Mar 19, 2022
Python
Everything on the MPDS API: the data retrieval interface for the Materials Platform for Data Science
Updated
Sep 28, 2021
HTML
Tools, utility, parsers useful in daily material science work
Updated
Mar 23, 2022
Python
Collection of papers on text mining for materials science
Package to automatically analyze Lobster runs
Updated
Mar 23, 2022
Python
A standalone React.js/Redux based web application for the design and visualization of atomistic materials structures. Used within the Exabyte.io platform and can be deployed in standalone mode.
Updated
Mar 23, 2022
JavaScript
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add a section on hyperparameter tuning since classical models were used with default hyperparameters