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      Multiscale Modeling of Aqueous Electric Double Layers

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          Abstract

          From the stability of colloidal suspensions to the charging of electrodes, electric double layers play a pivotal role in aqueous systems. The interactions between interfaces, water molecules, ions and other solutes making up the electrical double layer span length scales from Ångströms to micrometers and are notoriously complex. Therefore, explaining experimental observations in terms of the double layer’s molecular structure has been a long-standing challenge in physical chemistry, yet recent advances in simulations techniques and computational power have led to tremendous progress. In particular, the past decades have seen the development of a multiscale theoretical framework based on the combination of quantum density functional theory, force-field based simulations and continuum theory. In this Review, we discuss these theoretical developments and make quantitative comparisons to experimental results from, among other techniques, sum-frequency generation, atomic-force microscopy, and electrokinetics. Starting from the vapor/water interface, we treat a range of qualitatively different types of surfaces, varying from soft to solid, from hydrophilic to hydrophobic, and from charged to uncharged.

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          Comparison of simple potential functions for simulating liquid water

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            Generalized neural-network representation of high-dimensional potential-energy surfaces.

            The accurate description of chemical processes often requires the use of computationally demanding methods like density-functional theory (DFT), making long simulations of large systems unfeasible. In this Letter we introduce a new kind of neural-network representation of DFT potential-energy surfaces, which provides the energy and forces as a function of all atomic positions in systems of arbitrary size and is several orders of magnitude faster than DFT. The high accuracy of the method is demonstrated for bulk silicon and compared with empirical potentials and DFT. The method is general and can be applied to all types of periodic and nonperiodic systems.
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              The missing term in effective pair potentials

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                Author and article information

                Journal
                Chem Rev
                Chem Rev
                cr
                chreay
                Chemical Reviews
                American Chemical Society
                0009-2665
                1520-6890
                20 December 2023
                10 January 2024
                : 124
                : 1
                : 1-26
                Affiliations
                []Fachbereich Physik, Freie Universität Berlin , 14195 Berlin, Germany
                []Laboratory of Computational Science and Modeling, IMX, École Polytechnique Fédérale de Lausanne , 1015 Lausanne, Switzerland
                [§ ]Institute of Theoretical Chemistry, Ulm University , 89081 Ulm, Germany
                []Department of Physics and Information Technology, Kyushu Institute of Technology , 820-8502 Iizuka, Japan
                []PRESTO, Japan Science and Technology Agency , 4-1-8 Honcho, Kawaguchi, Saitama 332-0012, Japan
                []Institute of Theoretical and Computational Physics, Graz University of Technology , 8010 Graz, Austria
                Author notes
                Author information
                https://orcid.org/0000-0002-6460-1556
                https://orcid.org/0000-0002-9112-0010
                https://orcid.org/0000-0003-2844-2313
                https://orcid.org/0000-0002-4970-4696
                https://orcid.org/0000-0002-1252-7745
                Article
                10.1021/acs.chemrev.3c00307
                10785765
                38118062
                bbb7490f-cc59-4348-bc9a-6767e519a9dc
                © 2023 The Authors. Published by American Chemical Society

                Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 07 May 2023
                : 30 November 2023
                : 17 November 2023
                Funding
                Funded by: Deutsche Forschungsgemeinschaft, doi 10.13039/501100001659;
                Award ID: IRTG-2662
                Funded by: Precursory Research for Embryonic Science and Technology, doi 10.13039/501100009023;
                Award ID: JPMJPR21O2
                Funded by: Max-Planck-Gesellschaft, doi 10.13039/501100004189;
                Award ID: NA
                Funded by: Deutsche Forschungsgemeinschaft, doi 10.13039/501100001659;
                Award ID: SFB1349
                Categories
                Review
                Custom metadata
                cr3c00307
                cr3c00307

                Chemistry
                Chemistry

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