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SUMMARY:Data-driven approaches to new thermoelectric material discovery
DTSTART:20170302T110000
DTEND:20170302T120000
DTSTAMP:20260510T135547Z
UID:a2099513dd5436125a18c4b7315cb751a2b3a321947c182176019627
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr Michael Gaultois\, University of Cambridge Department of Ch
 emistry\, U.K.\nBreaking out of the common composition space to discover n
 ew chemistries is a difficult challenge in all materials disciplines\, and
  many of the most notable materials classes under investigation today were
  discovered fortuitously. Experimental efforts often gravitate toward incr
 ementally improving known chemistries through chemical substitution\, dopi
 ng\, microstructure engineering\, etc.\, as these efforts are more likely 
 to bear fruit than high-risk searches through chemical whitespace for enti
 rely new materials. Moreover\, principles and beliefs about what constitut
 e potentially interesting materials are based only on the existing paradig
 m\, which may be irrelevant for other classes of materials.\n\nThermoelect
 ric materials are a class of materials that can generate power from heat\,
  but their widespread deployment has been limited because thermoelectric m
 aterials are currently inefficient\, made from rare elements\, and decompo
 se at high temperatures when operated in air. Researchers have sought to d
 evelop oxide thermoelectric materials to overcome these shortfalls\, but d
 evelopment of oxide materials is still relatively new\, and has lacked gui
 ding principles that have led to significant advances in traditional therm
 oelectric materials.\n\nThe work presented here outlines the development o
 f design principles for oxide thermoelectric materials\, which involved th
 e creation of a thermoelectric materials database\, identification of the 
 property space of interest\, and the experimental prepara-tion and charact
 erization of materials in this property space. The presentation will also 
 highlight ongoing work\, which has used machine learning models to create 
 a materials recommendation engine to be used by experimentalists to help s
 timulate the search for new material families.\n\nBio:\nDr Michael Gaultoi
 s is a Marie Curie International Fellow in the University of Cambridge Dep
 artment of Chemistry. Michael completed his PhD in Chemistry at the Univer
 sity of California in Santa Barbara with Prof. Ram Seshadri\, and in May 2
 015 joined the group of Prof. Clare Grey for postdoctoral research\, where
  he is studying inorganic functional materials for electrochemical energy 
 storage\, CO2 capture and looping\, and O2 looping.
LOCATION:MED 2 1124 (Coviz2) http://plan.epfl.ch/?lang=fr&room=MED21124
STATUS:CONFIRMED
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