From Characterization to Discovery: Artificial Intelligence, Machine Learning and High-Throughput Experiments for Heterogeneous Catalyst Design
Jorge Benavides-Hernández,
Franck Dumeignil
Abstract:This review paper delves into synergistic integration of artificial intelligence (AI) and machine learning (ML) with highthroughput experimentation (HTE) in the field of heterogeneous catalysis, presenting a broad spectrum of contemporary methodologies and innovations. We methodically segmented the text into three core areas: catalyst characterization, data-driven exploitation, and data-driven discovery. In the catalyst characterization part, we outline current and prospective techniques used for HTE and how A… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.