{"license":"https://creativecommons.org/licenses/by/4.0/","type":"journal_article","has_accepted_license":"1","status":"public","project":[{"_id":"9106a876-16d5-11f0-9cad-bbf11c9952f9","name":"Quantitative Unbiased Shape Analysis with Geometry &amp; Topology","grant_number":"ESP 9584724"}],"fulldoi":"https://doi.org/10.1038/s41467-026-77363-w","pmid":1,"date_updated":"2026-10-12T09:03:58Z","day":"30","scopus_import":"1","ddc":["500"],"acknowledgement":"We thank the Danish e-Infrastructure Cooperation (DeiC) for access to computational resources at Sophia and LUMI-C (DeiC-AAU-N5-202200005). This work was supported by the Independent Research Fund Denmark (1026-00037), European Union (ERC, NewGLASS, 101044664), and Danish Data Science Academy, which in turn is funded by the Novo Nordisk Foundation (NNF21SA0069429) and VILLUM FONDEN (40516). Y.B.B. acknowledges support from the Austrian Science Fund (FWF) 10.55776/ESP9584724.","researchdata_availability":"yes","OA_type":"gold","quality_controlled":"1","PlanS_conform":"1","file":[{"success":1,"file_size":1889857,"date_created":"2026-10-12T09:00:06Z","access_level":"open_access","file_id":"23104","checksum":"eba760f5982a89f59664957e00c5d2d6","date_updated":"2026-10-12T09:00:06Z","content_type":"application/pdf","relation":"main_file","file_name":"2026_NatureComm_Pegoraro.pdf","creator":"dernst"}],"year":"2026","department":[{"_id":"HeEd"}],"dataavailabilitystatement":"All data supporting the findings of this study are available within the article and Supplementary Information files. Source data are provided with this paper. The developed code to perform the max-flow calculations is available as part of the Topological Materials Analysis (ToMA) library, which is available at Zenodo (https://doi.org/10.5281/zenodo.10781424) and Github (https://github.com/yossibokorbleile/TopologicalMaterialAnalysis), with documentation available at https://yossi.eu/toma/. To enhance usability, we have included a brief documentation on how to compile ToMA as well as a minimal working example of the code together with an example trajectory directly in the ToMA repository. LAMMPS is an open-source code available at https://lammps.sandia.gov.","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"month":"09","volume":17,"date_published":"2026-09-30T00:00:00Z","OA_place":"publisher","das_tickbox":"1","oa":1,"supplementarymaterial":"yes","_id":"23087","publisher":"Springer Nature","article_type":"original","title":"Predicting ionic conductivity of sulfide glass solid-state electrolytes using max-flow methodology","author":[{"last_name":"Pegoraro","full_name":"Pegoraro, Matteo","first_name":"Matteo"},{"full_name":"Christensen, Rasmus","first_name":"Rasmus","last_name":"Christensen"},{"full_name":"Sørensen, Søren S.","first_name":"Søren S.","last_name":"Sørensen"},{"last_name":"Lindbjerg","first_name":"Anders R.","full_name":"Lindbjerg, Anders R."},{"last_name":"Du","first_name":"Tao","full_name":"Du, Tao"},{"id":"920a7385-7995-11ef-9bfd-8c434cd8f3c2","orcid":"0000-0002-4861-9174","first_name":"Yossi","full_name":"Bleile, Yossi","last_name":"Bleile"},{"last_name":"Svane","full_name":"Svane, Anne Marie","first_name":"Anne Marie"},{"last_name":"Biscio","full_name":"Biscio, Christophe A.N.","first_name":"Christophe A.N."},{"first_name":"Lisbeth","full_name":"Fajstrup, Lisbeth","last_name":"Fajstrup"},{"first_name":"Morten M.","full_name":"Smedskjaer, Morten M.","last_name":"Smedskjaer"}],"abstract":[{"text":"Disordered materials such as glasses are promising candidates as solid-state electrolytes for batteries, but they tend to exhibit low ionic conductivity and current methods for investigating and predicting the ionic conductivity of electrolyte materials are inefficient. Here, we propose a framework that summarizes the topological properties of the electrolyte material’s atomic structure with a weighted graph based on periodic boundary conditions. We then compute a variation of the max-flow algorithm, a commonly used model in continuum models of transportation and liquid flow, on this summary and show that it is compatible with the simulated periodic atomic structures. Using molecular dynamics simulations of various glassy solid-state electrolyte families including both mobile lithium and sodium ions, we validate the approach by showing a positive correlation between the area-normalized maximum flow predicted from the static glass structures and the ionic conductivity as obtained from the simulations, especially in the case of high-conductivity sulfide glass electrolytes. We envision that the developed methodology, which only relies on static atomic structure, will accelerate the discovery of highly conductive sulfide glassy electrolytes for high-performance all-solid-state batteries.","lang":"eng"}],"external_id":{"pmid":["42811056"]},"article_number":"10343","file_date_updated":"2026-10-12T09:00:06Z","oa_version":"Published Version","publication_identifier":{"eissn":["2041-1723"]},"date_created":"2026-10-11T22:02:03Z","article_processing_charge":"Yes","doi":"10.1038/s41467-026-77363-w","publication_status":"published","citation":{"ieee":"M. Pegoraro <i>et al.</i>, “Predicting ionic conductivity of sulfide glass solid-state electrolytes using max-flow methodology,” <i>Nature Communications</i>, vol. 17. Springer Nature, 2026.","chicago":"Pegoraro, Matteo, Rasmus Christensen, Søren S. Sørensen, Anders R. Lindbjerg, Tao Du, Yossi Bokor Bleile, Anne Marie Svane, Christophe A.N. Biscio, Lisbeth Fajstrup, and Morten M. Smedskjaer. “Predicting Ionic Conductivity of Sulfide Glass Solid-State Electrolytes Using Max-Flow Methodology.” <i>Nature Communications</i>. Springer Nature, 2026. <a href=\"https://doi.org/10.1038/s41467-026-77363-w\">https://doi.org/10.1038/s41467-026-77363-w</a>.","ista":"Pegoraro M, Christensen R, Sørensen SS, Lindbjerg AR, Du T, Bokor Bleile Y, Svane AM, Biscio CAN, Fajstrup L, Smedskjaer MM. 2026. Predicting ionic conductivity of sulfide glass solid-state electrolytes using max-flow methodology. Nature Communications. 17, 10343.","ama":"Pegoraro M, Christensen R, Sørensen SS, et al. Predicting ionic conductivity of sulfide glass solid-state electrolytes using max-flow methodology. <i>Nature Communications</i>. 2026;17. doi:<a href=\"https://doi.org/10.1038/s41467-026-77363-w\">10.1038/s41467-026-77363-w</a>","short":"M. Pegoraro, R. Christensen, S.S. Sørensen, A.R. Lindbjerg, T. Du, Y. Bokor Bleile, A.M. Svane, C.A.N. Biscio, L. Fajstrup, M.M. Smedskjaer, Nature Communications 17 (2026).","apa":"Pegoraro, M., Christensen, R., Sørensen, S. S., Lindbjerg, A. R., Du, T., Bokor Bleile, Y., … Smedskjaer, M. M. (2026). Predicting ionic conductivity of sulfide glass solid-state electrolytes using max-flow methodology. <i>Nature Communications</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41467-026-77363-w\">https://doi.org/10.1038/s41467-026-77363-w</a>","mla":"Pegoraro, Matteo, et al. “Predicting Ionic Conductivity of Sulfide Glass Solid-State Electrolytes Using Max-Flow Methodology.” <i>Nature Communications</i>, vol. 17, 10343, Springer Nature, 2026, doi:<a href=\"https://doi.org/10.1038/s41467-026-77363-w\">10.1038/s41467-026-77363-w</a>."},"intvolume":"        17","publication":"Nature Communications","DOAJ_listed":"1","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","language":[{"iso":"eng"}]}