Invention Grant
- Patent Title: Machine learning in metrology measurements
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Application No.: US15750972Application Date: 2017-12-06
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Publication No.: US11248905B2Publication Date: 2022-02-15
- Inventor: Eran Amit
- Applicant: KLA-TENCOR CORPORATION
- Applicant Address: US CA Milpitas
- Assignee: KLA-TENCOR CORPORATION
- Current Assignee: KLA-TENCOR CORPORATION
- Current Assignee Address: US CA Milpitas
- Agency: Hodgson Russ LLP
- International Application: PCT/US2017/064955 WO 20171206
- International Announcement: WO2019/035854 WO 20190221
- Main IPC: G01B11/27
- IPC: G01B11/27 ; G03F7/00 ; G06N99/00 ; G06N20/00 ; G06F30/39 ; G03F7/20 ; G06F30/398

Abstract:
Metrology methods and targets are provided, that expand metrological procedures beyond current technologies into multi-layered targets, quasi-periodic targets and device-like targets, without having to introduce offsets along the critical direction of the device design. Machine learning algorithm application to measurements and/or simulations of metrology measurements of metrology targets are disclosed for deriving metrology data such as overlays from multi-layered target and corresponding configurations of targets are provided to enable such measurements. Quasi-periodic targets which are based on device patterns are shown to improve the similarity between target and device designs. Offsets are introduced only in non-critical direction and/or sensitivity is calibrated to enable, together with the solutions for multi-layer measurements and quasi-periodic target measurements, direct device optical metrology measurements.
Public/Granted literature
- US20190086200A1 Machine Learning in Metrology Measurements Public/Granted day:2019-03-21
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