PATENT CLAIM ANALYSIS

Application Number: 16090032
Application Type: Utility
Filing Date: 2018-09
Publication Date: 2019-04
Patent Classification: ["355", "077000"]

Abstract:
A light intensity modulation method implemented by using a mask ( 101 ) includes the steps of: 1) based on a circle of confusion (CoC) function of an illumination system ( 102 ), an initial light intensity distribution of an illumination field of view (FOV) and a target light intensity distribution of the illumination FOV, calculating a transmittance distribution of the mask ( 101 ) used to modulate the initial light intensity distribution into the target light intensity distribution; 2) meshing the mask ( 101 ) according to a desired accuracy of the target light intensity distribution and determining a distribution of opaque dots in each of cells resulting from the meshing based on the transmittance distribution of the mask ( 101 ) and a desired accuracy of the transmittance distribution; and 3) fabricating the mask ( 101 ) based on the determined distribution of the opaque dots and then deploying the mask ( 101 ) in the illumination system. Advantages including a high modulation accuracy, an applicability to wide FOV size, light intensity and wavelength ranges and compatibility with established manufacturing processes can be attained.

Claim (Index 5):
The light intensity modulation method according to  claim 1 , wherein the opaque dots are implemented as chrome dots.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 97.0
- Lexical Diversity: 2.55696
- Patent Class: 355.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['11136404', '10624555', '10603821', '13509642', '13366829']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6687745804517395
- 35 USC 102 Novelty (BERT): 0.480485972801238
- Combined Prediction Score: 0.6499457196866893
- Mean Citation Score: 177.89332199999996
- Max Citation Score: 184.06204
- Similarity Product: 126.97595026941536

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

Dataset: test