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Exploring Challenging C2+ Products During CO2 Reduction via Machine Learning Acceleration (Adv. Energy Mater. 16/2025)
Advanced Energy Materials, Volume 15, Issue 16, April 22, 2025.
CO2 Reduction
In article number 2500177, Mingzi Sun and Bolong Huang have applied the first-principles machine learning method to unravel the reaction mechanisms of challenging C2+ products during the CO2 reduction reaction on graphdiyne-supported atomic catalysts, which supply insights into improving the selectivity of designed catalysts.
