News Release

Spin symmetry breaking unlocks new path to highly efficient hydrogen catalysts

Peer-Reviewed Publication

Dalian Institute of Chemical Physics, Chinese Academy Sciences

Figure Abstract

image: 

Spin density symmetry breaking in single-atom catalysts can significantly enhance the performance of hydrogen evolution reactions. Through interpretable machine learning and theoretical calculations, the research team quantified basic features into composite descriptors with well-defined structure-activity relationships, revealing a direct correlation between spin density symmetry breaking and catalytic activity, and offering new insights for the rational design of high-efficiency catalysts.

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Credit: Chinese Journal of Catalysis

A research team led by Prof. Zhonghua Li from Harbin Institute of Technology has discovered how spin density symmetry breaking in single-atom catalysts significantly improves hydrogen evolution reaction (HER) performance. Their findings, published in Chinese Journal of Catalysis (DOI: 10.1016/S1872-2067(25)64837-6), provide a new strategy for designing efficient, low-cost catalysts for clean hydrogen production.

The study combined density functional theory (DFT) calculations with interpretable machine learning (ML) to investigate HER activity in metal-nitrogen-carbon single-walled carbon nanotube (M-N3C-SWCNT) catalysts. Results showed a near-volcano relationship between spin density symmetry breaking and catalytic performance, with Mn-, Pd-, and Pt-based catalysts exhibiting the highest activity.

By introducing symmetry breaking into the catalyst structure, unpaired electrons accumulate near active sites, lowering reaction barriers and increasing turnover frequency by up to 40-fold compared to symmetric counterparts (M-N4-SWCNT). The ML model successfully extracted two governing factors—symmetry breaking effect and electron transfer effect—that jointly determine HER efficiency.

This work establishes a dual activation mechanism involving surface atom displacement and para-activation, offering a generalizable framework for catalyst design. The integrated DFT-ML-DFT approach accelerates the discovery of high-performance catalysts, supporting the transition toward sustainable hydrogen energy.

About the Journal

Chinese Journal of Catalysis is co-sponsored by Dalian Institute of Chemical Physics, Chinese Academy of Sciences and Chinese Chemical Society, and it is currently published by Elsevier group. This monthly journal publishes in English timely contributions of original and rigorously reviewed manuscripts covering all areas of catalysis. The journal publishes Reviews, Accounts, Communications, Articles, Highlights, Perspectives, and Viewpoints of highly scientific values that help understanding and defining of new concepts in both fundamental issues and practical applications of catalysis. Chinese Journal of Catalysis ranks among the top six journals in Applied Chemistry with a current SCI impact factor of 17.7. The Editors-in-Chief are Profs. Can Li and Tao Zhang.

At Elsevier: http://www.journals.elsevier.com/chinese-journal-of-catalysis 

Manuscript submission: https://mc03.manuscriptcentral.com/cjcatal


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