Scalable AI framework enables autonomous microkinetics discovery for materials research
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[Submitted on 27 Jun 2026]
Summary
This paper presents a scalable AI-driven framework for autonomous scientific discovery, using microkinetics discovery as a testbed. The framework combines agentic workflow automation, high-performance computing, and scientific surrogate models to reduce expert intervention, recover from failed simulations, and systematically evaluate surrogate model reliability. The study demonstrates how AI skills can transform complex domain workflows into robust, scalable capabilities for next-generation materials research.
Source
bskyScalable AI framework enables autonomous microkinetics discovery for materials researcharxiv.orgKey quotes
· 3 pulledWe present a scalable AI-driven framework that advances autonomous scientific discovery by combining agentic workflow automation, high-performance computing, and scientific surrogate models.
Using microkinetics discovery as a testbed, the work demonstrates how AI can reduce expert intervention, recover from failed simulations, and systematically evaluate surrogate model reliability.
This study shows how AI skills can transform complex domain workflows into robust, scalable capabilities for next-generation materials research.
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