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<p>We constructed a series of single-atom MOFs using phthalocyanine as the matrix to investigate their electrocatalytic performance for chlorine evolution reaction (CER). Density functional theory (DFT) and machine learning (ML) were used to explore the differences in the catalytic performance of MOFs composed of different transition metal (TM) atoms for CER and the reasons for these differences. When the Pt atoms are used as active sites, the Gibbs free energy changes (ΔG) of CER and competitive oxygen evolution reaction (OER) are − 0.26 and 2.42&#xa0;eV, respectively. The comparison of the overpotentials for OER and CER indicates that Pt@Pc possesses excellent selectivity for CER. Based on AIMD simulations, it was found that Pt@Pc exhibits excellent activity and selectivity for CER. The piecewise function of the d-band center and the ΔG of CER indicates that the d-band center has a significant impact on ΔG, but the d-band center alone is insufficient to describe ΔG on 28 different TM@Pc. Feature importance analysis using machine learning confirmed that the number of d electrons and the electron affinity of the metal active sites both have a significant impact on the Gibbs free energy change of CER.</p>

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Phthalocyanine-based single-atom catalysts as electrocatalysts for chlorine evolution reaction

  • 期刊论文

  • 发表日期：

    2026年3月30日

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  • Jiake Fan,
  • Lei Yang,
  • Lixin Ye,
  • Mengyun Mei,
  • Weihua Zhu

摘要

We constructed a series of single-atom MOFs using phthalocyanine as the matrix to investigate their electrocatalytic performance for chlorine evolution reaction (CER). Density functional theory (DFT) and machine learning (ML) were used to explore the differences in the catalytic performance of MOFs composed of different transition metal (TM) atoms for CER and the reasons for these differences. When the Pt atoms are used as active sites, the Gibbs free energy changes (ΔG) of CER and competitive oxygen evolution reaction (OER) are − 0.26 and 2.42 eV, respectively. The comparison of the overpotentials for OER and CER indicates that Pt@Pc possesses excellent selectivity for CER. Based on AIMD simulations, it was found that Pt@Pc exhibits excellent activity and selectivity for CER. The piecewise function of the d-band center and the ΔG of CER indicates that the d-band center has a significant impact on ΔG, but the d-band center alone is insufficient to describe ΔG on 28 different TM@Pc. Feature importance analysis using machine learning confirmed that the number of d electrons and the electron affinity of the metal active sites both have a significant impact on the Gibbs free energy change of CER.