Deciphering conductivity in PEDOT guided by machine learning: From solvent baths to charge pathsShow others and affiliations
2025 (English)In: Physical Review Materials, E-ISSN 2475-9953, Vol. 9, no 10.0Article in journal (Refereed) Published
Abstract [en]
PEDOT:Tos is a promising conducting polymer for electronic and bioelectronic applications, yet its charge transport is affected by various factors and remains challenging to optimize. This study investigates the impact of solvent posttreatment on PEDOT:Tos thin films, exploring its influence on morphology and electrical conductivity. A combined experimental-theoretical approach is employed, integrating molecular dynamics, density functional theory, and transport calculations on one hand and conductivity, GIWAXS and XPS measurements on the other hand. Moreover, we developed a machine learning (ML) framework based on convolutional neural networks with the Coulomb matrix as the predictor, and transfer integrals for multiscale transport calculations as targets. Our results reveal that solvent-induced morphological changes strongly affect charge transport, with the ML model effectively reproducing observed conductivity. The developed ML model dramatically boosts the speed of mobility calculations, enabling the analysis of large-scale polymer films that were previously beyond computational reach
Place, publisher, year, edition, pages
American Physical Society, 2025. Vol. 9, no 10.0
National Category
Condensed Matter Physics
Identifiers
URN: urn:nbn:se:ri:diva-79964DOI: 10.1103/5h7d-yvsdScopus ID: 2-s2.0-105022977506OAI: oai:DiVA.org:ri-79964DiVA, id: diva2:2020485
Note
The ESRF and the NWO are acknowledged for allocating beam time at the Dutch-Belgian beamline (DUBBLE, ESRF, Grenoble) for the GIWAXS experiments. I.Z. and N.Z. acknowledge the support from the European Commission through the Marie Sk\u0142odowska\u2013Curie projects HORATES (Grant No. GA-955837). I.Z. acknowledges support from Swedish Government Strategic Research Area in Materials Science on Advanced Functional Materials at Link\u00F6ping University (Faculty Grant SFO-Mat-LiU No. 2009\u201300971), and Swedish Research Council (2024\u201304449). The computations were performed on resources provided by the National Academic Infrastructure for Supercomputing in Sweden (NAISS) at NSC. I.P. acknowledges the support from the funding from Sweden's Innovation Agency, Vinnova, DEvelopment of TRAnsparent CONductors for transparent photovoltaic cells. \u201CDETRACON\u201D, Diary No.: 2024\u201300598.
2025-12-102025-12-102025-12-10Bibliographically approved