Navigating challenges and opportunities of machine learning in hydrogen catalysis and production processes: Beyond algorithm development

• Main Authors: Salehmin M.N.I., Tiong S.K., Mohamed H., Umar D.A., Yu K.L., Ong H.C., Nomanbhay S., Lim S.S.
• Other Authors: 55628787200
• Format: Review
• Published: Elsevier B.V. 2025
• Subjects: Algorithms development; Catalyst synthesis; Computational modelling; Hydrogen Energy; Hydrogen energy, hydrogen production process; Hydrogen evolution reaction catalyst synthesis; Hydrogen evolution reactions; Hydrogen production process; Machine-learning; ]+ catalyst; Hydrogen evolution reaction

With the projected global surge in hydrogen demand, driven by increasing applications and the imperative for low-emission hydrogen, the integration of machine learning (ML) across the hydrogen energy value chain is a compelling avenue. This review uniquely focuses on harnessing the synergy between M...