Computational high-throughput screening of electrocatalytic materials for hydrogen evolution.

Area of Science:

• Materials Science
• Computational Chemistry
• Electrochemistry

Background:

• Accelerating materials discovery for catalysts is crucial for energy applications.
• Computational screening methods require integration with experimental validation.

Purpose of the Study:

• To develop and apply a high-throughput computational screening scheme for identifying new electrocatalysts.
• To discover novel materials for the hydrogen evolution reaction (HER).

Main Methods:

• Density functional theory (DFT)-based high-throughput screening.
• Evaluation of catalytic activity and stability for over 700 binary surface alloys.
• Experimental synthesis and testing of promising candidate materials.

Main Results:

• Bismuth-platinum (BiPt) was computationally identified as a highly active HER electrocatalyst.
• Predicted activity of BiPt is comparable to or exceeds that of pure platinum.
• Synthesized BiPt demonstrated improved HER performance over pure platinum, validating computational predictions.

Conclusions:

• Integrated computational and experimental approaches can effectively accelerate catalyst discovery.
• BiPt is a promising, high-performance electrocatalyst for the hydrogen evolution reaction.
• DFT-based screening is a viable strategy for identifying advanced catalytic materials.