Overview highlights the evolution of nonaqueous solvents in chemistry, suggesting new functional applications for sustainable practices.
Nonaqueous solvents have become versatile media in modern chemistry, offering tunable properties, sustainable processing, and access to reactivities challenging in water.Recent advances in the development and synthesis of classical and molecular solvents from renewable resources, particularly driven by sustainability considerations, have significantly expanded their range of applications.These developments can be rationalized within a unified framework based on how solvent structure and dynamics govern mesoscale organization and function.Structurally programmable solvents, such as ionic liquids and deep eutectic solvents, provide tailored solvation landscapes through specific intermolecular interactions, enabling selective extraction, catalysis, and molecular recognition.Stimuliresponsive systems introduce dynamic control, where external triggers (e.g., temperature, pH, CO 2 ) modulate phase behavior, polarity, and interfacial properties, thereby coupling reaction and separation processes.Self-organizing and transient solvent systems, including microemulsions, nanostructured domains, and ephemeral solvents, generate compartmentalized environments that mimic soft-matter systems and allow spatial and temporal control over reactions.Finally, bioinspired and hybrid solvents, such as NADES (Natural Deep Eutectic Solvents) and CO 2 -based mixtures, integrate multiple functionalities and enable the stabilization of complex biomolecules alongside efficient processing routes.Across these categories, a common paradigm emerges: solvent systems are no longer passive media but actively engineered components of chemical processes.Their ability to integrate functionality, responsiveness, and sustainability highlights their central role in advancing modern chemistry.In this context, environmental impact will remain a key criterion in the future development of next-generation solvents, complementing classical performance metrics.
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Müller et al. (2026) studied this question.
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