Dataset for: Descriptor-Guided Isolated-Site Engineering Activates Layered V2O5 for Oxygen Evolution Catalysis

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Authors: Byoung Guan Lee, Monaam Benali, Min Kyu Choi, Jan Luxa, Vojtěch Kundrát, Jakub Zálešák, Ľubica Cenknerová, Yeongnam Ko, Zdeněk Sofer, Rui Gusmão, Ki Chul Kim
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Abstract

This dataset contains raw and processed computational and experimental data supporting descriptor-guided isolated-site engineering of transition-metal-incorporated layered V2O5 for oxygen evolution reaction electrocatalysis. The dataset includes density-functional-theory structural optimization, adsorption thermodynamics, charge-density redistribution, and theoretical overpotential analysis for transition-metal-embedded V2O5 monolayers, together with hydrothermal synthesis, structural and compositional characterization, microscopy, and electrochemical performance evaluation of pristine and transition-metal-modified V2O5 catalysts in alkaline electrolyte.

Fields of Study & Subjects

Electrocatalysts for Energy Conversion Supercapacitor Materials and Fabrication Machine Learning in Materials Science

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
2 February 2026
Language
EN
Document type
Dataset