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<p>Large language models are shifting catalysis from prediction-first pipelines to workflow-level coordination of hypotheses, computation, and experiments. In this Perspective, we argue that autonomous catalysis requires closing both representation and workflow gaps through a verification-first paradigm, in which large language model agents orchestrate heterogeneous tools, ground claims in auditable evidence, and use uncertainty-aware validation. We further propose system-level metrics to benchmark reliable autonomous catalysis.</p>

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Verification-first autonomous catalysis: large language models as infrastructure for mechanism, computation, and experiment

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月29日

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  • Yan Liu,
  • Pengfei Ou

摘要

Large language models are shifting catalysis from prediction-first pipelines to workflow-level coordination of hypotheses, computation, and experiments. In this Perspective, we argue that autonomous catalysis requires closing both representation and workflow gaps through a verification-first paradigm, in which large language model agents orchestrate heterogeneous tools, ground claims in auditable evidence, and use uncertainty-aware validation. We further propose system-level metrics to benchmark reliable autonomous catalysis.