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SUMMARY:Rapid Exploration of Crystal Chemical Space  - Aron Walsh\, Imperi
 al College London
DTSTART:20250310T140000Z
DTEND:20250310T143000Z
UID:TALK228043@talks.cam.ac.uk
CONTACT:Kang Wang
DESCRIPTION:Traditional materials modelling workflows\, even in the form o
 f high-throughput approaches\, are limited to small numbers of composition
 s and structures. I will present progress in materials informatics solutio
 ns for navigating a larger crystal chemical space.  This includes techniqu
 es for compositional screening based on elemental features and mapping fro
 m chemical formulae to three-dimensional crystal structures. A focus will 
 be placed on hand-built chemical filters to reduce the magnitude of the se
 arch space and filters that are learned from data in the form of deep lear
 ning models based on crystal graphs. The performance of data-driven and do
 main knowledge-inspired approaches will be compared. Outstanding challenge
 s in the field including robust synthesisability metrics and generative ar
 tificial intelligence models for sampling new materials will also be discu
 ssed. 
LOCATION:zoom.us/j/92447982065?pwd=RkhaYkM5VTZPZ3pYSHptUXlRSkppQT09
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