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SUMMARY:Materials discovery using deep learning
DTSTART:20181217T131500
DTEND:20181217T141500
DTSTAMP:20260407T011331Z
UID:9010b4b5d72dc34d22edbfab31fe5d3dfad20de96810e1efa349a854
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Gareth Conduit\, University of Cambridge UK\nWe propose 
 a novel deep learning tool for materials discovery. The approach merges to
 gether both experimental data and computer simulations to exploit all poss
 ible sources of information. The tool has been used to design several mate
 rials that have been experimentally verified and patented. We present just
  one case study where we discover and characterize the new nickel-base all
 oy for direct laser deposition most likely to simultaneously satisfy targe
 ts of processibility\, cost\, density\, phase stability\, creep resistance
 \, oxidation\, and resistance to thermal stresses. Experimental testing co
 nfirms that the physical properties of the proposed alloy exceed those of 
 other commercially available Ni-base alloys for combustor liner applicatio
 ns.\n\nProbabilistic design of a molybdenum-base alloy using a neural netw
 ork\nB.D. Conduit\, N.G. Jones\, H.J. Stone & G.J. Conduit\nScripta Materi
 alia 146\, 82 (2018)\n\nMaterials data validation and imputation with an a
 rtificial neural network\nP.C. Verpoort\, P. MacDonald & G.J. Conduit\nCom
 putational Materials Science 147\, 176 (2018)\n\nDesign of a nickel-base s
 uperalloy using a neural network\nB.D. Conduit\, N.G. Jones\, H.J. Stone &
  G.J. Conduit\nMaterials & Design 131\, 358 (2017)\n\nBio: Gareth Conduit 
 has a track record of applying artificial intelligence to solve real-world
  problems. The technique\, originally developed for materials design\, is 
 now being commercialized by startup Intellegens in not only materials desi
 gn\, but also infrastructure\, drug discovery\, and healthcare. Previously
 \, Gareth had research interests in strongly correlated phenomena\, in par
 ticular proposing spin spiral state in the itinerant ferromagnet that was 
 later observed in CeFePO. Gareth's group is based at the University of Cam
 bridge. 
LOCATION:MXF 1 https://plan.epfl.ch/?room==MXF%201
STATUS:CONFIRMED
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