Predicting early failure of quantum cascade lasers during accelerated burn-in testing using machine learning

Device life time is a significant consideration in the cost of ownership of quantum cascade lasers (QCLs). The life time of QCLs beyond an initial burn-in period has been studied previously; however, little attention has been given to predicting premature device failure where the device fails within...

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Detalles Bibliográficos
Autores principales: Aydinkarahaliloglu, Cagri, Jatar, Shashank, Wang, Xiaojun, Fong, Mary, Gupta, Vijay, Troccoli, Mariano, Hoffman, Anthony J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9163159/
https://www.ncbi.nlm.nih.gov/pubmed/35654815
http://dx.doi.org/10.1038/s41598-022-13303-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9163159/
https://www.ncbi.nlm.nih.gov/pubmed/35654815
http://dx.doi.org/10.1038/s41598-022-13303-0

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