Electrochemical CO2 Reduction over Metal-/Nitrogen-Doped Graphene Single-Atom Catalysts Modeled Using the Grand-Canonical Density Functional Theory
Abstract
Renewably driven, electrochemical conversion of carbon dioxide to value-added products is expected to be a critical tool in global decarbonization. However, theoretical studies based on the computational hydrogen electrode (CHE) largely ignore the nonlinear effects of the applied potential on the calculated results, leading to inaccurate predictions of catalytic behavior or mechanistic pathways. Here, we use grand canonical density functional theory (GC-DFT) to model electrochemical CO2 reduction (CO2R) over metal- and nitrogen-doped graphene catalysts (MNCs) and explicitly include the effects of the applied potential. We used GC-DFT to compute the CO2R to CO reaction intermediate energies at –0.3, –0.7 and –1.2 VSHE catalyzed by MNCs each doped with one of the ten 3d block metals coordinated by four pyridinic nitrogen atoms. Our results predict that Sc-, Ti-, Co-, Cu-, and Zn-N4Cs effectively catalyze CO2R at moderate to large reducing potentials (–0.7 to –1.2 VSHE). ZnN4C is a particularly promising electrocatalyst for CO2R to CO both at low and moderate applied potentials based on our thermodynamic analysis. Our findings also explain the observed pH independence of CO production over FeN4C and predict that the rate determining step of CO2R over FeN4C is not *CO2- formation but rather *CO desorption. Additionally, themore »
- Authors:
-
- Univ. of Colorado, Boulder, CO (United States)
- Univ. of Colorado, Boulder, CO (United States); King Fahd Univ. of Petroleum and Minerals, Dhahran (Saudi Arabia)
- Univ. of Colorado, Boulder, CO (United States); Kuwait Univ., Safat (Kuwait)
- Univ. of Colorado, Boulder, CO (United States); National Renewable Energy Lab. (NREL), Golden, CO (United States); Delft Univ. of Technology (The Netherlands)
- Publication Date:
- Research Org.:
- Univ. of Colorado, Boulder, CO (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Basic Energy Sciences (BES); National Science Foundation (NSF)
- OSTI Identifier:
- 1879981
- Grant/Contract Number:
- SC0022247; ACI-1532235; ACI-1532236
- Resource Type:
- Accepted Manuscript
- Journal Name:
- ACS Catalysis
- Additional Journal Information:
- Journal Volume: 12; Journal ID: ISSN 2155-5435
- Publisher:
- American Chemical Society (ACS)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 10 SYNTHETIC FUELS; 25 ENERGY STORAGE; 36 MATERIALS SCIENCE; 37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; electrocatalysis; computational chemistry; single-atom catalysts; electrochemistry; grand canonical density functional theory; DFT calculations; surface chemistry; CO2 reduction; catalysts; energy; free energy; metals; transition metals
Citation Formats
Brimley, Paige, Almajed, Hussain, Alsunni, Yousef, Alherz, Abdulaziz W., Bare, Zachary J. L., Smith, Wilson A., and Musgrave, Charles B. Electrochemical CO2 Reduction over Metal-/Nitrogen-Doped Graphene Single-Atom Catalysts Modeled Using the Grand-Canonical Density Functional Theory. United States: N. p., 2022.
Web. doi:10.1021/acscatal.2c01832.
Brimley, Paige, Almajed, Hussain, Alsunni, Yousef, Alherz, Abdulaziz W., Bare, Zachary J. L., Smith, Wilson A., & Musgrave, Charles B. Electrochemical CO2 Reduction over Metal-/Nitrogen-Doped Graphene Single-Atom Catalysts Modeled Using the Grand-Canonical Density Functional Theory. United States. https://doi.org/10.1021/acscatal.2c01832
Brimley, Paige, Almajed, Hussain, Alsunni, Yousef, Alherz, Abdulaziz W., Bare, Zachary J. L., Smith, Wilson A., and Musgrave, Charles B. Thu .
"Electrochemical CO2 Reduction over Metal-/Nitrogen-Doped Graphene Single-Atom Catalysts Modeled Using the Grand-Canonical Density Functional Theory". United States. https://doi.org/10.1021/acscatal.2c01832. https://www.osti.gov/servlets/purl/1879981.
@article{osti_1879981,
title = {Electrochemical CO2 Reduction over Metal-/Nitrogen-Doped Graphene Single-Atom Catalysts Modeled Using the Grand-Canonical Density Functional Theory},
author = {Brimley, Paige and Almajed, Hussain and Alsunni, Yousef and Alherz, Abdulaziz W. and Bare, Zachary J. L. and Smith, Wilson A. and Musgrave, Charles B.},
abstractNote = {Renewably driven, electrochemical conversion of carbon dioxide to value-added products is expected to be a critical tool in global decarbonization. However, theoretical studies based on the computational hydrogen electrode (CHE) largely ignore the nonlinear effects of the applied potential on the calculated results, leading to inaccurate predictions of catalytic behavior or mechanistic pathways. Here, we use grand canonical density functional theory (GC-DFT) to model electrochemical CO2 reduction (CO2R) over metal- and nitrogen-doped graphene catalysts (MNCs) and explicitly include the effects of the applied potential. We used GC-DFT to compute the CO2R to CO reaction intermediate energies at –0.3, –0.7 and –1.2 VSHE catalyzed by MNCs each doped with one of the ten 3d block metals coordinated by four pyridinic nitrogen atoms. Our results predict that Sc-, Ti-, Co-, Cu-, and Zn-N4Cs effectively catalyze CO2R at moderate to large reducing potentials (–0.7 to –1.2 VSHE). ZnN4C is a particularly promising electrocatalyst for CO2R to CO both at low and moderate applied potentials based on our thermodynamic analysis. Our findings also explain the observed pH independence of CO production over FeN4C and predict that the rate determining step of CO2R over FeN4C is not *CO2- formation but rather *CO desorption. Additionally, the GC-DFT computed density of states analysis illustrates how the electronic states of MNCs and adsorbates change non-uniformly with applied potential, resulting in a significantly increased *CO2- stability relative to other intermediates and demonstrating that formation of the adsorbed *CO2- anion is critical to CO2R activation. Furthermore, this work demonstrates how GC-DFT paves the way for physically realistic and accurate theoretical simulations of reacting electrochemical systems.},
doi = {10.1021/acscatal.2c01832},
journal = {ACS Catalysis},
number = ,
volume = 12,
place = {United States},
year = {Thu Aug 04 00:00:00 EDT 2022},
month = {Thu Aug 04 00:00:00 EDT 2022}
}
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