Machine learning for accelerated bandgap prediction in strain-engineered quaternary III–V semiconductors

Research output: Contribution to journal › Article › peer-review

Original language	English
Journal	The Journal of Chemical Physics
DOIs	https://doi.org/10.1063/5.0159604
Publication status	Published - 14 Sep 2023
Externally published	Yes

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@article{27a57ad7862d46abbc66ddb0f6f283de,

title = "Machine learning for accelerated bandgap prediction in strain-engineered quaternary III–V semiconductors",

author = "Badal Mondal and Julia Westermayr and Ralf Tonner-Zech",

year = "2023",

month = sep,

day = "14",

doi = "10.1063/5.0159604",

language = "English",

journal = "The Journal of Chemical Physics",

}

TY - JOUR

T1 - Machine learning for accelerated bandgap prediction in strain-engineered quaternary III–V semiconductors

AU - Mondal, Badal

AU - Westermayr, Julia

AU - Tonner-Zech, Ralf

PY - 2023/9/14

Y1 - 2023/9/14

UR - https://doi.org/10.1063/5.0159604

U2 - 10.1063/5.0159604

DO - 10.1063/5.0159604

M3 - Article

JO - The Journal of Chemical Physics

JF - The Journal of Chemical Physics

ER -