Prediction and metrology of stochastic photoresist thickness defects
US12406197B2 · kind B2 · utility
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19Claims
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Key dates
| Filing date | Jun 2, 2021 |
| Grant date | Sep 2, 2025 |
| Priority date | — |
| Expiry date | Apr 19, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/082
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A mask pattern for a semiconductor device can be used as an input to determine a photoresist thickness probability distribution using a machine learning module. For example, the machine learning module can determine a probability map of Z-height. This can be used to determine stochastic variation in photoresist thickness for a semiconductor device. The Z-height may be calculated at a coordinate in the X-direction and Y-direction.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.