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SUMMARY:Prediction-Led Discovery of Functional Molecular Organic Crystals 
 - Prof Graeme Day\, University of Southampton
DTSTART:20241126T151500Z
DTEND:20241126T161500Z
UID:TALK224290@talks.cam.ac.uk
CONTACT:David Madden
DESCRIPTION:The seminar will explore the application of crystal structure 
 prediction (CSP) methods to the inverse design of crystalline molecular ma
 terials with targeted properties. There has been impressive recent progres
 s in computational methods for predicting crystal structures from first pr
 inciples\, making use of efficient methods for exploring energy landscapes
  coupled with accurate evaluations of the stability of computer-generated 
 crystal structures [1]. Given these advances\, there is a current focus on
  how to make the best use of CSP to identify the most promising molecules 
 to deliver a desired property. Our goal is to build a computational framew
 ork that integrates structure prediction\, property prediction and methods
  to explore the chemical space of possible molecules [2]. Examples from th
 e area of porous materials will demonstrate how computation-led research h
 as resulted in the discovery of unusual materials with extraordinary prope
 rties. [3\, 4] We are also developing how these computational methods will
  interact with automation in the materials chemistry lab\, where promising
  molecules are screened to realise predicted structures [5\, 6]\, with a l
 ong-term aim of closed-loop materials discovery.\n\n[1] Predictive crystal
 lography at scale: mapping\, validating\, and learning from 1000 crystal e
 nergy landscapes\, Taylor\, C. R.\, Butler\, P. W. V.\, and Day\, G. M.\, 
 Faraday Discussions\, https://doi.org/10.1039/D4FD00105B (2024)\;\n\n[2] E
 volutionary chemical space exploration for functional materials: computati
 onal organic semiconductor discovery\, Cheng\, C. Y. and Day\, G. M.\, Che
 mical Science\, 11\, 4922 (2020)\;\n\n[3] Pulido\, A.\,  Chen\, L.\, Kaczo
 rowski\, T.\, Holden\, D.\, Little\, M. A.\, Chong\, S. Y.\, Slater\, B. J
 .\, McMahon\, D. P.\, Bonillo\, B.\, Stackhouse\, C.\, Stephenson\, A.\, K
 ane\, C. M.\, Clowes\, R.\, Hasell\, T.\, Cooper\, A. I. and Day\, G. M.\,
  Nature\, 543\, 657 (2017)\;\n\n[4] Porous isoreticular non-metal organic 
 frameworks\, O’Shaughnessy\, M.\, Glover\, J.\, Hafizi\, R\, Barhi\,M.\,
  Clowes\, R\, Chong\, S. Y.\, Argent\, S. P.\, Day\, G. M. and Cooper\, A.
  I.\, Nature 630\, 102–108 (2024)\;\n\n[5] Mining predicted crystal stru
 cture landscapes with high throughput crystallisation: old molecules\, new
  insights\, Cui\, P.\, McMahon\, D. P.\, Spackman\, P. R.\, Alston\, B. M.
 \, Little\, M. A.\, Day\, G. M. and Cooper\, A. I.\, Chemical Science\, 10
 \, 9988 (2019)\;\n\n[6] Modular\, multi-robot integration of laboratories:
  an autonomous workflow for solid-state chemistry\, Lunt\, A. M.\, Fakhrul
 deen\, H.\, Pizzuto\, G.\, Longley\, L.\, White\, A.\, Rankin\, N.\, Clowe
 s\, R.\, Alston\, B.\, Gigli\, L\, Day\, G.. M.\, Cooper\, A. I. and Chong
 \, S. Y.\, Chemical Science\, 15\, 2456-2463 (2024).
LOCATION:Pfizer Lecture Theatre\, Department of Chemistry
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