Time-resolved in situ vibrational spectroscopy for electrocatalysis: challenge and opportunity

Understanding the structure-activity relationship of catalysts and the reaction pathway is crucial for designing efficient, selective, and stable electrocatalytic systems. In situ vibrational spectroscopy provides a unique tool for decoding molecular-level factors involved in electrocatalytic reactions. Typically, spectra are recorded when the system reaches steady states under set potentials, known as steady-state measurements, providing static pictures of electrode properties at specific potentials. However, transient information that is crucial for understanding the dynamic of electrocatalytic reactions remains elusive. Thus, time-resolved in situ vibrational spectroscopies are developed. This mini review summarizes time-resolved in situ infrared and Raman techniques and discusses their application in electrocatalytic research. With different time resolutions, these time-resolved techniques can capture unique dynamic processes of electrocatalytic reactions, short-lived intermediates, and the surface structure revolution that would be missed in steady-state measurements alone. Therefore, they are essential for understanding complex reaction mechanisms and can help unravel important molecular-level information hidden in steady states. Additionally, improving spectral time resolution, exploring low/ultralow frequency detection, and developing operando time-resolved devices are proposed as areas for advancing time-resolved techniques and their further applications in electrocatalytic research.

Automated summary

Understanding the structure-activity relationship of catalysts and the dynamic of electrocatalytic reactions is essential for designing efficient systems. In situ vibrational spectroscopy provides a unique tool for decoding molecular-level factors involved in electrocatalysis. This review summarizes time-resolved in situ infrared and Raman techniques and their applications in electrocatalytic research, highlighting the importance of capturing dynamic processes and transient information.