RT Journal Article
T1 Combined DFT and Kinetic Monte Carlo Study of UiO-66 Catalysts for γ-Valerolactone Production
A1 Le Thi Thanh, Hiep
A1 Ferro Costas, David
A1 Fernández Ramos, Antonio
A1 Ortuño Maqueda, Manuel Ángel
K1 Catalysts
K1 Cluster chemistry
K1 Energy
K1 Kinetic parameters
K1 Metal organic frameworks
AB Zr-based metal–organic frameworks (MOFs) are excellent heterogeneous porous catalysts due to their thermal stability. Their tunability via node and linker modifications makes them amenable for theoretical studies on catalyst design. However, detailed benchmarks on MOF-based reaction mechanisms combined with kinetics analysis are still scarce. Thus, we here evaluate different computational models and density functional theory (DFT) methods followed by kinetic Monte Carlo studies for a case reaction relevant in biomass upgrading, i.e., the conversion of methyl levulinate to γ-valerolactone catalyzed by UiO-66. We show the impact of cluster versus periodic models, the importance of the DF of choice, and the direct comparison to experimental data via simulated kinetics data. Overall, we found that Perdew–Burke–Ernzerhof (PBE), a widely employed method in plane-wave periodic calculations, greatly overestimates reaction rates, while M06 with cluster models better fits the available experimental data and is recommended whenever possible.
PB American Chemical Society
SN 1932-7455
YR 2024
FD 2024-01-12
LK https://hdl.handle.net/10347/38455
UL https://hdl.handle.net/10347/38455
LA eng
NO Thanh-Hiep Thi Le, David Ferro-Costas, Antonio Fernández-Ramos, and Manuel A. Ortuño.  Combined DFT and Kinetic Monte Carlo Study of UiO-66 Catalysts for γ-Valerolactone Production, The Journal of Physical Chemistry C 2024 128 (3), 1049-1057
NO This work has received financial support from  the European Union (European Regional Development Fund─ERDF)
DS Minerva
RD 27 abr 2026