emmet

Material database framework

A framework for building and managing material properties databases

Be a master builder of databases of material properties. Avoid the Kragle.

GitHub

55 stars
13 watching
69 forks
Language: Python
last commit: 1 day ago
Linked from 1 awesome list


Backlinks from these awesome lists:

Related projects:

Repository Description Stars
materialsvirtuallab/maml A toolkit for machine learning in materials science, enabling the development of predictive models and simulations. 376
materialsproject/matbench Provides tools and resources for testing machine learning performance on materials science data 132
nt1m/material-framework A CSS-only framework for building Material Design-based web applications 387
ppdebreuck/modnet A Python package implementing a machine learning framework for predicting material properties from composition or crystal structure data. 82
adopted-ember-addons/ember-paper Brings Google's Material Design to Ember as an extension of the Ember framework 888
anthony-wang/crabnet A deep learning framework for predicting material properties from composition information. 94
exabyte-io/esse Provides data format definitions and examples for digital materials science 6
blaiszik/materials-databases A curated collection of databases providing access to materials-related data and properties through APIs. 80
materialsproject/atomate2 Automates complex materials science workflows using simple Python functions 169
avaloniacommunity/material.avalonia A collection of styles and controls for customizing Avalonia applications with Material Design theme 853
mikolajdobrucki/material-foundation A Material Design framework for building responsive web applications 352
materialsproject/custodian A job management framework for handling errors and failures in long-running computations 143
materialsintelligence/mat2vec Unsupervised word embeddings capture latent knowledge from materials science literature 624
hackingmaterials/matminer A toolkit for extracting insights from materials science data using machine learning and data mining techniques. 488
comprhys/aviary A framework for building and deploying machine learning models for materials discovery 48