Machine Learning Accelerated First-Principles Study of the Hydrodeoxygenation of Propanoic Acid

Yang, Wenqiang; Abdelfatah, Kareem E.; Kundu, Subrata Kumar; Rajbanshi, Biplab; Terejanu, Gabriel A.; Heyden, Andreas

doi:10.1021/acscatal.4c01419

ACS Catal.

2024

DOI: 10.1021/acscatal.4c01419

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Machine Learning Accelerated First-Principles Study of the Hydrodeoxygenation of Propanoic Acid

Wenqiang Yang,

Kareem E. Abdelfatah,

Subrata Kumar Kundu

et al.

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Cited by 2 publications

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Highly-efficient NiCo alloy catalysts towards hydrodeoxygenation of fatty acids to prepare alkanes

Qian,

Wang,

et al. 2025

Molecular Catalysis

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Highly-efficient NiCo alloy catalysts towards hydrodeoxygenation of fatty acids to prepare alkanes

Qian,

Wang,

et al. 2025

Molecular Catalysis

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Two-Electron or Four-Electron Nanocatalysis for Aerobic Glucose Oxidation: A Mechanism-Driven Prediction Model

Wang,

Li,

Zheng

et al. 2024

ACS Catal.

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The nanomaterial-catalyzed oxidation of glucose can produce H2O2 or H2O as the oxygen reduction products. However, the theoretical model predicting the selection between H2O2 and H2O products is still lacking, which limits the rational design of aerobic glucose oxidation nanocatalysts for H2O2-targeted applications in disease diagnoses and therapies. In this work, a mechanism-driven prediction model that can predict whether a nanocatalyst preferably undergoes the 2e-catalysis to produce H2O2 or the 4e-catalysis to produce H2O is developed. The development of the model is first based on the reaction thermodynamics, and then a correction constant is introduced in conjunction with experimental reports to compensate to some extent for the lack of consideration of other influencing factors such as the reaction kinetics. The predictive power of the model is verified by density functional theory investigations on the mechanisms and kinetics of the experimentally reported noble metal nanocatalysts. Using the model, binary alloy nanomaterials, which preferably undergo 2e-catalysis to produce H2O2, have been predicted. This work provides theoretical guidelines for the rational design of aerobic glucose oxidation nanocatalysts capable of producing H2O2 and facilitates their application in H2O2-targeted biomedicine.

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Machine Learning Accelerated First-Principles Study of the Hydrodeoxygenation of Propanoic Acid

Cited by 2 publications

References 84 publications

Highly-efficient NiCo alloy catalysts towards hydrodeoxygenation of fatty acids to prepare alkanes

Highly-efficient NiCo alloy catalysts towards hydrodeoxygenation of fatty acids to prepare alkanes

Two-Electron or Four-Electron Nanocatalysis for Aerobic Glucose Oxidation: A Mechanism-Driven Prediction Model

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