RT Journal Article
T1 Monitoring Hydroquinone Clathrates in Molecular Simulation Using Local Bond Order Parameters
A1 Rodríguez García, Brais
A1 Algaba Fernández, Jesús
A1 Jiménez Blas, Felipe
A1 Pérez Rodríguez, Martín
A1 Martínez Piñeiro, Manuel
AB Hydroquinone clathrates (HQ clathrates) are highly structured crystalline materials with promising application in carbon separation and sequestration, and also in hydrogen storage. In this  study, molecular simulation techniques are employed to analyze the structure of β-HQ clathrates using local bond order parameters. The methodology is based on the definition by Steinhardt and Lechner−Dellago of the averaged bond order parameters, which allow a precise differentiation between solid and liquid phases. Using molecular dynamics simulations, we evaluate the role of guest molecules such as CO2 and CH4 in the stability and formation of clathrates. In this study, we determine and test an optimal combination of bond order parameters (q̅12−q̅8) capable of accurately characterizing phase transitions with a classification error of less than 0.001%. The proposed method is able to qualitatively and quantitatively discern the membership of each molecule to the different phases during the crystallization and dissociation processes, demonstrating its effectiveness in the study of the dynamics of HQ clathrate at different pressure and temperature conditions. The results of this work provide a solid and applicable theoretical framework intended to further provide insight into the nucleation process of this system, contributing to its understanding.
PB American Chemical Society
SN 0887-0624
SN 1520-5029 (electrónico)
YR 2025
FD 2025
LK https://hdl.handle.net/10272/27531
UL https://hdl.handle.net/10272/27531
LA eng
NO García, B. R., Algaba, J., Blas, F. J., Pérez-Rodríguez, M., & Piñeiro, M. M. (2025). Monitoring Hydroquinone Clathrates in Molecular Simulation Using Local Bond Order Parameters. Energy & Fuels, 39(21), 9884–9892. https://doi.org/10.1021/acs.energyfuels.5c01091
NO This work was funded by Ministerio de Ciencia e Innovación (Grants No. PID2021-125081NB-I00 and PID2024-158030NB-I00) and Universidad de Huelva (P.O. FEDER EPIT1282023), both cofinanced by EU FEDER funds. MJT also acknowledges the research contract (ref 01/2022/38143) of Programa Investigo (Plan de Recuperación, Transformación y Resiliencia, Fondos NextGeneration EU) from Junta de Andalucía (HU/INV/0004/2022). MPR acknowledges grant ref CNS2022-135881 financed by MCIN/AEI/10.13039/501100011033 and NextGenerationEU/PRTR. We greatly acknowledge the RES resources provided by the Barcelona Supercomputing Center in Mare Nostrum to FI-2024-3-0019, and computing resources provided by the Centro de Supercomputación de Galicia (CESGA, www.cesga.es, Finisterrae III Supercomputer).
DS Repositorio Institucional de la Universidad de Huelva
RD 1 jun 2026