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1
Predicting Ionic Conductivity of Solid-State Battery Cathod..:
, In:
2024 United States National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM)
,
Le, Mai
;
Le, Hieu
;
Zhao, Lihong
... - p. 381-382 , 2024
Link:
https://doi.org/10.23919/USNC-URSINRSM60317.2024.10464..
RT T1 <cTitle>2024 United States National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM)</cTitle>: T1 <Title>Predicting Ionic Conductivity of Solid-State Battery Cathodes Using Machine Learning</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10464783&Exemplar=1&LAN=DE A1 Le, Mai A1 Le, Hieu A1 Zhao, Lihong A1 Wu, Xuqing A1 Chen, Jiefu A1 Yao, Yan YR 2024 K1 Resistance K1 Scanning electron microscopy K1 Machine learning K1 Voltage K1 Conductivity K1 Prediction algorithms K1 Solid state batteries K1 solid-state battery K1 ionic conductivity K1 machine learning K1 image analysis SP 381 OP 382 LK http://dx.doi.org/https://doi.org/10.23919/USNC-URSINRSM60317.2024.10464783 DO https://doi.org/10.23919/USNC-URSINRSM60317.2024.10464783 SF ELIB - SuUB Bremen
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