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Federico Calle-Vallejo^1,2

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Summary

This summary is machine-generated.

Computational methods are crucial for designing efficient electrocatalysts for oxygen evolution (OER) and oxygen reduction (ORR). This work introduces novel descriptors and methods to overcome limitations of current models, enhancing electrocatalyst design.

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Area of Science:

Electrochemistry and Materials Science
Computational Materials Design

Background:

Oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) are vital for energy technologies but are limited by sluggish kinetics and expensive catalysts.
Current computational models rely on intermediate free energies and scaling relations, which have historically oversimplified catalyst performance limitations.
The established paradigm of breaking scaling relations for OER/ORR electrocatalysts has shown limitations in improving overpotential.

Purpose of the Study:

To critically evaluate the prevailing computational approaches for OER and ORR electrocatalyst design.
To introduce and explain novel computational descriptors and optimization strategies beyond traditional scaling relations.
To provide quantitative tools for the rational design and optimization of advanced electrocatalysts.

Main Methods:

Review and critique of established computational models based on intermediate free energies and scaling relations.
Introduction of new concepts including electrochemical symmetry, delta-epsilon optimization, and bifunctional volcano plots.
Emphasis on error awareness in computational predictions for electrocatalyst development.

Main Results:

Demonstration that breaking the *OOH/*OH scaling relation does not guarantee improved OER overpotential.
Development of alternative descriptors and methodologies to address limitations of current computational models.
Establishment of quantitative tools for more effective computational design of OER and bifunctional OER/ORR electrocatalysts.

Conclusions:

The traditional focus on breaking scaling relations for OER/ORR electrocatalysts is insufficient for optimal performance.
Novel computational approaches, including electrochemical symmetry and delta-epsilon optimization, offer promising alternatives.
This work provides a framework for enhanced computational design and optimization of next-generation electrocatalysts.