This title appears in the Scientific Report :
2023
Please use the identifier:
http://dx.doi.org/10.1002/batt.202200228 in citations.
Please use the identifier: http://dx.doi.org/10.34734/FZJ-2023-05462 in citations.
One‐Shot Active Learning for Globally Optimal Battery Electrolyte Conductivity**
One‐Shot Active Learning for Globally Optimal Battery Electrolyte Conductivity**
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....
Saved in:
Personal Name(s): | Rahmanian, Fuzhan |
---|---|
Vogler, Monika / Wölke, Christian / Yan, Peng / Winter, Martin / Cekic-Laskovic, Isidora / Stein, Helge S. (Corresponding author) | |
Contributing Institute: |
Helmholtz-Institut Münster Ionenleiter für Energiespeicher; IEK-12 |
Published in: | Batteries & supercaps, 5 (2022) 10, S. e202200228 |
Imprint: |
Weinheim
Wiley-VCH
2022
|
DOI: |
10.1002/batt.202200228 |
DOI: |
10.34734/FZJ-2023-05462 |
Document Type: |
Journal Article |
Research Program: |
Battery Interface Genome - Materials Acceleration Platform Fundamentals and Materials |
Link: |
OpenAccess |
Publikationsportal JuSER |
Please use the identifier: http://dx.doi.org/10.34734/FZJ-2023-05462 in citations.
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. |