Reaching machine learning leverage to advance performance of electrocatalytic CO2 conversion in non-aqueous deep eutectic electrolytes

Reaching machine learning leverage to advance performance of electrocatalytic CO2 conversion in non-aqueous deep eutectic electrolytes

Abstract Deep eutectic electrolytes (DEEs) show promise for future electrochemical systems due to their adjustable buffer capacities. This study utilizes machine learning algorithms to analyse the carbon dioxide reduction reaction (CO2RR) in DEEs with a buffer capacity of approximately 10.21 mol/pH....

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Bibliographic Details
Main Authors: Ahmed Halilu, Mohamed Kamel Hadj-Kali, Hanee Farzana Hizaddin, Mohd Ali Hashim, Emad M. Ali, Suresh Bhargava
Format: Article
Language:English
Published: Nature Portfolio 2024-10-01
Series:Scientific Reports
Subjects:
Deep eutectic electrolytes
CO2 capture and utilization
Machine learning
Artificial Intelligence
Electrocatalysis
Reaction Engineering
Online Access:https://doi.org/10.1038/s41598-024-74893-5

Internet

https://doi.org/10.1038/s41598-024-74893-5

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