Meta-Learned and TCAD-Assisted Sampling in Semiconductor Laser Annealing

[Image: see text] While applying machine learning (ML) to semiconductor manufacturing is prevalent, an efficient way to sample the search space has not been explored much in key processes such as lithography, annealing, deposition, and etching. The aim is to use the fewest experimental trials to con...

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Detalles Bibliográficos
Autores principales: Rawat, Tejender Singh, Chang, Chung Yuan, Feng, Yen-Wei, Chen, ShihWei, Shen, Chang-Hong, Shieh, Jia-Min, Lin, Albert Shihchun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9836362/
https://www.ncbi.nlm.nih.gov/pubmed/36643440
http://dx.doi.org/10.1021/acsomega.2c06000

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9836362/
https://www.ncbi.nlm.nih.gov/pubmed/36643440
http://dx.doi.org/10.1021/acsomega.2c06000

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