Exploring the Influence of Applied Potential and Catalyst Morphology on the Selectivities of Copper Toward Carbon Dioxide Electroreduction Using Machine Learning

Electrochemical CO2 reduction (CO2RR) presents a sustainable approach to converting greenhouse gases into valuable chemicals. However, achieving precise product selectivity remains challenging. This study investigates the influence of applied potential and catalyst morphology on CO2RR selectivity us...

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Bibliografski detalji

Glavni autori:	Chengxi Yao, Mo Yan, Muhammad Asif, Ziyang Wang, Seungjae Lee, Joohwan Ha, Taesung Kim
Format:	Artigo
Jezik:	Inglês
Izdano:	Wiley 2025-11-01
Serija:	Advanced Intelligent Systems
Teme:	data‐driven electrochemical CO2 reduction machine learning selectivity SHapley Additive exPlanations
Online pristup:	https://doi.org/10.1002/aisy.202500311
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