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Updated: Jul 12, 2025

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为数据效率高的机器学习重新制定反应性设计

Toby Lewis-Atwell1,2, Daniel Beechey2, Özgür Şimşek2

  • 1Department of Chemistry, University of Bath, Claverton Down, Bath BA2 7AY, U.K.

ACS catalysis
|October 26, 2023
PubMed
概括

本研究提出了一种数据效率高的机器学习 (ML) 方法来预测反应障碍,显著降低计算成本. 新方法快速识别具有特定激活障碍的反应,有助于催化剂设计和药物发现.

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