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March 3, 2026
Liquid amine-based CO2 capture: A review of absorbent systems innovation, multi-scenario applications, and machine learning-assisted optimization
JC
Jingwen Chang
Tsinghua University
KC
Kailun Chen
Tsinghua University
JL
Jinglin Li
Tsinghua University
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Key Points
CO2 capture innovations are essential for reducing greenhouse gas emissions, supporting climate change mitigation efforts.
Machine learning techniques improve the efficiency and effectiveness of absorbent systems in various applications.
Assessment across multiple scenarios reveals diverse applications of liquid amine-based CO2 capture methods.
Highlights need for collaboration among technology developers and researchers to optimize current systems.
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Chang et al. (Fri,) studied this question.
synapsesocial.com/papers/69a75f53c6e9836116a2a9e0
https://doi.org/https://doi.org/10.1016/j.rser.2026.116754
Liquid amine-based CO2 capture: A review of absorbent systems innovation, multi-scenario applications, and machine learning-assisted optimization | Synapse