单原子催化剂中自旋密度对称性破缺介导的析氢反应

doi:10.1016/S1872-2067(25)64837-6

催化学报 ›› 2026, Vol. 80: 213-226.DOI: 10.1016/S1872-2067(25)64837-6

单原子催化剂中自旋密度对称性破缺介导的析氢反应

宋鑫^a, 李中华^a^,^*(), 盛利^a^,^*(), 刘扬^b^,^*()

^a哈尔滨工业大学化工与化学学院, 微系统与微结构制造教育部重点实验室, 黑龙江哈尔滨 150001
^b哈尔滨工业大学计算机学院, 黑龙江哈尔滨 150001

收稿日期:2025-06-20 接受日期:2025-08-08 出版日期:2026-01-18 发布日期:2026-01-05
通讯作者: 李中华,盛利,刘扬
基金资助:
国家自然科学基金(51272052);国家自然科学基金(50902040);国家自然科学基金(62071154);黑龙江省自然科学基金(LH2020B011);黑龙江省自然科学基金(LH2019B006);黑龙江省高校基本科研业务费专项资金(2021-KYYWF-0171)

Spin density symmetry breaking-mediated hydrogen evolution in single-atom catalysts

Xin Song^a, Zhonghua Li^a^,^*(), Li Sheng^a^,^*(), Yang Liu^b^,^*()

^aSchool of Chemistry and Chemical Engineering, Key Laboratory of Microsystems and Microstructures Manufacturing, Ministry of Education, Harbin Institute of Technology, Harbin 150001, Heilongjiang, China
^bSchool of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, Heilongjiang, China

Received:2025-06-20 Accepted:2025-08-08 Online:2026-01-18 Published:2026-01-05
Contact: Zhonghua Li, Li Sheng, Yang Liu
Supported by:
National Natural Science Foundation of China(51272052);National Natural Science Foundation of China(50902040);National Natural Science Foundation of China(62071154);Natural Science Foundation of Heilongjiang Province of China(LH2020B011);Natural Science Foundation of Heilongjiang Province of China(LH2019B006);Scientific Research Projects of Basic Scientific Research Operational Expenses of Heilongjiang Provincial Colleges and Universities(2021-KYYWF-0171)

摘要/Abstract

摘要：

对称性破缺单原子催化剂因其独特的电子环境可显著提升析氢反应(HER)效率, 在电解水制氢领域具有良好应用前景. 然而, “对称性破缺特征”与HER性能之间的构效关系尚不明确, 制约了高性能单原子催化剂(SACs)的理性设计. 目前研究多集中于对称结构SACs的HER机制, 而对具备对称性破缺结构的SACs缺乏系统性解析. 本文结合密度泛函理论(DFT)计算与机器学习(ML)方法, 深入探究“对称性破缺特征”对HER活性的调控规律, 为设计高效能源转换催化剂提供新思路.

本文系统研究了金属-氮-单壁碳纳米管(M-N3C-SWCNT)单原子催化剂上的HER机制. 结果表明, 自旋密度对称破缺程度(D_asym)与HER活性呈近火山型关系, 位于火山曲线底部的催化剂表现出最优性能(如M-N3C-SWCNT中的Mn, Pd, Pt体系). 自旋密度对称性破缺对吸附位点电子密度的调节是导致这一现象的重要原因. 计算得到的M-N3C-SWCNT(Mn, Pd, Pt)催化剂的ΔG_H*值分别低至0.015、-0.018和-0.026 eV. 相比于对称配位的M-N4-SWCNT, 在M-N3C-SWCNT中引入自旋密度对称性破缺, 有利于促进活性位点未配对电子富集并降低反应能垒, 使HER活性(TOF)较对称配位结构催化剂最高提升达40倍. 基于DFT数据集构建的ML模型(R² = 0.89, RMSE = 0.126)精准识别出两个关键描述符: 对称性破缺效应和电子转移效应. 较弱的对称性破缺效应与较强的电子转移效应协同增强HER性能. ML模型将M-N3C-SWCNTs上的自旋密度对称性破缺进一步凝练为具有构效关系的对称性破缺效应项. 在ML预测模型指导下, 进一步的理论计算结果表明, 减弱M-N3C-SWCNT中M-N2键强度和电子转移能力, 能够提高其HER活性. 基于此, 提出了M-N3C-SWCNT上HER活化的双重机制, 即表面原子偏移和对位活化机制. 本研究建立的DFT-ML-DFT框架为结合DFT与ML进行可解释催化研究提供了有价值的参考.

综上, 本工作揭示了自旋密度对称性破缺调控HER的规律, 建立的机器学习预测框架与双活化机制可为新型单原子催化剂开发提供普适性设计策略, 并加深了通过对称性破缺调控单原子催化剂析氢反应的理解. DFT-ML-DFT的深度融合将加速高性能对称性破缺催化剂在氢气规模化生产中的应用进程.

关键词: 对称性破缺, 自旋密度, 析氢反应, 可解释机器学习, 单原子催化剂

Abstract:

Symmetry-broken single-atom catalysts (SACs) are pivotal due to their asymmetric electronic environments, which enhance the activity of the hydrogen evolution reaction (HER). This study investigated how symmetry breaking in SACs affects HER performance using density functional theory (DFT) and variable selection machine learning (ML). The study revealed a nearly volcano-shaped correlation between the degree of spin density symmetry breaking (D_asym) and HER activity, with catalysts at the base of the volcano showing enhanced HER activity. Spin density symmetry breaking facilitates the enrichment of unpaired electrons on the active sites and reduces HER energy barriers, resulting in up to a 40-fold enhancement in HER performance of symmetry-broken SACs compared to symmetric SACs. The ML model accurately identified key descriptors, such as symmetry breaking and electronic transfer effects, allowing spin density symmetry breaking on M-N3C-SWCNTs to be further condensed into an effect term with a structure-property relationship. A weaker symmetry breaking effect and a stronger electron transfer enhance HER performance. ML-guided analysis highlighted a spin selection-related Volmer-Heyrovsky pathway with a dual activation mechanism involving surface atom displacement and para-activation. These findings offer critical insights into the design of advanced HER catalysts by elucidating the interplay between symmetry-breaking properties and catalytic behavior.

Key words: Symmetry breaking, Spin density, Hydrogen evolution reaction, Interpretable machine learning, Single-atom catalyst

宋鑫, 李中华, 盛利, 刘扬. 单原子催化剂中自旋密度对称性破缺介导的析氢反应[J]. 催化学报, 2026, 80: 213-226.

Xin Song, Zhonghua Li, Li Sheng, Yang Liu. Spin density symmetry breaking-mediated hydrogen evolution in single-atom catalysts[J]. Chinese Journal of Catalysis, 2026, 80: 213-226.

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链接本文: https://www.cjcatal.com/CN/10.1016/S1872-2067(25)64837-6

https://www.cjcatal.com/CN/Y2026/V80/I1/213

图/表 7

Scheme 1. Overview of research process.

Fig. 1. HER performance and stability analysis of M-N3C-SWCNTs. (a) Calculated ΔGH* values, with the dashed line representing the |ΔGH*| of the Pt catalyst. (b) Comparison of ΔGH* between pristine SWCNT and M-N3C-SWCNT (M = Sc, Mn, Pd, and Pt). (c) Calculated volcano curve. (d) Calculated Eb and Ef. (e) Analysis of single-atom stability (ΔEb). (f) Calculated dissolution potential (Udiss) values. (g)-(i) AIMD simulations conducted at 300 K.

Fig. 2. The relationship between spin density symmetry breaking and HER activity on M-N3C-SWCNTs. (a)-(f) Schematic diagrams of spin density symmetry breaking. Yellow represents spin up, while cyan represents spin down. The isosurface value is 0.01 e/Bohr3 for Mn SACs, whereas for Pd and Pt SACs, it is 0.0001 e/Bohr3. (g) Simplified illustration of Dasym calculation using OpenCV. (h) The relationship between |ΔGH*| and Dasym. (i) The relationship between TOF and Dasym.

Fig. 3. 2D spin density distribution and reaction pathways. (a) 2D spin density distribution for M-N3C-SWCNT and M-N4-SWCNT (M = Mn, Pd and Pt). Positive and negative values represent spin up and spin down, respectively. The V-T and V-H pathways on Mn-N3C-SWCNT (b), Pd-N3C-SWCNT (c), and Pt-N3C-SWCNT (d).

Fig. 4. Feature selection and hyperparameter optimization of the VS-SISSO model applied to M-N3C-SWCNTs. (a) Feature selection diagram. (b) Optimal feature set selection using the elastic net method. (c) RMSE as a function of model complexity across various dimensions. (d) Distribution of absolute prediction errors for various hyperparameter combinations. (e)-(j) Performance comparison of the VS-SISSO model across different combinations of D and F.

Fig. 5. Correlation of model compositions with HER activity in M-N3C-SWCNTs. (a) Correlation of |c1·β1| with |ΔGH*|. (b) Correlation of |c2·β2| with |ΔGH*|. (c,d) HER performance comparison based on from |c1·β1| and |c2·β2| for M-N3C-SWCNT (M = Mn, Pd, and Pt). (e) Comparison of contributions from |c1·β1| and |c2·β2| for M-N3C-SWCNTs. (f) Importance analysis of features in the prediction model. (g) Evolutionary route of symmetry breaking.

Fig. 6. Relationship between composite descriptors and DFT calculation results. (a) Correlation of HER activity with ICOHPM-N2. (b) Correlation of HER activity with TDOS at Fermi level. (c) Diagram of dual activation mechanism. (d)-(i) Planar-average charge density difference of M-N3C-SWCNTs and M-N4-SWCNTs along the tube axis direction. Green represents regions of electron depletion, whereas pink denotes regions of electron accumulation. The isosurface value of all structures is 0.003 e/Bohr3. ΔΔρ = Δρadsorption site - Δρmetal atom.

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单原子催化剂中自旋密度对称性破缺介导的析氢反应

Spin density symmetry breaking-mediated hydrogen evolution in single-atom catalysts

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