BEGIN:VCALENDAR
VERSION:2.0
PRODID:icalendar-ruby
CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VTIMEZONE
TZID:Europe/Vienna
BEGIN:DAYLIGHT
DTSTART:20220327T030000
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3
TZNAME:CEST
END:DAYLIGHT
BEGIN:STANDARD
DTSTART:20221030T020000
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10
TZNAME:CET
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260404T195924Z
UID:61691ed053c7d352820706@ist.ac.at
DTSTART:20220512T110000
DTEND:20220512T120000
DESCRIPTION:Speaker: Giovanni Pavan\nhosted by Andela Saric\nAbstract: Supr
 amolecular polymers\, composed of monomers that self-assemble via non-cova
 lent interaction into 1D\, 2D\, or 3D structures (or materials) are attrac
 ting increasing interest in many fields.1 In such self-assembled systems\,
  the constitutive building-blocks obey to a well-defined supramolecular eq
 uilibrium.2 This imparts an intrinsically dynamic character to the assembl
 ies that populate the system\, which exist as exquisitely statistical/dyna
 mical entities in continuous communication with each other and with the ex
 ternal environment\, generating de facto a complex molecular system.While 
 typical experimental approaches allow to obtain average ensemble informati
 on on the dynamics of the entire system\,3 advanced simulation approaches 
 may provide submolecular resolution insights into the origin of the dynami
 cs of the (individual) assemblies.4 However\, the key molecular factors th
 at control the communication networks and emergent properties in these com
 plex molecular systems remain most often unclear. Learning how to master s
 uch complex molecular systems requires to enter into their innate dynamics
  at a submolecular resolution\, and to obtain information on the molecular
  processes that control them.In this talk\, I will provide an overview of 
 the computational approaches that we are recently adopting to reconstruct 
 the intrinsic dynamics of self-assembling molecular systems. This journey 
 brought us into the study of their complexity\,5 of their fluctuations\,6 
 and into the design and development of data-driven approaches to compare a
 nd classify them.7 We are coming out with a new perspective\, which contai
 ns general concepts that can be transferred to a variety of complex molecu
 lar systems and holds great potential for many applications.1. Aida\, T.\;
  Meijer\, E. W.\; Stupp\, S. I. Science 2012\, 335\, 813-8172. a) Lehn\, J
 .-M. Prog. Polym. Sci. 2005\, 30\, 814-831\; b) Davis\, A. V.\, Yeh\, R. M
 . & Raymond\, K. N. Proc. Natl Acad. Sci. USA 2002\, 99\, 4793-47963. a) B
 aker\, M. B.\; Pavan\, G. M.\; Meijer\, E. W.\; et al. Nat. Commun. 2015\,
  6\, 6234\; b) Lou\, X.\; Meijer\, E. W.\; et al. Nat. Commun. 2017\, 8\, 
 154204. Bochicchio\, D.\; Salvalaglio\, M.\; Pavan\, G. M. Nature Commun.\
 , 2017\, 8\, 1475. Crippa\, M.\; Perego\, C.\; de Marco\, A.\; Pavan\, G. 
 M. Nat. Commun.\, 2022\, in press\, DOI: 10.1038/s41467-022-29804-5 (ChemR
 xiv 2021\, DOI:10.26434/chemrxiv-2021-vm2hs)6. a) Gasparotto\, P.\; Bochic
 chio\, D.\; Ceriotti\, M.\; Pavan\, G. M. J. Phys. Chem. B 2020\, 124\, 58
 9-599\; b) de Marco\, A. L.\; Bochicchio\, D.\; Gardin\, A.\; Doni\, G.\; 
 Pavan\, G. M. ACS Nano 2021\, 15\, 14229-142417. Gardin\, A.\; Perego\, C.
 \; Doni\, G.\; Pavan\, G. M. ArXiv 2021\, arXiv:2112.08044 Join Zoom Meet
 inghttps://istaustria.zoom.us/j/62060210216?pwd=Sk1QZW1DRGFxc3J4NzR3cnk3Y3
 RmZz09 Meeting ID: 620 6021 0216Passcode: 649535
LOCATION:Heinzel Seminar Room / Office Bldg West (I21.EG.101)\, ISTA
ORGANIZER:cpetz@ist.ac.at
SUMMARY:Giovanni Pavan: Innate Dynamics\, Molecular Communication Networks 
 &amp\; Emergent Bioinspired Properties in Complex Supramolecular Systems
URL:https://talks-calendar.ista.ac.at/events/3727
END:VEVENT
END:VCALENDAR