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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Hauptverfasser: Chengxi Yao, Mo Yan, Muhammad Asif, Ziyang Wang, Seungjae Lee, Joohwan Ha, Taesung Kim
Format: Artigo
Sprache:Inglês
Veröffentlicht: Wiley 2025-11-01
Schriftenreihe:Advanced Intelligent Systems
Schlagworte:
data‐driven
electrochemical CO2 reduction
machine learning
selectivity
SHapley Additive exPlanations
Online Zugang:https://doi.org/10.1002/aisy.202500311
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