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SUMMARY:Getting from the computer to real world materials faster with mach
 ine learning - Prof. Heather J. Kulik\, MIT
DTSTART:20250203T140000Z
DTEND:20250203T143000Z
UID:TALK226375@talks.cam.ac.uk
CONTACT:Dr Fabian Berger
DESCRIPTION:I will describe our efforts to accelerate the discovery of nov
 el transition metal containing materials using machine learning. I will di
 scuss how we have leveraged experimental data sets through both text minin
 g and semantic embedding to uncover relationships between structure and fu
 nction. Then I will describe how we have leveraged large datasets of synth
 esized materials to uncover those with novel function in polymer networks.
  I will describe how we demonstrate the success of our design strategy thr
 ough macroscopically visible changes in network scale properties.
LOCATION:zoom.us/j/92447982065?pwd=RkhaYkM5VTZPZ3pYSHptUXlRSkppQT09
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