Using machine learning with optical profilometry for GaN wafer screening

Abstract To improve the manufacturing process of GaN wafers, inexpensive wafer screening techniques are required to both provide feedback to the manufacturing process and prevent fabrication on low quality or defective wafers, thus reducing costs resulting from wasted processing effort. Many of the...

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Bibliographic Details
Main Authors: James C. Gallagher, Michael A. Mastro, Mona A. Ebrish, Alan G. Jacobs, Brendan P. Gunning, Robert J. Kaplar, Karl D. Hobart, Travis J. Anderson
Format: Article
Language:English
Published: Nature Portfolio 2023-02-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-29107-9