Size-Dependent Graphene Support for Decorating Gold Nanoparticles as a Catalyst for Hydrogen Evolution Reaction with Machine Learning-Assisted Prediction

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dc.contributor.authorBoontarika Saeloo
dc.contributor.authorKulpavee Jitapunkul
dc.contributor.authorPawin Iamprasertkun
dc.contributor.authorGasidit Panomsuwan
dc.contributor.authorWeekit Sirisaksoontorn
dc.contributor.authorTawan Sooknoi
dc.contributor.authorWisit Hirunpinyopas
dc.date.accessioned2026-05-08T19:16:02Z
dc.date.issued2023-11-2
dc.description.abstractGP/AuNPs electrode surface also play crucial roles in enhancing electrolytes for penetration in the electrode, suggesting a highly electrochemical surface area. Moreover, machine learning (Random Forest) was also used to reveal the essential features of the advanced catalytic material design for catalyst-based applications.
dc.identifier.doi10.1021/acsami.3c10553
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/15301
dc.publisherACS Applied Materials & Interfaces
dc.subjectElectrocatalysts for Energy Conversion
dc.subjectGraphene research and applications
dc.subjectAdvancements in Battery Materials
dc.titleSize-Dependent Graphene Support for Decorating Gold Nanoparticles as a Catalyst for Hydrogen Evolution Reaction with Machine Learning-Assisted Prediction
dc.typeArticle

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