Machine learning assisted Co₃O₄/NiO popsicle sticks-infused electrospun nanofibers for efficient oxygen evolution reaction.

ABSTRACT: Wide range of noble metal free bimetallic and trimetallic based electrocatalysts have been synthesized to develop efficient oxygen evolution reaction (OER) systems to-date, however, to determine which metal part of bimetallic and trimetallic electrocatalysts plays a significant role in controlling OER efficacy remains very challenging. To address this issue, herein we have employed machine learning (ML) for the first time to determine OER efficacy controlling metal element, thus leading to the development of an optimized bimetallic electrocatalyst. Briefly, we have designed a novel, simple ML optimized sustainable OER electrocatalyst based on Co₃O₄/NiO popsicle sticks (CNPS) infused polyaniline/cellulose acetate (a biopolymer) (PNCA) electrospun nanofibers supported o

SUBMITTER: Al-Ghamdi AA 

PROVIDER: S-EPMC11950386 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature