Mechanism Identification and High-Throughput Screening of Molecules for the Hydrogen Evolution Reaction

Objective

The electrocatalytic hydrogen evolution reaction (HER) plays an important role in sustainable hydrogen energy conversion. Organic molecules, as potential alternatives to expensive Pt-based metals, can significantly reduce the cost of catalysts. However, the HER mechanism of organic molecules in aqueous solutions is poorly understood. The unclear structure-mechanism relationship hinders the discovery of efficient molecular catalysts. This project systematically investigates the HER mechanism of organic molecules under both acidic and alkaline conditions through Density Functional Theory (DFT) calculations and microkinetic models. Subsequently, structural descriptors are developed to capture the structure-activity relationships of organic molecules. High-throughput screening based on these descriptors is employed to identify promising HER catalysts from millions of molecules through machine learning approaches. These active candidates are further validated through theoretical calculations and experimental measurements. By combining mechanism analysis, descriptor construction, high-throughput screening, and validation, the workflow not only identifies new molecular catalysts for HER, but also provides a valuable framework for screening and discovering other materials.