Modelling proton transfer in [HEIM][TFSI] ionic liquid

dc.contributor.affiliationUniversidade de Santiago de Compostela. Departamento de Física de Partículas
dc.contributor.affiliationUniversidade de Santiago de Compostela. Instituto de Materiais (iMATUS)
dc.contributor.authorOtero Lema, Martín
dc.contributor.authorGoloviznina, Kateryna
dc.contributor.authorVarela Cabo, Luis Miguel
dc.contributor.authorSalanne, Mathieu
dc.contributor.authorMontes-Campos, Hadrián
dc.contributor.authorServa, Alessandra
dc.date.accessioned2025-10-22T07:20:53Z
dc.date.available2025-10-22T07:20:53Z
dc.date.issued2025-08-15
dc.description.abstractProtic ionic liquids, PILs, are promising materials for energy storage applications, in part due to their ability to decouple proton transport from ion diffusion. In this work, we model the proton transfer mechanism in 1-ethylimidazolium bis(trifluoromethanesulfonyl)imide ([HEIM][TFSI]) IL by means of Neural Network Force Field simulations. The latter are combined with classical polarizable molecular dynamics simulations to explore the structure and dynamics of the fully ionized system and Density Functional Theory calculations to estimate the energy barriers for the different proton transfer reactions. Our results show that proton transfer is indeed possible when doping the ionic liquid with an excess of deprotonated cations, but not with an excess of protonated anions. We highlight the importance of the formation of dimers between donor and acceptor species for the reaction to occur, and we identify the main driving factor for the reaction to be the energy cost for reaching a suitable coordination environment and form such dimers, which is higher than that for the transfer reaction.
dc.description.peerreviewedSI
dc.description.sponsorshipThe financial support of the Spanish Ministry of Science and Innovation (PID2021-126148NA- I00 funded by MICIU/AEI/10.13039/501100011033/FEDER, UE) is gratefully acknowledged. This work was funded by the Xunta de Galicia (GRC ED431C 2024/06). M. O. L. thanks the Xunta de Galicia for his “Axudas de apoio á etapa predoutoral” grant (ED481A 2022/236). This work was done within the framework of project HI_MOV – “Corredor Tecnológico Transfronterizo de Movilidad con Hidrógeno Renovable”, with reference 0160_HI_MOV_1_E, co-financed by the European Regional Development fund (ERDF), in the scope of Interreg VI A Spain – Portugal Cooperation Program (POCTEP) 2021–2027. This work is part of the project CNS2023-144785, funded by MICIU/AEI/10.13039/501100011033 and the European Union “NextGenerationEU”/PRTR. H. M. C. thanks the USC for his “Convocatoria de Recualificación do Sistema Universitario Español-Margarita Salas” postdoctoral grant under the “Plan de Recuperación Transformación” program funded by the Spanish Ministry of Universities with European Union's NextGenerationEU funds. The authors acknowledge HPC resources granted by GENCI, France (resources of IDRIS, Grant No. 2023-A0140910463).
dc.identifier.citationMaterials Today Energy Volume 53, October 2025, 102018
dc.identifier.doi10.1016/j.mtener.2025.102018
dc.identifier.urihttps://hdl.handle.net/10347/43334
dc.journal.titleMaterials Today Energy
dc.language.isoeng
dc.publisherElsevier
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-126148NA-I00/ES/
dc.relation.publisherversionhttps://doi.org/10.1016/j.mtener.2025.102018
dc.rights© 2025 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license. Attribution 4.0 International
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectProton transfer
dc.subjectProtic ionic liquids
dc.subjectMolecular dynamics
dc.subjectNeural network force field
dc.subjectPolarizable force field
dc.titleModelling proton transfer in [HEIM][TFSI] ionic liquid
dc.typejournal article
dc.type.hasVersionVoR
dc.volume.number53
dspace.entity.typePublication
relation.isAuthorOfPublication137dedc2-ea57-4cd6-b5bc-94b55d9d8b98
relation.isAuthorOfPublication78f7e837-a983-40db-89f2-5363070f31bc
relation.isAuthorOfPublication.latestForDiscovery137dedc2-ea57-4cd6-b5bc-94b55d9d8b98

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