13 citations · 16 across the 4 of their papers we have counts for
4 papers
Decoding local framework dynamics in the ultra-small pore MOF MIL-120(Al) CO2 sorbent with Machine Learned Potentials
Dong Fan, Felipe Lopes Oliveira, Mohammad Wahiduzzaman +1
Metal-organic frameworks (MOFs) with ultra-small pores offer an optimal environment to effectively capture guest molecules such as CO2. Subtle local dynamics of their frameworks, e…
Machine Learning Potential for Modelling H Adsorption/Diffusion in MOF with Open Metal Sites
Shanping Liu, Romain Dupuis, Dong Fan +5
Metal-organic frameworks (MOFs) incorporating open metal sites (OMS) have been identified as promising sorbents for many societally relevant-adsorption applications including CO$_2…
Unravelling Negative In-plane Stretchability of 2D MOF by Large Scale Machine Learning Potential Molecular Dynamics
Dong Fan, Aydin Ozcan, Pengbo Lyu +1
Two-dimensional (2D) metal-organic frameworks (MOFs) hold immense potential for various applications due to their distinctive intrinsic properties compared to their 3D analogues. H…
Coarse Grained modeling of Zeolitic Imidazolate Framework-8 using MARTINI Force Fields
Cecilia M. S. Alvares, Guillaume Maurin, Rocio Semino
In this contribution, the well-known MARTINI particle-based coarse graining approach is tested for its ability to model the ZIF-8 metal-organic framework. Its capability to describ…