Proposing Explainable Descriptors Towards Enhanced N2 Reduction Performance on the Two-Dimensional Bismuthine Nanosheets Modified by P-block Element-based Electrocatalysts

IF 2.9 3区 化学 Q3 CHEMISTRY, PHYSICAL
Zhongti Sun, Dengning Sun, Yangyang Wan, Guoqiang Liu, Ruirui Wang, Hao Shen, Jing Chen, Ying Wang, Xiaokun Du, Tao Ye
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Abstract

P-block element-based electrocatalysts that feature tunable electronic structure to achieve exceptional N2 activation and proton suppression have garnered extensive interests in the electrochemical N2 reduction reaction (NRR). Albeit various reaction mechanisms were proposed to understand and optimize the NRR performance, the method to effectively design and rapidly screen potential candidates was still elusive. Herein, a couple of explicit and interpretable descriptors on the entire p-block element-based electrocatalysts are put forward to predict NRR activity and selectivity via high-throughput theoretical simulations and symbolic regression algorithm, taking two-dimensional (2D) bismuthine doped and adsorbed by p-block elements as an example. The descriptor is merely composed by inherent atomic properties (p orbital electron number, electron affinity, electronegativity, and atomic radius, etc.) combining with algebraic operators, independent on the intricated DFT calculations. Multi-task regression results demonstrate that the doped and adsorbed bismuthine system possess the same descriptor, namely, doped descriptor can primely forecast the NRR performance of adsorbed system, vice versa. Five potential candidates (5/40) with outstanding NRR activity, selectivity and stability are screened. C-doped and Si-doped bismuthine possess the less negative limiting potential of NRR [UL(NRR)] with 0.46 and 0.68 V and positive [UL(NRR)UL(HER)] value of 1.15 and 0.13 V, respectively, superior to the majority of reported p-block element-based electrocatalyst, which are expected to be verified by the experimental research. This work offers a feasible solution for developing promising NRR electrocatalysts and potentially other electrochemical reactions on the basis of explainable descriptor using geometric information and intrinsic atomic quantities.
p -嵌段元素基电催化剂修饰二维铋纳米片增强N2还原性能的可解释描述符
基于p -嵌段元素的电催化剂具有可调的电子结构,可以实现特殊的N2活化和质子抑制,在电化学N2还原反应(NRR)中引起了广泛的兴趣。尽管人们提出了多种反应机制来理解和优化NRR的性能,但有效设计和快速筛选潜在候选物的方法仍然难以捉摸。本文以p块元素掺杂和吸附的二维铋为例,通过高通量理论模拟和符号回归算法,提出了一组明确的、可解释的全p块元素电催化剂的描述符,以预测NRR活性和选择性。描述符仅仅是由固有的原子性质(p轨道电子数、电子亲和性、电负性和原子半径等)与代数算子结合而成,与复杂的DFT计算无关。多任务回归结果表明,掺杂和吸附铋体系具有相同的描述符,即掺杂描述符可以初步预测吸附体系的NRR性能,反之亦然。筛选出5个具有显著NRR活性、选择性和稳定性的候选物(5/40)。c掺杂和si掺杂铋酸盐的NRR [UL(NRR)]的负极限电位较低,分别为 0.46 V和 0.68 V,正极限电位[UL(NRR))分别为1.15 V和0.13 V,优于大多数已报道的p-区块元素基电催化剂,这有待于实验研究的验证。这项工作为基于几何信息和本征原子量的可解释描述符开发有前途的NRR电催化剂和潜在的其他电化学反应提供了可行的解决方案。
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来源期刊
Physical Chemistry Chemical Physics
Physical Chemistry Chemical Physics 化学-物理:原子、分子和化学物理
CiteScore
5.50
自引率
9.10%
发文量
2675
审稿时长
2.0 months
期刊介绍: Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.
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