Accelerating catalytic advancements through the precision of high-throughput experiments & calculations

Digital Discovery 2026 Open access

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Authors: Jenny G. Vitillo, Alán Aspuru‐Guzik, Eric Doskocil, Omar K. Farha, Timur İslamoğlu, Heather J. Kulik, Peter Margl, Stuart Miller, Jordan C. T. Reddel, Aayush R. Singh, Varinia Bernales
DOI: 10.1039/d5dd00524h
Cited by: 3
References: 81

Abstract

This Opinion article shows how integrated computational and experimental approaches accelerate catalyst development and highlights key challenges in data quality, model accuracy, and scalability across Technology Readiness Levels.

Fields of Study & Subjects

Catalysis and Oxidation Reactions Machine Learning in Materials Science CO2 Reduction Techniques and Catalysts

Publication details

Journal / source
Digital Discovery
Publisher
Royal Society of Chemistry (RSC)
Volume
5
Issue
2
Pages
497–509
Publication date
1 January 2026
Language
EN