Precursor Recommendation by ML Materials Similarity from Scientific Literature

Learns precursor recommendations from 29,900 text-mined solid-state synthesis recipes.

Use for: AI Synthesis Planning, Autonomous Labs, and Synthesis Data. Method focus: solid-state; AI synthesis planning. Material family: general materials. Validation: Match validation to target: phase purity, composition, microstructure, and property measurement.. Safety note: Check SDS, institutional SOPs, equipment limits, and waste rules before use.

Citation: Precursor Recommendation by ML Materials Similarity from Scientific Literature. Materials synthesis resource. https://arxiv.org/abs/2302.02303

Acknowledgement: Curated by MaterialsAtlas Open Resources from open courses, protocols, official documentation, scholarly papers, datasets, safety references, and synthesis-planning resources.