Efficient and rapid preparation of high-performance porous reduced graphene films as HER/OER bifunctional electrocatalysts for overall water splitting

International Journal of Hydrogen Energy, Год журнала: 2025, Номер 120, С. 412 - 421

Опубликована: Март 28, 2025

Язык: Английский

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Machine Learning Optimized FeCoMn‐Trimetallic MOF‐Decorated Nanofibers for Enhanced OER Catalysis

Advanced Sustainable Systems, Год журнала: 2025, Номер unknown

Опубликована: Март 17, 2025

Abstract Despite significant advancements in noble metal‐free trimetallic MOF‐based electrocatalysts for efficient oxygen evolution reaction (OER), limited attention is given to identify which metal will play most role controlling OER performance. Thus, address this gap, herein ternary metallic (FeCoMn) squarate‐based MOF via a solvothermal approach synthesized. Additionally, machine learning (ML) algorithms are employed on experimental datasets during synthesis strategy optimize concentrations more swiftly and efficiently design highly squarate electrocatalysts. Interestingly, ML optimization has identified Fe as key element significantly influencing efficacy. To further boost efficacy, ML‐optimized FeCoMn drop‐casted onto conductive electrospun polycaprolactone (PC) nanofibers, facilitating smooth, uniform flow of ions electrons across the entire surface, maximizing exposed active sites, all anchored sponge‐like Ni foam (NF) substrate. Results reveal that FeCoMn/PC displays high electrocatalytic activity with lower overpotential (170 mV at current density 10 mA cm −2 ), Tafel slope 66.6.8 dec −1 , compared (overpotential 180 mV, 89.3 ). best knowledge, first time optimized FeCoMn/PC‐based electrocatalyst reported.

Язык: Английский

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Machine learning-optimized trimetallic MOF integrated nanofibers for precise detection of p-Nitrophenol in agricultural soil

Chemical Engineering Journal, Год журнала: 2025, Номер unknown, С. 161299 - 161299

Опубликована: Март 1, 2025

Язык: Английский

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Machine Learning-Guided Optimization of Bimetallic Oxide Nanostructures for Enhanced OER Electrocatalytic Activity

Energy & Fuels, Год журнала: 2025, Номер unknown

Опубликована: Март 15, 2025

Язык: Английский

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

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Март 28, 2025

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, determine which part plays a significant role in controlling OER efficacy remains very challenging. To address this issue, herein we employed machine learning (ML) for the first time element, thus leading development an optimized electrocatalyst. Briefly, designed novel, simple ML sustainable electrocatalyst on Co 3 O 4 /NiO popsicle sticks (CNPS) infused polyaniline/cellulose acetate (a biopolymer) (PNCA) electrospun nanofibers supported nickel foam (NF). CNPS PNCA (CNPS@PNCA) electrode offers maximum homogenous exposition active sites shows high activity by exhibiting low onset potential (1.41 V vs. RHE), overpotential (237 mV at 10 mA cm −2 ) Tafel slope 62.1 dec −1 . Additionally, it better stability more than 100 h is consistent with reported literature.

Язык: Английский

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Machine Learning-Optimized Overpotential in Zr-Doped CeO₂ Electrocatalysts for Enhanced OER Efficiency

Energy & Fuels, Год журнала: 2025, Номер unknown

Опубликована: Апрель 23, 2025

Язык: Английский

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Nanocube-structured ZnSn(OH)₆ for enhanced bifunctional electrocatalysis in oxygen evolution and urea oxidation reactions

Solid State Ionics, Год журнала: 2025, Номер 427, С. 116915 - 116915

Опубликована: Май 28, 2025

Язык: Английский

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