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Updated: Aug 3, 2026

Simple Methods for the Preparation of Non-noble Metal Bulk-electrodes for Electrocatalytic Applications
Published on: June 21, 2017
Tailoring metals, axial ligands, and carbon substrates in TMN4-graphene for direct seawater electrolysis: A
Wenhao Miao1, Qiuling Jiang2, Xiuxuan Hou2
1College of Chemical Engineering, Inner Mongolia University of Technology, Inner Mongolia Key Laboratory of Theoretical and Computational Chemistry Simulation, Hohhot 010051, PR China.
Abstract:
Driven by the surging demand for sustainable energy production, direct seawater electrolysis for hydrogen generation has emerged as a pivotal research frontier. As a result, the design and optimization of highly stable, active, and selective oxygen-evolution-reaction (OER) catalysts has garnered considerable attention. In this study, by modifying the N-doped graphene substrates (S1-S3), introducing different axial ligands (X = Cl or OH), and tuning the transition metals (TM) at the active sites, we designed a total of 144 catalysts, consisting of 48 TMN4-Sk and 96 TMN4-Sk-X variants. By combining density functional theory (DFT) calculations with data-driven machine learning (ML) techniques, we carried out a thorough evaluation of these 144 TMN4 catalysts for use as anode catalysts in direct seawater electrolysis. Using DFT calculations, we identified 12 catalysts with superior OER activity and 4 catalysts (IrN4-S1, CoN4-S3, CoN4-S1-OH, MnN4-S1-Cl) exhibiting good selectivity of chloride oxidation reaction (ClOR) vs. OER under simulated seawater conditions, holding promise as candidates for direct seawater electrolysis. To predict the correlation between the intrinsic properties of 119 stable TMN4-Sk and TMN4-Sk-X catalysts and their OER activity, ML algorithms were applied. According to the Gradient Boosting Regression (GBR) model, the catalysts' OER performance is strongly governed by properties such as the metal center's electronegativity (χ), Bader charge (QTM), and the number of d-electrons (Nd). More importantly, we identified a descriptor D that exhibits a strong correlation with OER overpotential (ηOER). These features are therefore considered key descriptors of OER catalytic activity. This work not only deepens our understanding of OER mechanism but also identifies effective catalysts with lower overpotentials, thereby establishing a basis for designing higher-efficiency electrocatalysts for hydrogen generation through direct seawater electrolysis.
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