ReviewInternational journal of molecular sciences2026
Solubilizing Nonpolar Substances in Polar Solvents: Strategies, Molecular Mechanisms, and Applications.
Review in International journal of molecular sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Efficient solubilization of nonpolar substances in polar solvents represents a fundamental challenge in environmental remediation, green chemistry, and separation processes. This limitation stems from the hydrophobic effect, which creates thermodynamic barriers, resulting in low intrinsic solubility and strong phase separation. This review examines the thermodynamic basis of solubilization, focusing on free-energy changes and molecular interaction mechanisms. It discusses various strategies, including surface and interface engineering, host-guest inclusion, solvent engineering, and nanostructure encapsulation, along with their practical applications. Future research directions include smart responsive materials, green solvent design theories, and precise construction of solubilization systems through multi-scale simulations.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.