Machine learning-driven optimization of Deep Eutectic Solvents: Accelerating physicochemical properties modeling

doi:10.1016/j.susmat.2025.e01536

Machine learning-driven optimization of Deep Eutectic Solvents: Accelerating physicochemical properties modeling

2025-07-12

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DOI：10.1016/j.susmat.2025.e01536

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• Machine Learning-Driven DES Optimization for the development of green solvents. • Data-Driven Predictive Modeling that enables accurate physicochemical properties and reduced trial-and-error methods. • Process Optimization for real-time solvent customization, reducing waste generation and energy consumption. • Future Perspectives encompass advancements in pollutant remediation and green chemical processes.

Machine learning-driven optimization of Deep Eutectic Solvents: Accelerating physicochemical properties modeling

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