Liquid-phase thermal decomposition-derived nanoparticles for electrocatalytic applications

Driven by the demand for rational nanoparticle (NP) design in electrocatalysis-based energy applications, various synthesis methods have been developed. Among these methods, liquid-phase thermal decomposition (LTD) is a unique and industry-friendly approach owing to its low cost and easy scalability, and most importantly, the size, shape, and stability of the nanoparticles (NPs) can be easily controlled with the simple adjustment of the reaction parameters. This review provides a comprehensive discussion and up-to-date perspectives on the importance of LTD-derived NPs (LTDNPs) in promoting electrocatalytic processes. First, we explore the fundamentals related to the LTD method, emphasizing how reaction parameters such as synthesis temperature, time, and atmosphere are critical to the properties of NPs. This evaluation analyzes how intrinsic and extrinsic electrocatalytic properties are influenced by the size, shape, and composition of the NPs. We also summarize and analyze rational catalyst designs through density functional theory and machine learning to illuminate the structure-to-performance relationship. In addition, the review elucidates the effectiveness of these NPs in electrocatalytic processes such as the oxygen reduction reaction (ORR), oxygen/hydrogen evolution reactions (OER/HER), nitrogen reduction reaction (NRR), and carbon dioxide reduction reaction (CO₂RR). Furthermore, we discuss insights concerning the stability and long-term performance of LTDNPs in relation to various degradation mechanisms. In terms of economic considerations, comparisons are also made with NPs generated by alternative methods. Finally, we outline numerous directions for advanced catalyst design by LTD using design of experiments (DOE) and theoretical modeling to scale up this process with device integration. This review serves as a comprehensive reference for investigators aiming to utilize the full potential of LTDNPs in electrocatalysis.