About

Log in?

DTU users get better search results including licensed content and discounts on order fees.

Anyone can log in and get personalized features such as favorites, tags and feeds.

Log in as DTU user Log in as non-DTU user No thanks

DTU Findit

Journal article

Dipole-field interactions determine the CO2 reduction activity of 2D Fe-N-C single atom catalysts

In Acs Catalysis 2020, Volume 10, pp. 7826-7835
From

Department of Physics, Technical University of Denmark1

Catalysis Theory Center, Department of Physics, Technical University of Denmark2

Stanford University3

Iron−nitrogen-doped graphene (FeNC) has emerged as an exciting earth-abundant catalyst for electrochemical CO2 reduction (CO2R). However, standard theoretical approaches based on density functional theory (DFT) suggest complete poisoning of the active sites and are unable to rationalize the experimentally observed dramatic pH dependence and Tafel slopes, which have a critical impact on the electrocatalytic activity.

In this work, we overcome these challenges through a rigorous theoretical investigation of FeNC single-atom catalysts using a combination of several state-of-the-art methods: hybrid functionals, continuum solvation, and potential-dependent electrochemical reaction energetics. Our model shows dipole-field interactions in CO2 adsorption to determine the overall activity, which resolves the contentious origin of experimentally observed pH dependence and rationalizes differences in activity and Tafel slopes among different samples in experimental work.

A critical conclusion of our study is that single-atom catalysts can be tuned for electrocatalytic activity not only through the traditionally considered binding energies but also through the corresponding surface dipole moment of rate-determining surface intermediates. Our presented methodology paves the way for accurate mechanistic studies as well as the computational catalyst design of general single-atom catalysts.

Language: English
Publisher: American Chemical Society
Year: 2020
Pages: 7826-7835
ISSN: 21555435
Types: Journal article
DOI: 10.1021/acscatal.0c01375
ORCIDs: Chan, Karen

DTU users get better search results including licensed content and discounts on order fees.

Log in as DTU user

Access

Analysis