Machine Learning for Deep Trench Bottom Width Measurements using Scatterometry : AM: Advanced Metrology

We present a machine learning enhanced metrology method to measure the bottom width of deep trenches (about 42 µm in depth) using optical scatterometry. For this study, 2D line trenches as well as circular 3D trenches with varying trench side-wall angles were investigated. A combination of reference...

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Bibliographic Details
Published in2023 34th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC) pp. 1 - 6
Main Authors Srichandan, Sasmita, Heider, Franz, Polak, Yulia, Ehrentraut, Georg, Juhasz, Laszlo, Haberjahn, Martin, Sakalauskas, Egidijus, Haupt, Ronny
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2023
Subjects
bottom CD
CD-SEM
Machine learning
OCD
Radar measurements
Reflectivity
scatterometry
Semiconductor device measurement
Semiconductor device modeling
Shape measurement
spectral reflectometry
Three-dimensional displays
trench shape
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Summary:We present a machine learning enhanced metrology method to measure the bottom width of deep trenches (about 42 µm in depth) using optical scatterometry. For this study, 2D line trenches as well as circular 3D trenches with varying trench side-wall angles were investigated. A combination of reference sets from SEM cross-sections, inline CD-SEM as well as depth measurements obtained from reflectance fringes are used to train the machine learning model. The results are cross verified against SEM cross-sections.
ISSN:2376-6697
DOI:10.1109/ASMC57536.2023.10121130