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

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.