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Machine-Learning-Enabled Prediction of Adiabatic Temperatur..:

Melody Su (11613614) ; Ryan Grimes (11613617) ; Sunidhi Garg (11613620)..
https://figshare.com/articles/dataset/Machine-Learning-Enabled_Prediction_of_Adiabatic_Temperature_Change_in_Lead-Free_BaTiO_sub_3_sub_Based_Electrocaloric_Ceramics/16887596. , 2021

Link: https://doi.org/10.1021/acsami.1c15021.s003

RT Journal
T1 <Title>Machine-Learning-Enabled Prediction of Adiabatic Temperature Change in Lead-Free BaTiO 3 ‑Based Electrocaloric Ceramics</Title>

UL https://suche.suub.uni-bremen.de/peid=base-ftsmithonian:oai:figshare.com:article_16887596&Exemplar=1&LAN=DE
				
A1 Melody Su (11613614)
A1 Ryan Grimes (11613617)
A1 Sunidhi Garg (11613620)
A1 Dezhen Xue (4045976)
A1 Prasanna V. Balachandran (1853842)
YR 2021
K1 Biotechnology
K1 Inorganic Chemistry
K1 Plant Biology
K1 Biological Sciences not elsewhere classified
K1 Chemical Sciences not elsewhere classified
K1 Information Systems not elsewhere classified
K1 enable interested users
K1 applied electric field
K1 classification learning model
K1 adiabatic temperature change
K1 published electrocaloric measurements
K1 temperature vs δ
K1 driven machine learning
K1 based ml models
K1 electrocaloric applications
K1 direct measurements
K1 trained models
K1 regression models
K1 targeted phase
K1 near rhombohedral
K1 global maxima
K1 general trend
K1 expected phase
K1 enabled prediction
K1 elemental descriptors
K1 combined regression
K1 chemical composition
JF https://figshare.com/articles/dataset/Machine-Learning-Enabled_Prediction_of_Adiabatic_Temperature_Change_in_Lead-Free_BaTiO_sub_3_sub_Based_Electrocaloric_Ceramics/16887596
LK http://dx.doi.org/https://doi.org/10.1021/acsami.1c15021.s003
DO https://doi.org/10.1021/acsami.1c15021.s003
SF ELIB - SuUB Bremen

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