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SUMMARY:First-Principles Search for Battery Electrodes - Ziheng Lu
DTSTART:20210210T113000Z
DTEND:20210210T123000Z
UID:TALK156001@talks.cam.ac.uk
CONTACT:Chuck Witt
DESCRIPTION:Electrode materials are critical components of rechargeable ba
 tteries which determine a series of device-level performances including en
 ergy density\, rate capability\, cyclic stability\, and cost. Conventional
 ly\, the search of electrode materials relies on experimental trial-and-er
 ror and traversing existing computational databases. While these methods h
 ave led to the discovery of several commercially-viable cathodes materials
 \, the chemical space being explored is limited and many hidden phases hav
 e been overlooked\, especially those with meta-stability. We explore the p
 ossibility of using first-principles crystal structure prediction methods\
 , in particular\, ab-initio random structural searching (AIRSS)\, to searc
 h for novel electrode materials. We show that\, by limiting the search spa
 ce using a number of constraints including interatomic distances\, cell vo
 lumes and spin states\, AIRSS can efficiently predict both thermodynamical
 ly stable and meta-stable electrode materials. Specifically\, we use LiCoO
 2\, LiFePO4\, and LixMnyOz to showcase the efficiency of the current metho
 d by re-identifying known cathodes. The effect of tunable parameters such 
 as interatomic distances\, cell volumes\, and spin states on efficiency of
  sampling is discussed in detail. A minimal “learning” process is intr
 oduced by adapting interatomic distance constraints from low-energy random
  structures which efficiently captures the local coordination environment 
 of atoms. We also use this method to make predictions. A family of cathode
  materials based on transition-metal oxalates is proposed which demonstrat
 es superb energy density\, oxygen-redox stability\, and lithium diffusion 
 properties.
LOCATION:Zoom
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