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      Correlating the 3D Morphology of Polymer-Based Battery Electrodes with Effective Transport Properties

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          Abstract

          Polymer-based batteries represent a promising candidate for next-generation batteries due to their high power densities, decent cyclability, and environmentally friendly synthesis. However, their performance essentially depends on the complex multiscale morphology of their electrodes, which can significantly affect the transport of ions and electrons within the electrode structure. In this paper, we present a comprehensive investigation of the complex relationship between the three-dimensional (3D) morphology of polymer-based battery electrodes and their effective transport properties. In particular, focused ion beam scanning electron microscopy (FIB-SEM) is used to characterize the 3D morphology of three polymer-based electrodes which differ in material composition. The subsequent segmentation of FIB-SEM image data into active material, carbon-binder domain and pore space enables a comprehensive statistical analysis of the electrode structure and a quantitative morphological comparison of the electrode samples. Moreover, spatially resolved numerical simulations allow for computing effective properties of ionic and electronic transport. The obtained results are used for establishing analytical regression formulas which describe quantitative relationships between the 3D morphology of the electrodes and their effective transport properties. To the best of our knowledge, this is the first time that the 3D structure of polymer-based battery electrodes is quantitatively investigated at the nanometer scale.

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                Author and article information

                Journal
                ACS Appl Mater Interfaces
                ACS Appl Mater Interfaces
                am
                aamick
                ACS Applied Materials & Interfaces
                American Chemical Society
                1944-8244
                1944-8252
                21 November 2024
                04 December 2024
                : 16
                : 48
                : 66571-66583
                Affiliations
                [1 ]Institute of Stochastics, Ulm University , 89069 Ulm, Germany
                [2 ]Institute of Modelling and Computational Science, Applied Mathematics, Helmut-Schmidt-Universität/Universität der Bundeswehr Hamburg , 22043 Hamburg, Germany
                [3 ]Institute of Applied Materials, Helmholtz-Zentrum Berlin für Materialien und Energie , 14109 Berlin, Germany
                [4 ]Laboratory of Organic and Macromolecular Chemistry (IOMC), Friedrich Schiller University Jena , 07743 Jena, Germany
                [5 ]Center for Energy and Environmental Chemistry (CEEC), Friedrich Schiller University Jena , 07743 Jena, Germany
                [6 ]Helmholtz Institute for Polymers in Energy Applications Jena (HIPOLE Jena) , 07743 Jena, Germany
                Author notes
                Author information
                https://orcid.org/0000-0002-2952-0208
                https://orcid.org/0000-0001-5861-0483
                https://orcid.org/0000-0002-6373-6600
                https://orcid.org/0000-0003-4978-4670
                https://orcid.org/0000-0001-9795-5345
                Article
                10.1021/acsami.4c17522
                11622701
                39569633
                3bd869ec-13e4-412e-8d08-95d4e1ad83a6
                © 2024 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
                : 11 October 2024
                : 18 November 2024
                : 15 November 2024
                Funding
                Funded by: Deutsche Forschungsgemeinschaft, doi 10.13039/501100001659;
                Award ID: CA 633/4-1
                Funded by: Deutsche Forschungsgemeinschaft, doi 10.13039/501100001659;
                Award ID: SCHU 1229/54-1
                Funded by: Deutsche Forschungsgemeinschaft, doi 10.13039/501100001659;
                Award ID: SCHM 997/39-1
                Funded by: Deutsche Forschungsgemeinschaft, doi 10.13039/501100001659;
                Award ID: MA 5039/7-1
                Categories
                Research Article
                Custom metadata
                am4c17522
                am4c17522

                Materials technology
                polymer-based battery,electrode,fib-sem tomography,nanostructure,statistical image analysis,effective charge transport,structure−property relationship

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