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University of Cambridge > Talks.cam > Lennard-Jones Centre > Microscopic Mechanism of Thermally Induced Ordered-Disordered Phase transitions in Zeolitic Imidazolate Frameworks Revealed via Molecular Dynamics and Machine Learning Techniques
Microscopic Mechanism of Thermally Induced Ordered-Disordered Phase transitions in Zeolitic Imidazolate Frameworks Revealed via Molecular Dynamics and Machine Learning TechniquesAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Dr Philipp Pracht. Metal-organic frameworks (MOFs) feature promising applications for important industrial and societal problems. In order to move forward in our quest for developing new MOF materials, we need to gain further molecular-level understanding on their transformations and phase transitions. In this presentation, I will highlight our recent study1 of the molecular mechanism of ordered-disordered phase transitions undergone by two zeolitic imidazolate frameworks composed by Zn2+ and imidazolate: a porous (ZIF-4) and a dense, non-porous (ZIF-zni) polymorph, via a combination of data science and computer simulation approaches. Molecular dynamics simulations were carried out at the atomistic level through the nb-ZIF-FF force field2 that incorporates ligand–metal reactivity and relies on dummy atoms to reproduce the correct tetrahedral topology around Zn2+ centres. Symmetry functions computed over a database of structures of the four phases, were used as inputs to train a neural network that predicts the probabilities of belonging to each of the phases at the local Zn2+ level with 90% accuracy. We find that the amorphization of ZIF -4 and the melting of ZIF -zni involve connectivity changes in the first neighbour ligands around the central Zn2+ cations. In addition, the former is a non-isotropic process and we trace back the origins of this behaviour to density and lability of coordination bonds. These investigations are part of a larger project where reactive processes of MOFs in solution are studied via a combination of multiscale simulations and data science techniques (ERC starting grant, MAGNIFY project [3]). [1] arXiv: 2311.16351 [2] S. R. G. Balestra and R. Semino; J. Chem. Phys, 157, 184502 (2022) [3] https://www.rociosemino.com/magnify-project This talk is part of the Lennard-Jones Centre series. This talk is included in these lists:
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