Department of Chemistry, Seoul National University, Seoul, South Korea.
Chem Soc Rev. 2020 Dec 21;49(24):9154-9196. doi: 10.1039/d0cs00575d. Epub 2020 Nov 3.
Recent years have witnessed an upsurge in the development of non-precious catalysts (NPCs) for alkaline water electrolysis (AWE), especially with the strides made in experimental and computational techniques. In this contribution, the most recent advances in NPCs for AWE were systematically reviewed, emphasizing the application of in situ/operando experimental methods and density functional theory (DFT) calculations in their understanding and development. First, we briefly introduced the fundamentals of the anode and cathode reaction for AWE, i.e., the oxygen evolution reaction (OER) and the hydrogen evolution reaction (HER), respectively. Next, the most popular in situ/operando approaches for characterizing AWE catalysts, including hard and soft XAS, ambient-pressure XPS, liquid and identical location TEM, electrochemical mass spectrometry, and Raman spectroscopy were thoroughly summarized. Subsequently, we carefully discussed the principles, computational methods, applications, and combinations of DFT with machine learning for modeling NPCs and predicting the alkaline OER and HER. With the improved understanding of the structure-property-performance relationship of NPCs for AWE, we proceeded to overview their current development, summarising state-of-the-art design strategies to boost their activity. In addition, advances in various extensively investigated NPCs for AWE were evaluated. By conveying these methods, progress, insights, and perspectives, this review will contribute to a better understanding and rational development of non-precious AWE electrocatalysts for hydrogen production.
近年来，碱性水电解（AWE）中非贵金属催化剂（NPC）的发展呈现出蓬勃发展的态势，尤其是在实验和计算技术方面取得了长足的进步。在这篇综述中，系统地回顾了 NPC 在 AWE 中的最新进展，强调了原位/操作实验方法和密度泛函理论（DFT）计算在其理解和开发中的应用。首先，我们简要介绍了 AWE 中阳极和阴极反应的基本原理，分别为析氧反应（OER）和析氢反应（HER）。接下来，我们详细总结了用于表征 AWE 催化剂的最流行的原位/操作方法，包括硬 X 射线吸收光谱（XAS）、常压 X 射线光电子能谱（XPS）、液相和同位置透射电子显微镜（TEM）、电化学质谱和拉曼光谱。随后，我们仔细讨论了 DFT 与机器学习相结合用于建模 NPC 并预测碱性 OER 和 HER 的原理、计算方法、应用和组合。通过提高对 AWE NPC 的结构-性能-关系的理解，我们开始综述其当前的发展，总结了提高其活性的最先进的设计策略。此外，还评估了各种广泛研究的 NPC 在 AWE 中的进展。通过传达这些方法、进展、见解和观点，本综述将有助于更好地理解和合理开发用于产氢的非贵金属 AWE 电催化剂。
