Charge–discharge properties of LiMn2O4-group positive electrode active materials for lithium-ion batteries using high-throughput experimental screening and machine learning models

Charge–discharge properties of LiMn2O4-group positive electrode active materials for lithium-ion batteries using high-throughput experimental screening and machine learning models

To improve the charge – discharge properties of an LiMn2O4 positive electrode active material for a lithium-ion battery, the effect of additive elements was investigated using high-throughput experiments and materials informatics techniques. First, the material libraries of LiMn1.4NixAyBzO4±δ (A, B ...

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Bibliographic Details
Main Authors: Shin Tajima, Mitsutaro Umehara, Kensuke Takechi
Format: Article
Language:English
Published: Taylor & Francis Group 2023-12-01
Series:Science and Technology of Advanced Materials: Methods
Subjects:
high-throughput experiments
materials informatics
machine learning
lithium-ion battery
xanes
positive electrode active material
limn2o4
chemical delithiation
support vector regression
Online Access:http://dx.doi.org/10.1080/27660400.2023.2260299

Internet

http://dx.doi.org/10.1080/27660400.2023.2260299

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