Machine learning in metrology measurements
US11248905B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Dec 6, 2017 |
| Grant date | Feb 15, 2022 |
| Priority date | — |
| Expiry date | Nov 25, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.