Accurate Modelling of the 2e- Oxygen Reduction Reaction by Assessing Molecular Errors
Ricardo Urrego-Ortiz a b, Federico Calle-Vallejo b c
a Department of Materials Science and Chemistry Physics & Institute of Theoretical and Computational Chemistry (IQTCUB), University of Barcelona, C/Martí I Franquès 1, 08028 Barcelona, Spain.
b Nano-Bio Spectroscopy Groups and European Theoretical Spectroscopy Facility (ETSF), Department of Advanced Materials and Polymers: Physics, Chemistry and Technology, University of the Basque Country UPV/EHU, Av. Tolosa 72, 20018 San Sebastián, Spain.
c IKERBASQUE, Basque Foundation for Science, Plaza de Euskadi 5, 48009 Bilbao, Spain.
Materials for Sustainable Development Conference (MATSUS)
Proceedings of MATSUS Fall 2024 Conference (MATSUSFall24)
#C&T - electrocat - Computational and theoretical electrocatalysis
Lausanne, Switzerland, 2024 November 12th - 15th
Organizers: Federico Calle-Vallejo and Max Garcia-Melchor
Oral, Ricardo Urrego-Ortiz, presentation 118
DOI: https://doi.org/10.29363/nanoge.matsusfall.2024.118
Publication date: 28th August 2024

The two-electron oxygen reduction reaction (2e- ORR) is an appealing alternative to produce hydrogen peroxide (H2O2) for isolated communities, where water treatment infrastructure is rudimentary or non-existent [1]. Notwithstanding, to efficiently carry the 2e- ORR, stable and selective electrocatalysts are needed that circumvent the complete reduction to water (4e- ORR). As pure noble metals and their alloys generally display the best performance, affordable and active materials are intensively sought after [2,3].

 

Computational models to design ORR electrocatalysts extensively rely on DFT-calculated adsorption energies of key intermediates, such as *OOH and *OH. To avoid the ill-defined energy of O2, water is used as reference, which is suitable for the 4e- ORR. However, when applied to the 2e- ORR, it is often overlooked the fact that H2O2 is seriously misdescribed by density functional theory calculations, potentially harming the conclusions of widely used routines to design improved electrocatalysts [4,5].

 

In this presentation, I will show that the DFT energies of O2 and H2O2 entail large errors for several exchange-correlation functionals and that these errors are correlated. I will also explain how this prevents the calculation of accurate equilibrium potentials and distorts the free-energy diagram of the ideal catalyst, even when water is used as a reference. Finally, I will detail how Sabatier-type plots are affected when incorrect energies of molecules are used for the 2e- ORR, emphasizing that experimental trends of real materials are matched when both O2 and H2O2 energy are rectified.

 

 

References

[1]        S. Brueske, C. Kramer, A. Fisher, Bandwidth Study on Energy Use and Potential Energy Saving Opportunities in U.S. Chemical Manufacturing, (2015). https://www.osti.gov/biblio/1248749.

[2]        S.C. Perry, D. Pangotra, L. Vieira, L.-I. Csepei, V. Sieber, L. Wang, C. Ponce De León, F.C. Walsh, Electrochemical synthesis of hydrogen peroxide from water and oxygen, Nat Rev Chem 3 (2019) 442–458. https://doi.org/10.1038/s41570-019-0110-6.

[3]        S. Siahrostami, A. Verdaguer-Casadevall, M. Karamad, D. Deiana, P. Malacrida, B. Wickman, M. Escudero-Escribano, E.A. Paoli, R. Frydendal, T.W. Hansen, I. Chorkendorff, I.E.L. Stephens, J. Rossmeisl, Enabling direct H2O2 production through rational electrocatalyst design, Nature Mater 12 (2013) 1137–1143. https://doi.org/10.1038/nmat3795.

[4]        M.O. Almeida, M.J. Kolb, M.R.V. Lanza, F. Illas, F. Calle‐Vallejo, Gas‐Phase Errors Affect DFT‐Based Electrocatalysis Models of Oxygen Reduction to Hydrogen Peroxide, ChemElectroChem 9 (2022) e20220021 (1-7). https://doi.org/10.1002/celc.202200210.

[5]        R. Urrego-Ortiz, M. Almeida, F. Calle-Vallejo, Error awareness in the volcano plots of oxygen electroreduction to hydrogen peroxide, ChemSusChem (2024) e202400873. https://doi.org/10.1002/cssc.202400873.

The project that gave rise to these results also received the support of a PhD fellowship from “la Caixa” Foundation (ID 100010434, fellowship code LCF/BQ/DI22/11940040).

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