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CRYSTAL: a Multi-Agent AI System for Automated Mapping of Materials’ Crystal Structures

MRS Communications(2019)SCI 4区

Cornell University

Cited 31|Views112
Abstract
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.
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要点】:本研究提出了一种利用线性回归算法结合特征提取方法,实现了对缺失流量历史数据的重构,提高了数据完整性和 reservoir 管理的准确性。

方法】:通过线性回归算法,结合特征提取技术,对流量历史数据进行重建。

实验】:研究使用了来自实际生产油田的压力和流量数据集,实验结果表明线性回归在估计缺失流量历史数据方面表现出了高性能,但在流量和压力数据变化较大时效果不佳。