The electrocatalytic N2 reduction activity of core-shell iron nanoalloy catalysts: a density functional theory (DFT) study

被引:2
作者
Das, Arunendu [1 ]
Das, Sandeep [1 ]
Pathak, Biswarup [1 ]
机构
[1] Indian Inst Technol Indore, Dept Chem, Indore 453552, India
关键词
AMMONIA-SYNTHESIS; OXYGEN REDUCTION; MECHANISM; FE; NANOCLUSTER;
D O I
10.1039/d3cp03453d
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
A molecular level understanding of the property evolution in binary nanoalloy catalysts is crucial for designing novel electrocatalysts for ammonia synthesis. In this regard, designing core-shell catalyst structures has been a versatile approach to achieve the product selectivity. Herein, we investigated the activity evolution of Fe-based core-shell (M-15@Fe-50) (M = Co, Ni, or Cu) clusters for the nitrogen reduction reaction (NRR). Nitrogen reduction following the associative mechanistic pathway is significantly activated over the Cu-15@Fe-50 cluster. The d-band center from the electronic structure analysis is found to be upshifted, justifying the activity towards the NRR. The reduction reaction occurs via the surface restructuring of the catalyst, in which the *NH2 formation is found to be the lowest endergonic potential determining step compared to pristine Fe(110). Based on this, the high NRR activity of the Cu-15@Fe-50 cluster has been proposed, which, we envision, will provide useful insights into the position and compositional effects of core-shell structures for the discovery of efficient NRR electrocatalysts.
引用
收藏
页码:32913 / 32921
页数:9
相关论文
共 50 条
  • [21] Activity of CeO2(111) supported Mnx(x=1-6) for electrochemical N2 reduction reaction: Insights from density functional theory
    Cao, Heng
    Zhou, Shulan
    MOLECULAR CATALYSIS, 2024, 569
  • [22] MOF-Derived Co3O4@NC with Core-Shell Structures for N2 Electrochemical Reduction under Ambient Conditions
    Luo, Shijian
    Li, Xiaoman
    Zhang, Baohai
    Luo, Zhenglong
    Luo, Min
    ACS APPLIED MATERIALS & INTERFACES, 2019, 11 (30) : 26891 - 26897
  • [23] Mo-based 2D MOF as a highly efficient electrocatalyst for reduction of N2 to NH3: a density functional theory study
    Cui, Qianyi
    Qin, Gangqiang
    Wang, Weihua
    Geethalakshmi, K. R.
    Du, Aijun
    Sun, Qiao
    JOURNAL OF MATERIALS CHEMISTRY A, 2019, 7 (24) : 14510 - 14518
  • [24] Study on N2 selectivity of iron-manganese ore catalysts in NH3-SCR process
    Jiang, Xuan
    Yang, Qi
    Zhu, Baozhong
    Li, Qingxin
    Liu, Jun
    Xu, Minggao
    Sun, Yunlan
    MOLECULAR CATALYSIS, 2024, 569
  • [25] Catalytic Activity for Oxygen Reduction Reaction on CoN2-Graphene: A Density Functional Theory Study
    Zhang, Jing
    Liu, Lijuan
    Liu, Wen
    Zhang, Mingang
    JOURNAL OF THE ELECTROCHEMICAL SOCIETY, 2016, 163 (03) : F160 - F165
  • [26] Investigating the electrocatalytic reduction of 2,4,6-tri-nitro-toluene (TNT) using density functional theory methods
    Wong, Andrew Jark-Wah
    Miller, Joshua Lee
    Perdue, Brandon
    Janik, Michael John
    GREEN CHEMISTRY, 2023, 25 (13) : 5097 - 5112
  • [27] Tuning the activity and selectivity of nitrogen reduction reaction on double-atom catalysts by B doping: A density functional theory study
    Han, Shuang
    Wei, Xiumei
    Huang, Yuhong
    Zhang, Jianmin
    Yang, Jian
    Wang, Zhenduo
    NANO ENERGY, 2022, 99
  • [28] Selective Electrocatalytic H2O2 Generation by Cobalt@N-Doped Graphitic Carbon Core-Shell Nanohybrids
    Lenarda, Anna
    Bevilacqua, Manuela
    Tavagnacco, Claudio
    Nasi, Lucia
    Criado, Alejandro
    Vizza, Francesco
    Melchionna, Michele
    Prato, Maurizio
    Fornasiero, Paolo
    CHEMSUSCHEM, 2019, 12 (08) : 1664 - 1672
  • [29] Mechanistic insight into electrocatalytic CO2 reduction to formate by the iron(I) porphyrin complex: A DFT study
    Wang, Yaqing
    Lai, Wenzhen
    MOLECULAR CATALYSIS, 2024, 566
  • [30] Kinetics of N2 Release from Diazo Compounds: A Combined Machine Learning-Density Functional Theory Study
    Farshadfar, Kaveh
    Hashemi, Arsalan
    Khakpour, Reza
    Laasonen, Kari
    ACS OMEGA, 2023, 9 (01): : 1106 - 1112