DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
It is noted that claims 1-13 are considered eligible subject matter. The claims are not drawn to an abstract idea, but even if one could interpret the claims as an abstract idea, the claims make use of a particular machine, i.e. a interferometer.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 3, 4, 6, 9 and 11 are rejected under 35 U.S.C. 103(a) as being unpatentable over U.S. Patent Application Publication No. 2021003386 (Liu et al) in view of translation of CN115900582A (Liu, II et al).
Regarding claim 1, Liu et al discloses An interferometer (fig. 2) comprising: a light source (fig. 2, item 104) that generates a beam of light (fig. 2, item 101); a beam splitter in a path of the beam of light (fig. 2, item 106); a reference flat (fig. 2, item 114) in a path of the beam of light from the beam splitter (fig. 2, light from item 106); a stage (page 2, paragraph 24) configured to hold a workpiece (fig. 2, item 103) in a path of the beam of light from the beam splitter (fig. 2, path from item 106); a detector configured to receive light from the workpiece (fig. 2, item 119); and a processor (fig. 2, item 124) in electronic communication with the detector (fig. 2, communication line between 120 and 122), wherein the processor is configured to perform phase unwrapping procedures from an image generated using information from the detector (fig. 5, item 508 from item 502).
Liu et al does not disclose expressly performing phase unwrapping comprises running a neural network that removes phase error.
Liu et al, II discloses performing phase unwrapping comprises running a neural network that removes phase error (page 7, n0060).
Liu et al and Liu et all, II are combinable because they are from the same field of endeavor, i.e. interferograms.
Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to use a neural network to remove phase error.
The suggestion/motivation for doing so would have been to provide a more robust system by using an adaptable model for calculating error.
Therefore, it would have been obvious to combine the interferometer of Liu et al with neural network of Liu et al, II to obtain the invention as specified in claim 1.
Regarding claim 3, Liu et al discloses the workpiece is a semiconductor wafer (page 2, paragraph 22).
Regarding claim 4, Liu et al discloses a method comprising: disposing a workpiece (fig. 2,item 103) on a stage (page 2, paragraph 24) in an interferometer (fig. 2); taking measurements of the workpiece using the interferometer (fig. 5, item 502); and generating an image of a surface of the workpiece from the measurements, i.e. a phase map with pixels (fig. 5, item 504) using a processor (fig. 2, item 124); and removing phase error from the image with phase unwrapping (fig. 5, item 508) operated using the processor (fig. 2, item 124). Liu et al, II discloses performing phase unwrapping comprises running a neural network that removes phase error (page 7, n0060).
Regarding claim 6, Liu et al discloses the workpiece is a semiconductor wafer (page 2, paragraph 22).
Regarding claim 9, Liu et al discloses a non-transitory computer-readable storage medium (fig. 2, item 126), comprising one or more programs for executing the following steps on one or more computing devices (fig. 2, item 122) comprising: receiving information about a surface of a workpiece from an interferometer (fig. 5, item 502); generating an image of the surface of the workpiece using the information (fig. 2, item 504); and removing phase error from the image by phase unwrapping (fig. 5, item 508). Liu et al, II discloses performing phase unwrapping comprises running a neural network that removes phase error (page 7, n0060).
Regarding claim 11, Liu et al discloses the workpiece is a semiconductor wafer (page 2, paragraph 22).
Claims 2, 5 and 10 are rejected under 35 U.S.C. 103(a) as being unpatentable over Liu et al in view of Liu et al, II as applied to claims 1, 4, and 9 above, and further in view of U.S. Patent Application Publication No. 20190355347 (Arik et al)
Regarding claim 2, Liu et al (as modified by Liu et al, II) discloses all of the claimed elements as set forth above and incorporated herein by reference.
Liu et al (as modified by Liu et al, II) does not disclose expressly the neural network is a generative adversarial network; instead Liu et al, II discloses using a convolutional network (page 7, n0064).
Arik et al discloses a neural network is a convolutional network GAN (page 7, paragraph 100).
Liu et al (as modified by Liu et al, II) & Arik et al are combinable because they are from the same field of endeavor, i.e. using neural networks with waveforms.
Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to use a GAN.
The suggestion/motivation for doing so would have been to provide a more robust method by testing the system.
Therefore, it would have been obvious to combine Liu et al (as modified by Liu et al, II) with the use of GAN of Arik et al to obtain the invention as specified in claim 2.
Claims 5 and 10 are rejected for the same reasons as claim 2. Thus, the arguments analogous to that presented above for claim 2 are equally applicable to claims 5 and 10. Claims 5 and 10 distinguish from claim 2 only in that they have different dependencies, both of which have been previously rejected. Therefore, prior art applies.
Claims 7, 8, 12 and 13 are rejected under 35 U.S.C. 103(a) as being unpatentable over Liu et al in view of Liu et al, II as applied to claims 4 and 9 above, and further in view of U.S. Patent Application Publication No. 20230014823 (Cheng et al).
Regarding claim 7, Liu et al (as modified by Liu et al, II) discloses all of the claimed elements as set forth above and incorporated herein by reference.
Liu et al (as modified by Liu et al, II) does not disclose expressly the neural network is trained using examples of two thickness maps superimposed on each other.
Cheng et al discloses the neural network is trained using examples of two thickness maps superimposed on each other, i.e. two mapping of defects with different thicknesses (page 6, paragraph 90).
Liu et al (as modified by Liu et al, II) & Chang et al are combinable because they are from the same field of endeavor, i.e. training images for neural networks.
Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to combine image with different thicknesses for training.
The suggestion/motivation for doing so would have been to provide a more robust method by creating more training examples
Therefore, it would have been obvious to combine Liu et al (as modified by Liu et al, II) with the superimposing of Cheng et al to obtain the invention as specified in claim 7.
Regarding claim 8, Cheng et al the examples are measured using different tools, i.e. the different tools used in page 7, paragraph 104.
Claim 12 is rejected for the same reasons as claim 7. Thus, the arguments analogous to that presented above for claim 7 are equally applicable to claim 12. Claim 12 distinguishes from claim 7 only in that they have different dependencies, both of which have been previously rejected. Therefore, prior art applies.
Claim 13 is rejected for the same reasons as claim 8. Thus, the arguments analogous to that presented above for claim 8 are equally applicable to claim 13. Claim 13 distinguishes from claim 8 only in that they have different dependencies, both of which have been previously rejected. Therefore, prior art applies.
Conclusion
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/KATHLEEN Y DULANEY/Primary Examiner, Art Unit 2666 12/17/2025
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