RT info:eu-repo/semantics/article
T1 Molecular layering and CO₂ selectivity in graphene-supported natural deep eutectic solvent films: An in-silico investigation
A1 Rozas Azcona, Sara
A1 Aguilar Cuesta, Nuria
A1 Marcos Villa, Pedro A.
A1 Bol Arreba, Alfredo
A1 Aparicio Martínez, Santiago
K1 CO2 capture
K1 Flue gas
K1 Deep eutectic solvents
K1 Thin films
K1 Graphene
K1 Quantum chemistry
K1 Molecular dynamics
K1 Química cuántica
K1 Quantum chemistry
AB A multiscale computational study was conducted to investigate graphene-supported thin films composed of anatural deep eutectic solvent (NADES) formed by menthol and decanoic acid (MENTH:DA), with a focus onapplications in sustainable CO₂ capture. Density functional theory (DFT) and molecular dynamics (MD) simulations were employed to elucidate interfacial structuring, molecular interactions, and gas adsorption behavior.DFT results indicated a strong interaction between decanoic acid and the graphene surface (− 35.88 kJ/mol),characterized by a parallel orientation that maximizes van der Waals interactions. In contrast, menthol displayedweaker adsorption energies (− 5.15 kJ/mol) and a predominantly perpendicular orientation. MD simulationsrevealed the formation of distinct adsorption layers, with decanoic acid enriched in the first layer and menthol inthe second, while the NADES hydrogen-bonding network remained largely intact. CO₂ exhibited preferentialadsorption over flue gas components (N₂, H₂O, O₂), with substantial accumulation in both the first and secondinterfacial layers. Approximately 50% of the CO₂ content from flue gas mixtures was retained within thestructured region. Adsorption performance was found to be largely independent of temperature (303− 323K) andNADES film thickness (20–50 Å). These results provide fundamental insight into NADES–graphene interactionsand highlight the potential of type V, naturally derived deep eutectic solvents as selective and environmentallybenign materials for CO₂ separation technologie
PB Elsevier
SN 2452-2627
YR 2026
FD 2026-01
LK https://hdl.handle.net/10259/11717
UL https://hdl.handle.net/10259/11717
LA eng
NO This work was funded by the European Union (873005-WORLD-H2020-MSCA-RISE-2019). We also acknowledge SCAYLE (Supercomputación Castilla y León, Spain) and COMPUTAEX (Supercomputación Extremadura, Spain) for providing supercomputing facilities. The statements made herein are solely the responsibility of the authors
DS Repositorio Institucional de la Universidad de Burgos
RD 26-may-2026