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@ARTICLE{Rahmanian:1019515,
      author       = {Rahmanian, Fuzhan and Vogler, Monika and Wölke, Christian
                      and Yan, Peng and Winter, Martin and Cekic-Laskovic, Isidora
                      and Stein, Helge S.},
      title        = {{O}ne‐{S}hot {A}ctive {L}earning for {G}lobally {O}ptimal
                      {B}attery {E}lectrolyte {C}onductivity**},
      journal      = {Batteries $\&$ supercaps},
      volume       = {5},
      number       = {10},
      issn         = {2566-6223},
      address      = {Weinheim},
      publisher    = {Wiley-VCH},
      reportid     = {FZJ-2023-05462},
      pages        = {e202200228},
      year         = {2022},
      abstract     = {Non-aqueous aprotic battery electrolytes need to perform
                      wellover a wide range of temperatures in practical
                      applications.Herein we present a one-shot active learning
                      study to find allconductivity optima, confidence bounds, and
                      relating formulationtrends in the temperature range from
                      􀀀 30°C to 60°C. Thisoptimization is enabled by a
                      high-throughput formulation andcharacterization setup guided
                      by one-shot active learningutilizing robust and heavily
                      regularized polynomial regression.Whilst there is an
                      initially good agreement for intermediate andlow
                      temperatures, there is a need for the active learning step
                      toimprove the model for high temperatures. Optimized
                      electrolyteformulations likely correspond to the highest
                      physicallypossible conductivities within this formulation
                      system whencompared to literature data. A thorough error
                      propagationanalysis yields a fidelity assessment of
                      conductivity measurementsand electrolyte formulation.},
      cin          = {IEK-12},
      ddc          = {540},
      cid          = {I:(DE-Juel1)IEK-12-20141217},
      pnm          = {1221 - Fundamentals and Materials (POF4-122) / BIG-MAP -
                      Battery Interface Genome - Materials Acceleration Platform
                      (957189)},
      pid          = {G:(DE-HGF)POF4-1221 / G:(EU-Grant)957189},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000844221600001},
      doi          = {10.1002/batt.202200228},
      url          = {https://juser.fz-juelich.de/record/1019515},
}