PATENT CLAIM ANALYSIS

Application Number: 15861938
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2018-09
Patent Classification: ["356", "338000"]

Abstract:
Methods and systems for robust overlay error measurement based on a trained measurement model are described herein. The measurement model is trained from raw scatterometry data collected from Design of Experiments (DOE) wafers by a scatterometry based overlay metrology system. Each measurement site includes one or more metrology targets fabricated with programmed overlay variations and known process variations. Each measurement site is measured with known metrology system variations. In this manner, the measurement model is trained to separate actual overlay from process variations and metrology system variations which affect the overlay measurement. As a result, an estimate of actual overlay by the trained measurement model is robust to process variations and metrology system variations. The measurement model is trained based on scatterometry data collected from the same metrology system used to perform measurements. Thus, the measurement model is not sensitive to systematic errors, aysmmetries, etc.

Claim (Index 10):
The scatterometry based metrology system of  claim 9 , wherein the at least one additional parameter of interest includes any of a process parameter, a structural parameter, a dispersion parameter, and a layout parameter.

Metadata:
- Claim Count in Document: 5.0
- Percentile: 86.0
- Lexical Diversity: 2.19178
- Patent Class: 356.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14880077', '14704840', '14924308', '14790793', '15671661']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.7925743719776858
- 35 USC 102 Novelty (BERT): 0.5596932057384983
- Combined Prediction Score: 0.769286255353767
- Mean Citation Score: 412.203012
- Max Citation Score: 451.2528
- Similarity Product: 369.9063918233872

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test