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Published on: July 22, 2025
Rapid estimation of activation energy in heterogeneous catalytic reactions via machine learning
Keisuke Takahashi1,2, Itsuki Miyazato1,3
1Center for Materials research by Information Integration (CMI2), National Institute for Materials Science (NIMS), 1-2-1 Sengen, Tsukuba, Ibaraki, 305-0047, Japan.
Abstract:
Estimation of activation energies within heterogeneous catalytic reactions is performed using machine learning and catalysts dataset. In particular, descriptors for determining activation energy are revealed within the 788 activation energy dataset. With the implementation of machine learning and chosen descriptors, activation energy can be instantly predicted with over 90% accuracy during cross-validation. Thus, rapid estimation of activation energies within heterogeneous catalytic reactions can be made achievable via machine learning, leading toward the acceleration of catalysts design and characterization. © 2018 Wiley Periodicals, Inc.
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