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Machine learning application in thermal CO2 hydrogenation: catalyst design, process optimization, and mechanism insights

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Experimental and Theoretical Factors in CO2 Reduction on Pd‐Based Electrocatalysts and their Applicability for Integration with Data Science and High‐Throughput Experiments

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Atomic Ordering-Induced Ensemble Variation in Alloys Governs Electrocatalyst On/Off States

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Interpretable machine learning unravels synergistic effects in photothermal CO2 methanation

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Descriptors of Electrocatalysis for CO2 Reduction to C2+ Products Formation

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In-situ characterization technologies and theoretical calculations in carbon dioxide reduction: In-depth understanding of reaction mechanisms and rational design of electrocatalysts

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Commercialization path of data-driven green catalytic technology: the application of machine learning in technology lifecycle management

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Deep Learning for Computational Heterogeneous Catalysis: Fundamentals and Applications

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Analyzing the Active Site and Predicting the Overall Activity of Alloy Catalysts

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Advancing CO2RR with O-Coordinated Single-Atom Nanozymes: A DFT and Machine Learning Exploration

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The Synergistic Effect between Metal and Sulfur Vacancy to Boost CO2 Reduction Efficiency: A Study on Descriptor Transferability and Activity Prediction

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Electrochemical CO2 reduction to liquid fuels: Mechanistic pathways and surface/interface engineering of catalysts and electrolytes

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