Monitoring C–C coupling in catalytic reactions via machine-learned infrared spectroscopy

Tracking atomic structural evolution along chemical transformation pathways is essential for optimizing chemical transitions and enhancing control. However, molecule-level knowledge of structural rearrangements during chemical processes remains a great challenge. Here, we couple infrared spectroscopy as a non-invasive method to probe molecular transformations, with a machine-learned protocol to immediately map the spectroscopic fingerprints to atomistic structures. From the theoretical perspective, we demonstrate it here with the example of C-C coupling in catalytic reactions, elucidating various structural conformations along dynamic trajectories. Within the transferable application to the specific CO-CO dimerization reaction, the structural and energetic variations of the critical chemical species could be identified via infrared spectroscopy. This approach extends the power of spectroscopy from fingerprinting chemical configurations to using them for assigning dynamic structural information.

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Publication Details

Journal
National Science Review
Published
2024-11-04
DOI
https://doi.org/10.1093/nsr/nwae389
Citations
7
Primary Topic
Innovative Microfluidic and Catalytic Techniques Innovation
Type
article
Field-Weighted Citation Impact
1.29

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article

Monitoring C–C coupling in catalytic reactions via machine-learned infrared spectroscopy

Thomas Heine, Changyin Sun, Donglai Zhou, Sheng Ye et al.
7 citations
National Science Review
Innovative Microfluidic and Catalytic Techniques Innovation
1.29
article

Monitoring C–C coupling in catalytic reactions via machine-learned infrared spectroscopy

Thomas Heine, Changyin Sun, Donglai Zhou, Sheng Ye, Tongtong Yang, Xiaoyu Yue, Li Yang, Yan Hong Huang, Ruiting Zheng, Jun Jiang, Xijun Wang, Xiyu Li, Zhicheng Zhao
article en
7 citations

Abstract

Tracking atomic structural evolution along chemical transformation pathways is essential for optimizing chemical transitions and enhancing control. However, molecule-level knowledge of structural rearrangements during chemical processes remains a great challenge. Here, we couple infrared spectroscopy as a non-invasive method to probe molecular transformations, with a machine-learned protocol to immediately map the spectroscopic fingerprints to atomistic structures. From the theoretical perspective, we demonstrate it here with the example of C-C coupling in catalytic reactions, elucidating various structural conformations along dynamic trajectories. Within the transferable application to the specific CO-CO dimerization reaction, the structural and energetic variations of the critical chemical species could be identified via infrared spectroscopy. This approach extends the power of spectroscopy from fingerprinting chemical configurations to using them for assigning dynamic structural information.

National Science ReviewVol. 12(2)
University of Science and Technology of China (CN), Anhui University (CN), Helmholtz-Zentrum Dresden-Rossendorf (DE), Technische Universität Dresden (DE)
European Commission, National Natural Science Foundation of China, Anhui University, University of Science and Technology of China, Anhui Provincial Department of Education, Natural Science Foundation of Anhui Province
Life in Land
Openalex Percentile: Top 21%
Innovative Microfluidic and Catalytic Techniques Innovation
1.29
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