PATENT CLAIM ANALYSIS

Application Number: 15966918
Application Type: Utility
Filing Date: 2018-04
Publication Date: 2018-12
Patent Classification: ["702", "189000"]

Abstract:
The effective spot size of a spectroscopic metrology device is reduced through deconvolution of a measurement spectra set acquired from a measurement target combined with a training spectra set obtained from a training target. The measurement spectra set may be obtained using sparse sampling of a grid scan of a measurement target. The training spectra set is obtained from a grid scan of a training target that is similar to the measurement target. The training spectra set and the measurement spectra set include spectra from different grid nodes. Deconvolution of the measurement spectra and the training spectra sets produces an estimated spectrum for the measurement target that is an estimate of a spectrum from the measurement target produced with incident light having an effective spot size that is smaller than the actual spot size. One or more characteristics of the measurement target may then be determined using the estimated spectrum.

Claim (Index 10):
The method of  claim 1 , further comprising:\n obtaining a training spectra set from a scan of the grid array on a training target using the spectroscopic metrology device with the incident light having the measurement spot size to acquire a target spectra set, wherein the training spectra set comprises spectra from a second set of grid nodes in the grid array that is less than all grid nodes in the grid array; wherein performing the deconvolution of the measurement spectra set with the deconvolution kernel weight for each grid node in the first set of grid nodes comprises performing a deconvolution of a combination of the measurement spectra set and the training spectra set with the deconvolution kernel weight for each grid node in the first set of grid nodes and the second set of grid nodes to produce the estimated spectrum of the measurement target.

Metadata:
- Claim Count in Document: 2.0
- Percentile: 91.0
- Lexical Diversity: 2.6
- Patent Class: 702.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14505373', '14882370', '14825728', '13767769', '14720644']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.177922296166947
- 35 USC 102 Novelty (BERT): 0.6104347577751907
- Combined Prediction Score: 0.2211735423277714
- Mean Citation Score: 300.996834
- Max Citation Score: 616.165
- Similarity Product: 479.6904147937894

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

Dataset: test