Sökning: WFRF:(Jeschke Steffen 1986)
> (2021) >
Supervised Machine ...
Supervised Machine Learning-Based Classification of Li-S Battery Electrolytes
-
- Jeschke, Steffen, 1986 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
-
- Johansson, Patrik, 1969 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology,Centre national de la recherche scientifique (CNRS)
-
(creator_code:org_t)
- 2021-05-04
- 2021
- Engelska.
-
Ingår i: Batteries and Supercaps. - : Wiley. - 2566-6223. ; 4:7, s. 1156-1162
- Relaterad länk:
-
https://research.cha... (primary) (free)
-
visa fler...
-
https://onlinelibrar...
-
https://doi.org/10.1...
-
https://research.cha...
-
visa färre...
Abstract
Ämnesord
Stäng
- Machine learning (ML) approaches have the potential to create a paradigm shift in science, especially for multi-variable problems at different levels. Modern battery R&D is an area intrinsically dependent on proper understanding of many different molecular level phenomena and processes alongside evaluation of application level performance: energy, power, efficiency, life-length, etc. One very promising battery technology is Li-S batteries, but the polysulfide solubility in the electrolyte must be managed. Today, many different electrolyte compositions and concepts are evaluated, but often in a more or less trial-and-error fashion. Herein, we show how supervised ML can be applied to accurately classify different Li-S battery electrolytes a priori based on predicting polysulfide solubility. The developed framework is a combined density functional theory (DFT) and statistical mechanics (COSMO-RS) based quantitative structure-property relationship (QSPR) model which easily can be extended to other battery technologies and electrolyte properties.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Annan data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Other Computer and Information Science (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Annan teknik -- Övrig annan teknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Other Engineering and Technologies -- Other Engineering and Technologies not elsewhere specified (hsv//eng)
- NATURVETENSKAP -- Kemi -- Teoretisk kemi (hsv//swe)
- NATURAL SCIENCES -- Chemical Sciences -- Theoretical Chemistry (hsv//eng)
Nyckelord
- polysulfide
- supervised machine learning
- solubility
- electrolyte design
- lithium-sulfur batteries
Publikations- och innehållstyp
- art (ämneskategori)
- ref (ämneskategori)
Hitta via bibliotek
Till lärosätets databas