Putting Charge Transfer Degree as a Bridge Connecting Surface‐Enhanced Raman Spectroscopy and Photocatalysis

Abstract To date, few systematic approach has been established for predicting catalytic performance by analyzing the spectral information of molecules adsorbed on photocatalyst surfaces. Effective charge transfer (CT) between the semiconductor photocatalysts and surface‐absorbed molecules is essential for enhancing catalytic activity and optimizing light energy utilization. This study aimed to validate the surface‐enhanced Raman spectroscopy (SERS) based on the CT enhancement mechanism in investigating the CT process during semiconductor photocatalytic C−C coupling model reactions. A copper ion doping strategy was employed to simultaneously enhance the SERS effect and catalytic activity of zinc oxide (ZnO) derived from metal‐organic framework (MOF). By analyzing molecular fingerprint SERS spectra, we calculated the degree of CT (ρ CT ), revealing that SERS enhancement is attributed to the CT mechanism. In situ SERS spectra confirmed a high correlation between the catalytic activity and ρ CT of ZnO with varying copper ion doping levels. A range of photoelectric and spectroscopic tests validated the effectiveness of SERS in linking CT to photocatalytic performance, consistent with first‐principles density functional theory (DFT) simulations. This finding is also validated in other semiconductor materials and catalytic reactions, demonstrating the broad applicability of ρ CT for predicting and evaluating SERS and catalytic activity.

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Publication Details

Journal
Angewandte Chemie
Published
2025-01-29
DOI
https://doi.org/10.1002/ange.202424986
Primary Topic
Electrochemical Analysis and Applications
Type
article
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article

Putting Charge Transfer Degree as a Bridge Connecting Surface‐Enhanced Raman Spectroscopy and Photocatalysis

Bing Zhao, Wei Song, Wenji Jiang, Junjie Chen et al.
Angewandte Chemie
Electrochemical Analysis and Applications
article

Putting Charge Transfer Degree as a Bridge Connecting Surface‐Enhanced Raman Spectroscopy and Photocatalysis

Bing Zhao, Wei Song, Wenji Jiang, Junjie Chen, Mengyuan Li, Xinmeng Wang, Hongye Liu
article en

Abstract

Abstract To date, few systematic approach has been established for predicting catalytic performance by analyzing the spectral information of molecules adsorbed on photocatalyst surfaces. Effective charge transfer (CT) between the semiconductor photocatalysts and surface‐absorbed molecules is essential for enhancing catalytic activity and optimizing light energy utilization. This study aimed to validate the surface‐enhanced Raman spectroscopy (SERS) based on the CT enhancement mechanism in investigating the CT process during semiconductor photocatalytic C−C coupling model reactions. A copper ion doping strategy was employed to simultaneously enhance the SERS effect and catalytic activity of zinc oxide (ZnO) derived from metal‐organic framework (MOF). By analyzing molecular fingerprint SERS spectra, we calculated the degree of CT (ρ CT ), revealing that SERS enhancement is attributed to the CT mechanism. In situ SERS spectra confirmed a high correlation between the catalytic activity and ρ CT of ZnO with varying copper ion doping levels. A range of photoelectric and spectroscopic tests validated the effectiveness of SERS in linking CT to photocatalytic performance, consistent with first‐principles density functional theory (DFT) simulations. This finding is also validated in other semiconductor materials and catalytic reactions, demonstrating the broad applicability of ρ CT for predicting and evaluating SERS and catalytic activity.

Angewandte ChemieVol. 137(11)
Electric Power Research Institute (US), Jilin University (CN), Economic Research Institute (BG), State Key Laboratory of Supramolecular Structure and Materials
Openalex Percentile: Top 99%
Electrochemical Analysis and Applications
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Putting Charge Transfer Degree as a Bridge Connecting Surface‐Enhanced Raman Spectroscopy and Photocatalysis — Bing Zhao, Wei Song, et al. · Angewandte Chemie (2025) | TGRS Research Map | TGRS