RT info:eu-repo/semantics/article
T1 Insights on the adsorption mechanism of different polyvinylpyrrolidone (PVP)-based battery binders on 2D-materials for LiPF6-Ec-Emc electrolyte via molecular simulations
A1 Wu, Qingliu
A1 Pekarovicova, Alexandra
A1 Aparicio Martínez, Santiago
A1 Gutiérrez Vega, Alberto
A1 Atilhan, Mert
K1 Computational modeling techniques
K1 Adsorption
K1 Binders
K1 2D-related nanomaterials
K1 LiPF6-EC-EMC electrolyte
K1 Adsorción
K1 Adsorption
AB In this study, the adsorption mechanism of different mixtures of monomers of polyvinylpyrrolidone (PVP)-based battery binders (polyvinylpyrrolidone:polyvinylidene difluoride, PVP:PVDF; polyvinylpyrrolidone:polyacrylic acid, PVP:PAA; and polyvinylpyrrolidone:lithiated polyacrylic acid, PVP:Li-PAA) on a graphene oxide (GO) nanoparticle was investigated using density functional theory (DFT), quantum theory of atoms in molecules (QTAIM) and molecular dynamics (MD) simulations in order to identify the thermodynamic, intermolecular forces and interfacial properties of these systems within the framework of battery applications employing LiPF6-EC-EMC electrolyte. Our work focuses into the short-range interactions and electronic properties of the adsorbed binder mixtures on the GO nanoparticle, and also into their interfacial properties (considering systems with and without the electrolyte, 1.2 M LiPF6 dissolved in EC/EMC 3/7, w/w), shedding light on the fundamental interactions that govern the mechanisms of GO (and also another 2D-nanomaterial such as graphite, for reference) enabling the physical adsorption of binders (and electrolyte compounds) for obtaining strongly adhered anode and cathode active substances in Li-ion battery applications. The results of this study advance the understanding of the adsorption mechanisms of binder mixtures and electrolyte compounds on carbon-based nanomaterials, and hold significant promise for the designing battery-optimized energy devices in lithium-ion batteries.
PB Elsevier
SN 0378-7753
YR 2024
FD 2024-11
LK https://hdl.handle.net/10259/12039
UL https://hdl.handle.net/10259/12039
LA eng
NO This research is based upon work supported by the U.S. Department of Energy's Office on Energy Efficiency and Renewable Energy, EERE) under the Advanced Manufacturing Office, award number DE-EE0009111. We also acknowledge European Union NextGenerationEU/PRTR funds. This study was also supported through computational resources and services provided by the Institute for Cyber-Enabled Research at Michigan State University. The statements made herein are solely the responsibility of the authors.
DS Repositorio Institucional de la Universidad de Burgos
RD 03-oct-2026