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Published on: December 6, 2021
Design of Single-Atom Catalysts Anchored in N-Doped Biphenylene Using Symbolic Regression for Electrocatalytic
Zheng Shu1,2, Zhangsheng Shi3, Huaxian Jia4
1Joint Key Laboratory of the Ministry of Education, Institute of Applied Physics and Materials Engineering, University of Macau, Macau, Macau SAR, 999078, China.
Abstract:
Electrocatalytic nitrate reduction (NO3RR) presents a synergistic strategy, achieving dual benefits in energy transformation and environmental remediation through a single process. However, the complexity of its reaction pathway and the lack of descriptors impede the rational design of high-performance NO3RR electrocatalysts. Herein, employing a series of transition metal doped and nitrogen decorated biphenylene network (TM-CxNy@BPN), an inclusive recipe toward the stability, reaction mechanism, and activity trend of single atomic catalysts (SACs) for NO3RR is proposed by integrating multidimensional insights from coordination environment, thermodynamic and electrochemical stability, Gibbs free energy profiles, electronic properties, and activity descriptors. It is revealed that the NO3RR performance of SACs is highly correlated with their local environments. Furthermore, the hybridization between the TM-3d orbitals and 2π* orbitals of NO3 - gives rise to the formation of d-π* orbitals, thus promoting the NO3 - activation. A symbolic regression is designed to capture the hidden descriptors of NO3RR, outperforming than using single adsorbate or electronic descriptors for hyper dimensional system entailing large geometric variability.
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