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SUMMARY:Mingjian Wen (University of Houston)
DTSTART:20240222T160000Z
DTEND:20240222T163000Z
DTSTAMP:20260421T124551Z
UID:MoRN/91
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/MoRN/91/">CR
 Ns Enabling Unbiased Exploration of the Reaction Space in Batteries</a>\nb
 y Mingjian Wen (University of Houston) as part of Seminar on the Mathemati
 cs of Reaction Networks\n\n\nAbstract\nChemical reaction networks (CRNs)\,
  when integrated with machine learning (ML) techniques\, can offer unprece
 dented opportunities to interrogate complex chemical systems. Here\, as an
  example\, I will delve into the use of graph neural networks and CRNs to 
 facilitate data-driven exploration of the chemical reaction space in Li-io
 n batteries\, aiming to find the optimal reaction pathways that lead to th
 e formation of the solid-electrolyte interphase. Additionally\, I will tou
 ch on other CRN problems where ML holds promising solutions.\n
LOCATION:https://researchseminars.org/talk/MoRN/91/
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