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CATEGORIES:Lennard-Jones Centre
SUMMARY:Microscopic Mechanism of Thermally Induced Ordered
 -Disordered Phase transitions in Zeolitic Imidazol
 ate Frameworks Revealed via Molecular Dynamics and
  Machine Learning Techniques - Prof. Rocio Semino\
 , Sorbonne University
DTSTART;TZID=Europe/London:20240122T140000
DTEND;TZID=Europe/London:20240122T143000
UID:TALK210673AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/210673
DESCRIPTION:Metal-organic frameworks (MOFs) feature promising 
 applications for important industrial and societal
  problems. In order to move forward in our quest f
 or developing new MOF materials\, we need to gain 
 further molecular-level understanding on their tra
 nsformations and phase transitions. In this presen
 tation\, I will highlight our recent study[1] of t
 he molecular mechanism of ordered-disordered phase
  transitions undergone by two zeolitic imidazolate
  frameworks composed by Zn2+ and imidazolate: a po
 rous (ZIF-4) and a dense\, non-porous (ZIF-zni) po
 lymorph\, via a combination of data science and co
 mputer simulation approaches. Molecular dynamics s
 imulations were carried out at the atomistic level
  through the nb-ZIF-FF force field[2] that incorpo
 rates ligand–metal reactivity and relies on dummy 
 atoms to reproduce the correct tetrahedral topolog
 y around Zn2+ centres. Symmetry functions computed
  over a database of structures of the four phases\
 , were used as inputs to train a neural network th
 at predicts the probabilities of belonging to each
  of the phases at the local Zn2+ level with 90% ac
 curacy. We find that the amorphization of ZIF-4 an
 d the melting of ZIF-zni involve connectivity chan
 ges in the first neighbour ligands around the cent
 ral Zn2+ cations. In addition\, the former is a no
 n-isotropic process and we trace back the origins 
 of this behaviour to density and lability of coord
 ination bonds. These investigations are part of a 
 larger project where reactive processes of MOFs in
  solution are studied via a combination of multisc
 ale simulations and data science techniques (ERC s
 tarting grant\, MAGNIFY project [3]). \n\n[1] arXi
 v: 2311.16351\n\n[2] S. R. G. Balestra and R. Semi
 no\; J. Chem. Phys\, 157\, 184502 (2022)\n\n[3] ht
 tps://www.rociosemino.com/magnify-project
LOCATION:Zoom link: https://zoom.us/j/92447982065?pwd=RkhaY
 kM5VTZPZ3pYSHptUXlRSkppQT09
CONTACT:Dr Philipp Pracht
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