google-deepmind/materials_discovery resource

Health v2 · maintenance only

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Adoption not part of the score

1230 stars · 195 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Google DeepMind's GNoME repository sharing a dataset of over 520,000 predicted stable inorganic crystal structures plus model definitions (GNoME and Nequip) and Colab notebooks. It supports machine learning-driven discovery of novel materials in materials science research.

Use cases

• find novel stable inorganic crystal structures for battery research
• train graph neural networks on materials project data
• explore convex hull data for a chemical family
• reproduce GNoME materials discovery paper results
• load DFT formation energy data as CSV
• visualize crystal structures in a colab notebook

When to choose

• you need a large dataset of predicted stable inorganic crystals
• you want to reproduce or extend GNoME machine learning models for materials discovery
• you research materials science with graph networks and DFT data

When to avoid

• you need production-supported software rather than a research codebase
• you need general-purpose chemistry simulation tools rather than crystal discovery datasets
• you expect polished APIs and official product support

Facets

dataset · maturity active

machine-learning data-science chemistry machine-learning python gnome materials-discovery crystal-structures dft convex-hull graph-networks research-dataset materials-science

Member repositories

For agents

markdown · JSON · MCP: product_card(name="google-deepmind/materials_discovery")