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Journal of the American Chemical Society· 2026Q1

Rigor and Reproducibility in Electrocatalysis: Integrating Theory and Experiment

Líney Árnadóttir, Alexander Bagger, Jason S. Bates, Ezra Lee Clark et al.

Short summary

A framework is proposed for rigorously integrating atomistic modeling (DFT) with experimental data to improve the reliability and predictive power of electrocatalysis research.

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Key points

  • Atomistic modeling using DFT is crucial for understanding electrocatalytic reactivity at a molecular level.
  • Practical approximations in DFT models can impact the reliability of insights into catalytic processes.
  • A framework is proposed for integrating theory and experiment with multiple connection points to enhance rigor and reproducibility.
  • Opportunities exist for validating theoretical models concerning active site structure, reaction energetics, and microkinetics.

AI-generated from the title and abstract; the full text is not read.

Abstract

Abstract Electrocatalysis is central to electrified energy conversion technologies, including the production of fuels and chemicals from renewable electricity. In recent years, atomistic modeling based on density functional theory (DFT) has become an indispensable tool for catalysis researchers because it can provide a molecular-level perspective of catalytic reactivity that is otherwise inaccessible through experimental measurements. Computational electrocatalysis model inputs are intended to capture fundamental understanding of the complex interfacial environment of the catalytic active site, but they rely on practical approximations that can affect the reliability of insights gained from DFT. This Perspective outlines a framework for rigorous and reproducible integration of theory and experiment in heterogeneous electrocatalysis research. We discuss state-of-the-art computational methods and sources of error in model development and interpretation. We describe opportunities for validation of theoretical models and experimental interpretations as they pertain to the structure of active sites, reaction energetics, and microkinetic modeling. We provide examples to help computational researchers develop models that move beyond obtaining qualitative agreement with reactivity trends, and toward the development of rigorous mechanistic insights that can be leveraged to predict promising new catalysts or operating conditions. Rigor and reproducibility are enhanced when theory and experiment have multiple nodes of connection, thereby enhancing the longevity and robustness of conclusions and insights about electrocatalytic reactivity.

The authors' abstract, as published at the source. Journal of the American Chemical Society, 2026 · DOI ↗

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Field: Renewable Energy, Sustainability and the Environment

Renewable Energy, Sustainability and the EnvironmentEnergy