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DTSTAMP:20210916T132454Z
LOCATION:Michel Mayor
DTSTART;TZID=Europe/Stockholm:20210708T180000
DTEND;TZID=Europe/Stockholm:20210708T183000
UID:submissions.pasc-conference.org_PASC21_sess167_msa314@linklings.com
SUMMARY:Computational High-Throughput Screening for Soft-Matter Materials
DESCRIPTION:Minisymposium\n\nComputational High-Throughput Screening for S
 oft-Matter Materials\n\nBereau\n\nAdvanced statistical methods are rapidly
  impregnating many scientific fields, offering new perspectives on long-st
 anding problems. In materials science, data-driven methods are already bea
 ring fruit in various disciplines, such as hard condensed matter or inorga
 nic chemistry, while comparatively little has happened in soft matter. I w
 ill describe how we use multiscale simulations to leverage data-driven met
 hods in soft matter. We aim at establishing structure-property relationshi
 ps for complex thermodynamic processes across the chemical space of small 
 molecules. Akin to screening experiments, we devise a high-throughput coar
 se-grained simulation framework. Coarse-graining is an appealing screening
  strategy for two main reasons: it significantly reduces the size of chemi
 cal space and it can suggest a low-dimensional representation of the struc
 ture-property relationship. To illustrate these aspects, I will model the 
 passive translocation of small molecules across a phospholipid bilayer. Ou
 r systematic exploration generates predictions for more than 1 million sma
 ll molecules, and connects key functional groups to the thermodynamic proc
 ess. I will further outline recent results on using a deep generative adve
 rsarial architecture to backmap molecular configurations to the atomistic 
 level.\n\nDomain: CS and Math, Chemistry and Materials, Physics
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