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Theoretical Study of Metal-Nitrogen Co-Doped Graphene Catalysts for Electrochemical Nitrogen Reduction Reaction

Shan, Weitao (2022) Theoretical Study of Metal-Nitrogen Co-Doped Graphene Catalysts for Electrochemical Nitrogen Reduction Reaction. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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A primary challenge of electrochemically synthesizing NH3 from N2 is to find efficient catalysts to break the inert N≡N bond under ambient conditions. Metal-nitrogen co-doped carbon (M-N-C) catalysts have exhibited encouraging performance for electrochemical nitrogen reduction reaction (NRR). Fundamental understandings related to the mechanism underlying the NRR performance on M-N-C catalysts are critically needed to further improve the activity and selectivity of these electrocatalysts.
In this study, density functional theory (DFT) calculations were performed to predict the NRR activity and selectivity of Fe-N-C, Co-N-C, and Ni-N-C catalysts. Specifically, forty-five types of MNxCy (M = Fe, Co, and Ni, x varies from 1 to 4, y varies from 1 to 3) moieties were modeled to relate the predicted NRR activity and selectivity with the chemical environment of active sites. The FeN3C1 site was predicted to have the best NRR activity and selectivity among all the sites examined. In particular, the limiting potential for NRR on the NiN3 site was predicted to be -0.83 V, which is in good agreement with the experimentally observed optimal potential of -0.80 V for NRR on Ni-N-C catalysts. For the first time, the influence of structural distortion on the NRR catalytic performance of Fe-N-C catalysts was computationally investigated. Both the NRR activity and selectivity were found to be enhanced on compressively strained FeN3 and FeN4 sites. The chemical bonding analysis revealed that the stronger binding of *NNH on the strained active sites contributed to the enhanced NRR activity. Furthermore, the electrochemical stability of FeN3 and FeN4 sites was evaluated by computing the free energy changes of NRR intermediate species as a function of pH value and applied potential. The calculated Pourbaix diagrams were demonstrated to explain the experimentally observed optimal condition for NRR. This study produces new knowledge of the relation between chemical environment and catalytic performance of NRR active sites, the beneficial effect of structural distortion in M-N-C catalysts for NRR, and a computational approach to predict the electrochemical stability of M-N-C catalysts. Therefore, this study provides guidance to the rational design and synthesis of high-performance M-N-C catalysts for electrochemical NRR.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Shan, Weitaowes66@pitt.eduwes660000-0002-5414-5710
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairWang, Guofengguw8@pitt.eduguw80000-0001-8249-4101
Committee MemberMao, Scottsxm2@pitt.edusxm20000-0003-0202-4391
Committee MemberOhodnicki, PaulPRO8@pitt.edupro80000-0003-2115-0692
Committee MemberLee, Sangyeopsylee@pitt.edusylee0000-0002-8783-9380
Committee MemberLeu, Paulpleu@pitt.edupleu0000-0002-1599-7144
Date: 16 January 2022
Date Type: Publication
Defense Date: 13 October 2021
Approval Date: 16 January 2022
Submission Date: 3 October 2021
Access Restriction: 1 year -- Restrict access to University of Pittsburgh for a period of 1 year.
Number of Pages: 122
Institution: University of Pittsburgh
Schools and Programs: Swanson School of Engineering > Materials Science and Engineering
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: nitrogen reduction reaction, carbon-based catalysts, electrochemical, density functional theory, active site structures, free energy calculation, structural distortion, implicit solvation, electrochemical stability
Date Deposited: 16 Jan 2022 18:28
Last Modified: 16 Jan 2023 06:15

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  • Theoretical Study of Metal-Nitrogen Co-Doped Graphene Catalysts for Electrochemical Nitrogen Reduction Reaction. (deposited 16 Jan 2022 18:28) [Currently Displayed]


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