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Decoding linker contributions in solid state synthesis of MOF-derived NiCo2O4/NiO/C composites for efficient electrocatalytic OER: Machine learning assisted prediction and forecasting of device stability

Sagar A. Chaudhari, Santosh S. Sutar, Parth S. Thorat, Vinod V. Patil, Vishal A. Jadhav, Umakant M. Patil, Hyun‐Kyung Kim, Vaishali Patil, Mohaseen S. Tamboli, Sadaf Jamal Gilani, Nguyen Tam Nguyen Truong, Dattakumar Mhamane, Rajkumar Patel, Mukund G. Mali

2025Journal of the Taiwan Institute of Chemical Engineers6 citationsDOI

Topics & Concepts

OverpotentialOxygen evolutionWater splittingMaterials scienceComposite numberElectrolysisElectrolysis of waterChemical engineeringElectrocatalystPyrolysisCarbon fibersComputer scienceRenewable energyProcess engineeringNanotechnologyComposite materialNon-blocking I/OGreenhouse gasElectrolytic cellMechanical engineeringElectrolyteStability (learning theory)Machine Learning in Materials ScienceGas Sensing Nanomaterials and SensorsElectrocatalysts for Energy Conversion
Decoding linker contributions in solid state synthesis of MOF-derived NiCo2O4/NiO/C composites for efficient electrocatalytic OER: Machine learning assisted prediction and forecasting of device stability | Litcius