Computational materials discovery

MatIntel

Given millions of computationally stable crystal structures, which ones are actually viable for a specific application — and could anyone plausibly make them? MatIntel scores the GNoME dataset against 80 application categories, then weights each candidate by real-world viability and a GNN-predicted synthesizability estimate.

Structures screened
554,000+
Application categories
80
ALIGNN property models
20
Candidates shown here
800

What you're looking at

This is a read-only snapshot of the pipeline's output: the top ten candidates in each of the 80 categories, ranked by weighted score. The live pipeline runs offline against the full dataset — the numbers below are its published result, not a query being executed now.

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Known limitations

Every number here is a prediction, not a measurement. Scores encode materials-science heuristics and GNN outputs, so a high rank means "worth a closer look," not "this works." The July 2026 audit documents the data defects found along the way, including a score-saturation bug that had collapsed eight categories into unranked ties, and the ALIGNN property columns that came back entirely null because the run had nothing to import. Both are written up rather than quietly fixed, because the failures are more instructive than the rankings.