CRYSTAL: a multi-agent AI system for automated mapping of materials’ crystal structures
| Autor: | Yexiang Xue, John M. Gregoire, R. Bruce van Dover, Shufeng Kong, Richard Bernstein, Santosh K. Suram, Brendan Rappazzo, Sebastian Ament, Junwen Bai, Carla P. Gomes, Johan Bjorck |
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| Rok vydání: | 2019 |
| Předmět: |
Theoretical computer science
Materials science Selection (relational algebra) Scientific discovery Data interpretation 02 engineering and technology Crystal structure 010402 general chemistry 021001 nanoscience & nanotechnology 01 natural sciences 0104 chemical sciences Crystal (programming language) Parallelism (grammar) General Materials Science Phase mapping 0210 nano-technology |
| Zdroj: | MRS Communications. 9:600-608 |
| ISSN: | 2159-6867 2159-6859 |
| DOI: | 10.1557/mrc.2019.50 |
| Popis: | We introduce CRYSTAL, a multi-agent AI system for crystal-structure phase mapping. CRYSTAL is the first system that can automatically generate a portfolio of physically meaningful phase diagrams for expert-user exploration and selection. CRYSTAL outperforms previous methods to solve the example Pd-Rh-Ta phase diagram, enabling the discovery of a mixed-intermetallic methanol oxidation electrocatalyst. The integration of multiple data-knowledge sources and learning and reasoning algorithms, combined with the exploitation of problem decompositions, relaxations, and parallelism, empowers AI to supersede human scientific data interpretation capabilities and enable otherwise inaccessible scientific discovery in materials science and beyond. |
| Databáze: | OpenAIRE |
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