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SUMMARY:MARVEL Distinguished Lecture – Gerbrand Ceder
DTSTART:20250130T150000
DTEND:20250130T161500
DTSTAMP:20260508T174139Z
UID:98979f2dfabb2e48784f1819742c4e42d368fc76bd27c5fa46cb44ec
CATEGORIES:Conferences - Seminars
DESCRIPTION:Gerbrand Ceder (UC Berkeley)\nhttps://epfl.zoom.us/j/657106251
 78\nPasscode:1652\n\nProf. Gerbrand Ceder\nUniversity of California Berkel
 ey\n\nHow the future of science may look:  AI and autonomous laboratorie
 s for materials synthesis \nComputational materials science has seen trem
 endous progress since the early days of Density Functional Theories.  St
 able algorithms enabled high-throughput computing which in turn enabled ma
 chine-learned potentials (MLP).  Though far from perfect at this point\,
  MLPs hold tremendous promise for accelerating materials simulation and di
 scovery.   \nSuch progress is not parallelled on the experimental side\
 , making it the gating factor in materials development.  In response we 
 built\, A-lab\, an autonomous facility for the closed-loop synthesis of in
 organic materials from powder precursors. All synthesis and characterizati
 on actions in A-lab\, including powder mixing and grinding\, firing\, char
 acterization by XRD and SEM\, and all sample transfers between them are fu
 lly automated\, leading to a lab that can synthesize and structurally char
 acterize compounds within 10-20 hrs of initiation.  The A-lab leverages 
 ab-initio computations through an API with the Materials Project\, histori
 cal data sets that are text-mined from the literature\, machine learning f
 or optimization of synthesis routes and interpretation of characterization
  data\, and active learning to plan and interpret the outcomes of experime
 nts performed using robotics. The automation of synthesis and analysis can
  be further integrated into scientific workflows similar to computational 
 workflows.    \n\nAbout the speaker\nGerbrand Ceder is the Samsung Di
 stinguished Professor of Engineering at UC Berkeley and a Senior Faculty S
 cientist at LBNL where he combines theory\, computation\, machine learning
 \, and experiments to develop novel materials for energy storage.  He h
 as published over 550 papers with over 130\,000 citations and a Hirsch ind
 ex of 182. He holds more than 50 US and foreign patents. He is a member of
  the National Academy of Engineering of the US\, the Royal Flemish Academy
  of Belgium for Science and The Art\, and the American Academy for the Art
 s and Sciences.  He is a Fellow of MRS\, APS\, TMS\, and ECS\, and has r
 eceived awards from the Electrochemical Society\, the Materials Research S
 ociety\, the Metals Minerals and Materials Society\, and the International
  Battery Association. He is a scientific advisor to multiple companies in 
 the energy storage and materials design space and a co-founder of Radical-
 AI. He leads the Department of Energy program on Earth-Abundant cathode ma
 terials (DRX+) and was active in formulating the US Materials Genome Initi
 ative. \n\n 
LOCATION:MED 2 1124 (Coviz2) https://plan.epfl.ch/?room==MED%202%201124 ht
 tps://epfl.zoom.us/j/65710625178?pwd=FYznVvKmRqlxe845OwidbOV64w57VC.1
STATUS:CONFIRMED
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