Rigor & Reproducibility in Electrocatalysis: Best Practices for Kinetic Studies
Abstract
Kinetic measurements can support or falsify mechanistic hypotheses in electrocatalysis, but only when rates reflect intrinsic catalytic behavior and models separate kinetic information from experimental artifacts and interfacial complexity. This perspective presents best practices for acquiring and interpreting electrocatalytic kinetic data, including mitigating artifacts arising from transport, ohmic losses, catalyst restructuring, contamination, and incomplete product accounting. Similarly, we provide guidelines for constructing rate expressions that treat elementary charge transfer, adsorption, and surface coverage, which enable interpretation of kinetic observables like apparent transfer coefficients, rate orders, and apparent activation energies that reflect properties of an interconnected reaction network. Mechanistic conclusions are strongest when competing hypotheses are tested against multiple complementary observables, including spectroscopy, isotopic labeling, and theory, enabling meaningful and reproducible mechanistic comparisons across laboratories.
Related
- Reproducibility, Benchmarks, and Mechanistic Diversity: Building Trust in Computational Electrocatalysis for the AI Era
- Spectroscopic–Catalytic Onset Decoupling in Energy Electrocatalysis: Evidence, Mechanistic Hypotheses and Research Priorities from 250 Studies
- Coffee Husk-Derived Activated Carbon for the Adsorptive Removal of Imatinib Mesylate from Water: Kinetic, Isotherm, Thermodynamic, and DFT Studies
- Active nanoglass powers metamaterial electrocatalysis.
- Electronic modulation of confined NiFe nanoalloys in hierarchical C3N4/CNT frameworks for bifunctional oxygen electrocatalysis
BibTeX
@misc{adams2026rigor,
title = {{Rigor & Reproducibility in Electrocatalysis: Best Practices for Kinetic Studies}},
author = {Jason Adams and Jason S. Bates and David Raciti and Robert E. Warburton and Adam Holewinski and Joaquin Resasco and Kelsey Stoerzinger and Anne C. Co and G. T. Kasun Kalhara Gunasooriya and Marcel Schreier and Anthony Shoji Hall and Elizabeth J. Biddinger and Ezra Clark and Eric Stuve},
howpublished = {ChemRxiv},
year = {2026},
month = oct,
doi = {10.26434/chemrxiv.15010884/v1},
url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010884/v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Rigor & Reproducibility in Electrocatalysis: Best Practices for Kinetic Studies
AU - Jason Adams
AU - Jason S. Bates
AU - David Raciti
AU - Robert E. Warburton
AU - Adam Holewinski
AU - Joaquin Resasco
AU - Kelsey Stoerzinger
AU - Anne C. Co
AU - G. T. Kasun Kalhara Gunasooriya
AU - Marcel Schreier
AU - Anthony Shoji Hall
AU - Elizabeth J. Biddinger
AU - Ezra Clark
AU - Eric Stuve
PY - 2026
DA - 2026/10/22
PB - ChemRxiv
DO - 10.26434/chemrxiv.15010884/v1
UR - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010884/v1
AB - Kinetic measurements can support or falsify mechanistic hypotheses in electrocatalysis, but only when rates reflect intrinsic catalytic behavior and models separate kinetic information from experimental artifacts and interfacial complexity. This perspective presents best practices for acquiring and interpreting electrocatalytic kinetic data, including mitigating artifacts arising from transport, ohmic losses, catalyst restructuring, contamination, and incomplete product accounting. Similarly, we provide guidelines for constructing rate expressions that treat elementary charge transfer, adsorption, and surface coverage, which enable interpretation of kinetic observables like apparent transfer coefficients, rate orders, and apparent activation energies that reflect properties of an interconnected reaction network. Mechanistic conclusions are strongest when competing hypotheses are tested against multiple complementary observables, including spectroscopy, isotopic labeling, and theory, enabling meaningful and reproducible mechanistic comparisons across laboratories.
ER -