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      Like dissolves like: A first-principles theory for predicting liquid miscibility and mixture dielectric constant

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          Abstract

          The empirical “like-dissolves-like” rule for liquid miscibility can be quantified.

          Abstract

          Liquid mixtures are ubiquitous. Miscibility and dielectric constant are fundamental properties that govern the applications of liquid mixtures. However, despite their importance, miscibility is usually predicted qualitatively based on the vaguely defined polarity of the liquids, and the dielectric constant of the mixture is modeled by introducing mixing rules. Here, we develop a first-principles theory for polar liquid mixtures using a statistical field approach, without resorting to mixing rules. With this theory, we obtain simple expressions for the mixture’s dielectric constant and free energy of mixing. The dielectric constant predicted by this theory agrees well with measured data for simple binary mixtures. On the basis of the derived free energy of mixing, we can construct a miscibility map in the parameter space of the dielectric constant and molar volume for each liquid. The predicted miscibility shows remarkable agreement with known data, thus providing a quantitative basis for the empirical “like-dissolves-like” rule.

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          Self-healing polymers

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            Quantitative relations between interaction parameter, miscibility and function in organic solar cells

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              Dielectric constants of heterogeneous mixtures

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                Author and article information

                Journal
                Sci Adv
                Sci Adv
                SciAdv
                advances
                Science Advances
                American Association for the Advancement of Science
                2375-2548
                February 2021
                12 February 2021
                : 7
                : 7
                : eabe7275
                Affiliations
                [1 ]Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA.
                [2 ]Yale-NUS College, Singapore 138527, Singapore.
                [3 ]Institute of High Performance Computing, Singapore 138632, Singapore.
                Author notes
                [* ]Corresponding author. Email: zhuang.bilin@ 123456yale-nus.edu.sg (B.Z.); zgw@ 123456caltech.edu (Z.-G.W.)
                Author information
                http://orcid.org/0000-0003-2934-4264
                http://orcid.org/0000-0002-3361-6114
                Article
                abe7275
                10.1126/sciadv.abe7275
                7880597
                33579702
                bfd3373c-2672-4423-a46a-24a712ec3121
                Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).

                This is an open-access article distributed under the terms of the Creative Commons Attribution license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 11 September 2020
                : 24 December 2020
                Funding
                Funded by: doi http://dx.doi.org/10.13039/100006770, American Chemical Society Petroleum Research Fund;
                Award ID: 53404-ND5
                Funded by: doi http://dx.doi.org/10.13039/100012693, Yale-NUS College;
                Award ID: Start-up grant
                Funded by: doi http://dx.doi.org/10.13039/100012693, Yale-NUS College;
                Award ID: Summer Research Program
                Funded by: doi http://dx.doi.org/10.13039/100012693, Yale-NUS College;
                Award ID: Summer Reseach Program
                Categories
                Research Article
                Research Articles
                SciAdv r-articles
                Chemistry
                Physics
                Chemistry
                Custom metadata
                Lou Notario

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