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 Interpretation
MPEP § 2111.01 states that “… Under a broadest reasonable interpretation (BRI), words of the claim must be given their plain meaning, unless such meaning is inconsistent with the specification. The plain meaning of a term means the ordinary and customary meaning given to the term by those of ordinary skill in the art at the relevant time. The ordinary and customary meaning of a term may be evidenced by a variety of sources, including the words of the claims themselves, the specification, drawings, and prior art. However, the best source for determining the meaning of a claim term is the specification - the greatest clarity is obtained when the specification serves as a glossary for the claim terms …”. Thus under a broadest reasonable interpretation, the greatest clarity is obtained when the specification (e.g., see “… an image obtained by compressing an X-ray topographic image taken to 250x250 pixels may be used for learning …” in paragraph 44) serves as a glossary for the claim term “an image obtained by compressing an X-ray topographic image taken to 250x250 pixels may be used for learning”.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned at the time any inventions covered therein were effectively filed absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned at the time a later invention was effectively filed in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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 of this title, 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.
Claim(s) 1, 3, 4, 10, 12-17, and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Buzaglo (US 2021/0334946) in view of Momose et al. (US 2011/0006309) and Konishi et al. (US 2024/0046417).
In regard to claim 1, Buzaglo discloses a method for evaluating a SiC substrate, comprising:
(a) an image acquisition step of acquiring an X-ray topographic image of an entire first surface of a SiC substrate (e.g., “… present disclosure relates to a method and system for classifying defects in wafer using wafer defect images, based on deep learning network … term "surface defects" or "defects" refers to both defects that are located entirely above the upper surface of the wafer (e.g., particles) and defects that are located partially below the upper surface of the wafer or entirely below the upper surface of the wafer. Accordingly, classification of defects can be particularly useful for semiconductor materials such as wafers and materials formed on wafers. Further, distinguishing between surface and subsurface defects could particularly be important for bare silicon wafers, silicon on insulator (SOI) films, strained silicon films, and dielectric films. Embodiments herein can be used to inspect a wafer containing silicon or having a silicon-containing layer formed thereon such as silicon carbide … imaging apparatus 102 can be at least one of, but not limited to … an Automated X-ray Inspection (AXI) apparatus … imaging apparatus 102 may be configured to capture images of the wafer placed in the imaging apparatus 102 …” in paragraphs 2, 33, 34, and 37); and
(b) an estimation step of estimating defects of the SiC substrate from the X-ray topographic image of the entire first surface of the SiC substrate based on learning results of deep learning (e.g., “… imaging apparatus 102 is associated with the electronic device 104 via a communication network 106 … electronic device 104 may include an application management framework for classifying defects in wafer using deep learning network. The application management framework may comprise different modules and sub modules to execute the operation of classifying defects in wafer using wafer defect images, based on deep learning network …” in paragraphs 33 and 35).
The method of Buzaglo lacks an explicit description of details of the “… defects …” such as a basal plane dislocation density and details of the “… training comprises: providing a plurality of labelled images … plurality of labelled images is generated using a labelling model …” (paragraphs 8 and 11) such as an image compression step of compressing the X-ray topographic image acquired in the image acquisition step, wherein, in the image compression step, the pixel size of the X-ray topographic image is 0.1 mm2 or larger, and wherein the estimation step is performed using a compressed X-ray topographic image. However, “… defects …” details are known to one of ordinary skill in the art (e.g., see “… SiC single crystal wafers generally incorporate crystal defects called threading screw dislocations (TSD) and threading edge dislocations (TED), or basal plane dislocations (BPD) … FIG. 18 shows a reflection X-ray topographic photograph of the entire surface of the SiC epitaxial film of an epitaxial SiC single crystal substrate …” in paragraphs 5 and 208 of Momose et al. and “… labelling model …” details are known to one of ordinary skill in the art (e.g., see “… a region to be analyzed with high precision is cut out from an image of the plane of the wafer 9 with coarse precision, pixel information thereof (an average, a median value, a histogram shape, and the like of pixels) is acquired, and a model for multiple regression analysis is created in which the pixel information on the analysis region is used as the explanatory variable and a defect density obtained by the analysis with high precision is used as the objective function …” in paragraph 67 of Konishi et al.). It should be noted that “when a patent claims a structure already known in the prior art that is altered by the mere substitution of one element for another known in the field, the combination must do more than yield a predictable results”. KSR International Co. v. Teleflex Inc., 550 U.S. 398 at 416, 82 USPQ2d 1385 (2007) at 1395 (citing United States v. Adams, 383 U.S. 39, 40 [148 USPQ 479] (1966)). See MPEP § 2143. In this case, one of ordinary skill in the art could have substituted known conventional defects (e.g., comprising details such as “SiC single crystal wafers generally incorporate crystal defects called” “basal plane dislocations (BPD)”) for the unspecified defects of Buzaglo, substituted a known conventional labelling model (e.g., comprising details such as “pixel information” is compressed to “an average” or “an average” as “the explanatory variable” for each “region to be analyzed with high precision”, in order to achieve “a defect density” labelled image using “a model for multiple regression analysis”) for the unspecified labelling model of Buzaglo, and the results of the substitutions would have been predictable. Therefore it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to provide known conventional defects (e.g., comprising details such as a basal plane dislocation density) as the unspecified defects of Buzaglo and to provide known conventional labelling model (e.g., comprising details such as an image compression step of compressing the X-ray topographic image acquired in the image acquisition step, wherein, in the image compression step, the pixel size of the X-ray topographic image is 0.1 mm2 or larger, and wherein the estimation step is performed using a compressed X-ray topographic image) as the unspecified labelling model of Buzaglo.
In regard to claim 3 which is dependent on claim 1, the cited prior art is applied as in claim 1 above. Buzaglo also discloses that further comprising: a preliminary step of measuring respective X-ray topographic images of a plurality of SiC substrates and respective defects of the plurality of SiC substrates, wherein, in the preliminary step, a relationship between the defects and the X-ray topographic images of the respective SiC substrates is learned by the deep learning (e.g., “… imaging apparatus 102 is associated with the electronic device 104 via a communication network 106 … electronic device 104 may include an application management framework for classifying defects in wafer using deep learning network. The application management framework may comprise different modules and sub modules to execute the operation of classifying defects in wafer using wafer defect images, based on deep learning network … imaging apparatus 102 may be configured to capture images of the wafer placed in the imaging apparatus 102 … imaging apparatus 102 may be then configured to store the captured images in the image storage unit 126 … plurality of deep learning models or deep learning classifier may be trained with different types of classification of defects in the wafer … reference images in the training process may lead in faster tuning or training of the deep learning internal parameters … deep learning module 122 trained to classify a specific defect for one wafer may also dynamically classify trained defects if the defects appear in different wafer …” in paragraphs 33, 35, and 37).
In regard to claim 4 which is dependent on claim 3, the cited prior art is applied as in claim 1 above. Buzaglo also discloses that the number of SiC substrates measured in the preliminary step is 100 or more (e.g., “… number of labelled images and the training epochs (i.e. when an entire dataset is passed both forward and backward through the deep learning neural network) required for convergence of the deep learning mode …” in paragraph 5). Alternatively it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to provide a “number of labelled images” (e.g., 200 labelled images) in the method of Buzaglo, in order to achieve “convergence of the deep learning mode”.
In regard to claim 10 which is dependent on claim 3, while Buzaglo also discloses that the SiC substrate to be measured in the preliminary step is different from that of the SiC substrate for which the X-ray topographic image is acquired in the image acquisition step (e.g., “… deep learning module 122 trained to classify a specific defect for one wafer may also dynamically classify trained defects if the defects appear in different wafer …” in paragraph 37), the method of Buzaglo lacks an explicit description of details of the “… different wafer …” such as the substrate’s diameters measured in the preliminary step are different from that of the substrate’s diameter acquired in the image acquisition step. However, “… different wafer …” details are known to one of ordinary skill in the art (e.g., see “… specifies a position and size of a wafer captured in an image from the image of the wafer …” in paragraph 57 of Konishi et al.). It should be noted that “when a patent claims a structure already known in the prior art that is altered by the mere substitution of one element for another known in the field, the combination must do more than yield a predictable results”. KSR International Co. v. Teleflex Inc., 550 U.S. 398 at 416, 82 USPQ2d 1385 (2007) at 1395 (citing United States v. Adams, 383 U.S. 39, 40 [148 USPQ 479] (1966)). See MPEP § 2143. In this case, one of ordinary skill in the art could have substituted a known conventional different wafer (e.g., comprising details such as “image of the wafer” is used to measure “size of a wafer”) for the unspecified different wafer of Buzaglo and the results of the substitution would have been predictable. Therefore it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to provide known conventional different wafer (e.g., comprising details such as the diameters of the SiC substrates to be measured in the preliminary step are different from that of the SiC substrate for which the X-ray topographic image is acquired in the image acquisition step) as the unspecified different wafer of Buzaglo.
In regard to claim 12, Buzaglo discloses a method for manufacturing a SiC substrate (e.g., “… semiconductor substrate (i.e. wafer) fabrication techniques …” in paragraph 3), comprising the method for evaluating a SiC substrate (the cited prior art is applied as in claim 1 above).
In regard to claim 13, Buzaglo discloses a SiC substrate evaluation device comprising:
(a) an input unit, wherein the input unit is configured such that an X-ray topographic image of an entire first surface of a SiC substrate is input thereto (e.g., “… present disclosure relates to a method and system for classifying defects in wafer using wafer defect images, based on deep learning network … term "surface defects" or "defects" refers to both defects that are located entirely above the upper surface of the wafer (e.g., particles) and defects that are located partially below the upper surface of the wafer or entirely below the upper surface of the wafer. Accordingly, classification of defects can be particularly useful for semiconductor materials such as wafers and materials formed on wafers. Further, distinguishing between surface and subsurface defects could particularly be important for bare silicon wafers, silicon on insulator (SOI) films, strained silicon films, and dielectric films. Embodiments herein can be used to inspect a wafer containing silicon or having a silicon-containing layer formed thereon such as silicon carbide … imaging apparatus 102 can be at least one of, but not limited to … an Automated X-ray Inspection (AXI) apparatus … imaging apparatus 102 may be configured to capture images of the wafer placed in the imaging apparatus 102 …” in paragraphs 2, 33, 34, and 37); and
(b) an output unit, wherein the output unit is configured to output a defects of the SiC substrate (e.g., “… imaging apparatus 102 is associated with the electronic device 104 via a communication network 106 … electronic device 104 may include an application management framework for classifying defects in wafer using deep learning network. The application management framework may comprise different modules and sub modules to execute the operation of classifying defects in wafer using wafer defect images, based on deep learning network …” in paragraphs 33 and 35).
The device of Buzaglo lacks an explicit description of details of the “… defects …” such as a basal plane dislocation density and details of the “… training comprises: providing a plurality of labelled images … plurality of labelled images is generated using a labelling model …” (paragraphs 8 and 11) such as to compress the X-ray topographic image such that the pixel size of the X-ray topographic image is 0.1 mm2 or larger, and to estimate the defects using a compressed X-ray topographic image. However, “… defects …” details are known to one of ordinary skill in the art (e.g., see “… SiC single crystal wafers generally incorporate crystal defects called threading screw dislocations (TSD) and threading edge dislocations (TED), or basal plane dislocations (BPD) … FIG. 18 shows a reflection X-ray topographic photograph of the entire surface of the SiC epitaxial film of an epitaxial SiC single crystal substrate …” in paragraphs 5 and 208 of Momose et al. and “… labelling model …” details are known to one of ordinary skill in the art (e.g., see “… a region to be analyzed with high precision is cut out from an image of the plane of the wafer 9 with coarse precision, pixel information thereof (an average, a median value, a histogram shape, and the like of pixels) is acquired, and a model for multiple regression analysis is created in which the pixel information on the analysis region is used as the explanatory variable and a defect density obtained by the analysis with high precision is used as the objective function …” in paragraph 67 of Konishi et al.). It should be noted that “when a patent claims a structure already known in the prior art that is altered by the mere substitution of one element for another known in the field, the combination must do more than yield a predictable results”. KSR International Co. v. Teleflex Inc., 550 U.S. 398 at 416, 82 USPQ2d 1385 (2007) at 1395 (citing United States v. Adams, 383 U.S. 39, 40 [148 USPQ 479] (1966)). See MPEP § 2143. In this case, one of ordinary skill in the art could have substituted known conventional defects (e.g., comprising details such as “SiC single crystal wafers generally incorporate crystal defects called” “basal plane dislocations (BPD)”) for the unspecified defects of Buzaglo, substituted a known conventional labelling model (e.g., comprising details such as “pixel information” is compressed to “an average” or “an average” as “the explanatory variable” for each “region to be analyzed with high precision”, in order to achieve “a defect density” labelled image using “a model for multiple regression analysis”) for the unspecified labelling model of Buzaglo, and the results of the substitutions would have been predictable. Therefore it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to provide known conventional defects (e.g., comprising details such as a basal plane dislocation density) as the unspecified defects of Buzaglo and to provide known conventional labelling model (e.g., comprising details such as the output unit is configured to compress the X-ray topographic image such that the pixel size of the X-ray topographic image is 0.1 mm2 or larger, to estimate a basal plane dislocation density of the SiC substrate using a compressed X-ray topographic image, and to output-a the basal plane dislocation density of the SiC substrate) as the unspecified labelling model of Buzaglo.
In regard to claim 14 which is dependent on claim 13, the cited prior art is applied as in claim 13 above. Buzaglo also discloses a learning unit, wherein the learning unit learns a relationship between respective X-ray topographic images of a plurality of SiC substrates and respective defects of the plurality of SiC substrates (e.g., “… imaging apparatus 102 is associated with the electronic device 104 via a communication network 106 … electronic device 104 may include an application management framework for classifying defects in wafer using deep learning network. The application management framework may comprise different modules and sub modules to execute the operation of classifying defects in wafer using wafer defect images, based on deep learning network … imaging apparatus 102 may be configured to capture images of the wafer placed in the imaging apparatus 102 … imaging apparatus 102 may be then configured to store the captured images in the image storage unit 126 associated with the imaging apparatus 102 … plurality of deep learning models or deep learning classifier may be trained with different types of classification of defects in the wafer … reference images in the training process may lead in faster tuning or training of the deep learning internal parameters … deep learning module 122 trained to classify a specific defect for one wafer may also dynamically classify trained defects if the defects appear in different wafer …” in paragraphs 33, 35, and 37).
In regard to claim 15 which is dependent on claim 14, the cited prior art is applied as in claim 13 above. Buzaglo also discloses that the learning unit is configured to learn through deep learning (e.g., “… imaging apparatus 102 is associated with the electronic device 104 via a communication network 106 … electronic device 104 may include an application management framework for classifying defects in wafer using deep learning network. The application management framework may comprise different modules and sub modules to execute the operation of classifying defects in wafer using wafer defect images, based on deep learning network … imaging apparatus 102 may be configured to capture images of the wafer placed in the imaging apparatus 102 … imaging apparatus 102 may be then configured to store the captured images in the image storage unit 126 associated with the imaging apparatus 102 … plurality of deep learning models or deep learning classifier may be trained with different types of classification of defects in the wafer … reference images in the training process may lead in faster tuning or training of the deep learning internal parameters … deep learning module 122 trained to classify a specific defect for one wafer may also dynamically classify trained defects if the defects appear in different wafer …” in paragraphs 33, 35, and 37).
In regard to claim 16 which is dependent on claim 13, the cited prior art is applied as in claim 13 above. Buzaglo also discloses a memory, wherein the memory is inside the evaluation device or on a server outside the evaluation device, and wherein the memory stores measured data of X-ray topographic images of entire first surfaces of a plurality of SiC substrates and defects of the plurality of SiC substrates (e.g., “… imaging apparatus 102 is associated with the electronic device 104 via a communication network 106 … electronic device 104 may include an application management framework for classifying defects in wafer using deep learning network. The application management framework may comprise different modules and sub modules to execute the operation of classifying defects in wafer using wafer defect images, based on deep learning network … imaging apparatus 102 may be configured to capture images of the wafer placed in the imaging apparatus 102 … imaging apparatus 102 may be then configured to store the captured images in the image storage unit 126 associated with the imaging apparatus 102 … plurality of deep learning models or deep learning classifier may be trained with different types of classification of defects in the wafer … reference images in the training process may lead in faster tuning or training of the deep learning internal parameters … deep learning module 122 trained to classify a specific defect for one wafer may also dynamically classify trained defects if the defects appear in different wafer …” in paragraphs 33, 35, and 37).
In regard to claim 17 which is dependent on claim 14, the cited prior art is applied as in claim 13 above. Buzaglo also discloses that the learning unit has a learning program, and wherein the learning program learns the correlation between the respective X-ray topographic images of the plurality of SiC substrates and the respective defects of the plurality of SiC substrates through deep learning (e.g., “… imaging apparatus 102 is associated with the electronic device 104 via a communication network 106 … electronic device 104 may include an application management framework for classifying defects in wafer using deep learning network. The application management framework may comprise different modules and sub modules to execute the operation of classifying defects in wafer using wafer defect images, based on deep learning network … imaging apparatus 102 may be configured to capture images of the wafer placed in the imaging apparatus 102 … imaging apparatus 102 may be then configured to store the captured images in the image storage unit 126 associated with the imaging apparatus 102 … plurality of deep learning models or deep learning classifier may be trained with different types of classification of defects in the wafer … reference images in the training process may lead in faster tuning or training of the deep learning internal parameters … deep learning module 122 trained to classify a specific defect for one wafer may also dynamically classify trained defects if the defects appear in different wafer …” in paragraphs 33, 35, and 37).
In regard to claim 19 which is dependent on claim 14, the cited prior art is applied as in claim 13 above. While Buzaglo also discloses at least one of the plurality of SiC substrates used for learning by the learning unit is different from that of the SiC substrate used for obtaining the X-ray topographic image to be input to the input unit (e.g., “… deep learning module 122 trained to classify a specific defect for one wafer may also dynamically classify trained defects if the defects appear in different wafer …” in paragraph 37), the device of Buzaglo lacks an explicit description of details of the “… different wafer …” such as at least one substrate’s diameter used for learning is different from that a substrate’s diameter used for input. However, “… different wafer …” details are known to one of ordinary skill in the art (e.g., see “… specifies a position and size of a wafer captured in an image from the image of the wafer …” in paragraph 57 of Konishi et al.). It should be noted that “when a patent claims a structure already known in the prior art that is altered by the mere substitution of one element for another known in the field, the combination must do more than yield a predictable results”. KSR International Co. v. Teleflex Inc., 550 U.S. 398 at 416, 82 USPQ2d 1385 (2007) at 1395 (citing United States v. Adams, 383 U.S. 39, 40 [148 USPQ 479] (1966)). See MPEP § 2143. In this case, one of ordinary skill in the art could have substituted a known conventional different wafer (e.g., comprising details such as “image of the wafer” is used to measure “size of a wafer”) for the unspecified different wafer of Buzaglo and the results of the substitution would have been predictable. Therefore it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to provide known conventional different wafer (e.g., comprising details such as the diameter of at least one of the plurality of SiC substrates used for learning by the learning unit is different from that of the SiC substrate used for obtaining the X-ray topographic image to be input to the input unit) as the unspecified different wafer of Buzaglo.
Claim(s) 5 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Buzaglo in view of Momose et al. and Konishi et al. as applied to claim(s) 3 and 14 above, and further in view of Ophir et al. (US 2021/0142466).
In regard to claim 5 which is dependent on claim 3, while Buzaglo also discloses (paragraph 37) that “… images may include at least one of the images such as inspection images, optical or electron beam images, wafer inspection images, optical and SEM based defect review images, simulated images, clips from a design layout, and so on …”, the method of Buzaglo lacks an explicit description of details of the “… images …” such as inverted or rotated images of the X-ray topographic images acquired in the preliminary step are used for the learning. However, “… images …” details are known to one of ordinary skill in the art (e.g., see “… illumination technology may comprise, electromagnetic radiation in the visual range, ultraviolet or even shorter wave radiation such as x rays, and possibly even particle beams … training data using pairs of images and 180° - rotated images derived from a plurality of sites on at least one training wafer …” in paragraphs 13 and 24 of Ophir et al.). It should be noted that “when a patent claims a structure already known in the prior art that is altered by the mere substitution of one element for another known in the field, the combination must do more than yield a predictable results”. KSR International Co. v. Teleflex Inc., 550 U.S. 398 at 416, 82 USPQ2d 1385 (2007) at 1395 (citing United States v. Adams, 383 U.S. 39, 40 [148 USPQ 479] (1966)). See MPEP § 2143. In this case, one of ordinary skill in the art could have substituted a known conventional image (e.g., comprising details such as “training data using pairs of images and 180° - rotated images”) for the unspecified image of Buzaglo and the results of the substitution would have been predictable. Therefore it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to provide known conventional image (e.g., comprising details such as inverted or rotated images of the X-ray topographic images acquired in the preliminary step are used for the learning) as the unspecified image of Buzaglo.
In regard to claim 18 which is dependent on claim 14, the cited prior art is applied as in claim 13 above. While Buzaglo also discloses (paragraph 37) that “… images may include at least one of the images such as inspection images, optical or electron beam images, wafer inspection images, optical and SEM based defect review images, simulated images, clips from a design layout, and so on …”, the device of Buzaglo lacks an explicit description of details of the “… images …” such as the learning unit learns using inverted or rotated images of at least one of the respective X-ray topographic images of the plurality of SiC substrates. However, “… images …” details are known to one of ordinary skill in the art (e.g., see “… illumination technology may comprise, electromagnetic radiation in the visual range, ultraviolet or even shorter wave radiation such as x rays, and possibly even particle beams … training data using pairs of images and 180° - rotated images derived from a plurality of sites on at least one training wafer …” in paragraphs 13 and 24 of Ophir et al.). It should be noted that “when a patent claims a structure already known in the prior art that is altered by the mere substitution of one element for another known in the field, the combination must do more than yield a predictable results”. KSR International Co. v. Teleflex Inc., 550 U.S. 398 at 416, 82 USPQ2d 1385 (2007) at 1395 (citing United States v. Adams, 383 U.S. 39, 40 [148 USPQ 479] (1966)). See MPEP § 2143. In this case, one of ordinary skill in the art could have substituted a known conventional image (e.g., comprising details such as “training data using pairs of images and 180° - rotated images”) for the unspecified image of Buzaglo and the results of the substitution would have been predictable. Therefore it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to provide known conventional image (e.g., comprising details such as the learning unit learns using inverted or rotated images of at least one of the respective X-ray topographic images of the plurality of SiC substrates) as the unspecified image of Buzaglo.
Claim(s) 6-9 and 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Buzaglo in view of Momose et al. and Konishi et al. as applied to claim(s) 1 above, and further in view of Gunjishima et al. (US 2014/0291700).
In regard to claim 6 which is dependent on claim 1, while Buzaglo also discloses that (e.g., “… imaging apparatus 102 can be at least one of, but not limited to, an Automated Optical Inspection (AOI) apparatus, an Automated X-ray Inspection (AXI) apparatus, a Joint Test Action Group (JTAG) apparatus, an In-circuit test (ICT) apparatus, and so on …” in paragraph 34), the device of Buzaglo lacks an explicit description of details of the “… Automated X-ray Inspection (AXI) apparatus …” such as the X-ray topographic image is a diffraction image containing a diffraction vector in the <11-20> direction. However, “… Automated X-ray Inspection (AXI) apparatus …” details are known to one of ordinary skill in the art (e.g., see “… applying X-ray topography (FIG. 3) of transmission arrangement, which is sensitive to an inner structure of a crystal, to a substrate nearly parallel to a c-plane (wafer A) and a substrate nearly parallel to a threading direction ( direction vertical to a basal plane) (wafer B); and computing a dislocation density … Dislocations each of which has a Burgers vector in a {0001} in-plane direction (mainly a direction parallel to a <11-20> direction) are projected to a {1-100} plane diffraction image of a wafer A … sum the respective total lengths of the basal plane dislocations obtained from a (1-100) plane diffraction image, a (-1010) plane diffraction image, and a (01-10) plane diffraction image, those being crystallographically-equivalent three diffraction images … it is also possible to use {11-20} plane diffraction for the measurement of a wafer A. On this occasion, all the basal plane dislocations are detected…” in paragraphs 76, 91, 94, and 95 of Gunjishima et al.). It should be noted that “when a patent claims a structure already known in the prior art that is altered by the mere substitution of one element for another known in the field, the combination must do more than yield a predictable results”. KSR International Co. v. Teleflex Inc., 550 U.S. 398 at 416, 82 USPQ2d 1385 (2007) at 1395 (citing United States v. Adams, 383 U.S. 39, 40 [148 USPQ 479] (1966)). See MPEP § 2143. In this case, one of ordinary skill in the art could have substituted a known conventional X-ray apparatus (e.g., comprising details such as “{11-20} plane diffraction” and/or “{1-100} plane diffraction image” for “computing a dislocation density”) for the unspecified X-ray apparatus of Buzaglo and the results of the substitution would have been predictable. Therefore it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to provide known conventional X-ray apparatus (e.g., comprising details such as the X-ray topographic image is a diffraction image containing a diffraction vector in the <11-20> direction) as the unspecified X-ray apparatus of Buzaglo.
In regard to claim 7 which is dependent on claim 1, while Buzaglo also discloses that (e.g., “… imaging apparatus 102 can be at least one of, but not limited to, an Automated Optical Inspection (AOI) apparatus, an Automated X-ray Inspection (AXI) apparatus, a Joint Test Action Group (JTAG) apparatus, an In-circuit test (ICT) apparatus, and so on …” in paragraph 34), the device of Buzaglo lacks an explicit description of details of the “… Automated X-ray Inspection (AXI) apparatus …” such as the X-ray topographic image is a diffraction image containing a diffraction vector in the <1-100> direction. However, “… Automated X-ray Inspection (AXI) apparatus …” details are known to one of ordinary skill in the art (e.g., see “… applying X-ray topography (FIG. 3) of transmission arrangement, which is sensitive to an inner structure of a crystal, to a substrate nearly parallel to a c-plane (wafer A) and a substrate nearly parallel to a threading direction ( direction vertical to a basal plane) (wafer B); and computing a dislocation density … Dislocations each of which has a Burgers vector in a {0001} in-plane direction (mainly a direction parallel to a <11-20> direction) are projected to a {1-100} plane diffraction image of a wafer A … sum the respective total lengths of the basal plane dislocations obtained from a (1-100) plane diffraction image, a (-1010) plane diffraction image, and a (01-10) plane diffraction image, those being crystallographically-equivalent three diffraction images … it is also possible to use {11-20} plane diffraction for the measurement of a wafer A. On this occasion, all the basal plane dislocations are detected…” in paragraphs 76, 91, 94, and 95 of Gunjishima et al.). It should be noted that “when a patent claims a structure already known in the prior art that is altered by the mere substitution of one element for another known in the field, the combination must do more than yield a predictable results”. KSR International Co. v. Teleflex Inc., 550 U.S. 398 at 416, 82 USPQ2d 1385 (2007) at 1395 (citing United States v. Adams, 383 U.S. 39, 40 [148 USPQ 479] (1966)). See MPEP § 2143. In this case, one of ordinary skill in the art could have substituted a known conventional X-ray apparatus (e.g., comprising details such as “{11-20} plane diffraction” and/or “{1-100} plane diffraction image” for “computing a dislocation density”) for the unspecified X-ray apparatus of Buzaglo and the results of the substitution would have been predictable. Therefore it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to provide known conventional X-ray apparatus (e.g., comprising details such as the X-ray topographic image is a diffraction image containing a diffraction vector in the <1-100> direction) as the unspecified X-ray apparatus of Buzaglo.
In regard to claim 8 which is dependent on claim 1, the device of Buzaglo lacks an explicit description of details of the “… different wafer …” such as the SiC substrate has a diameter of 145 mm or more. However, “… different wafer …” details are known to one of ordinary skill in the art (e.g., see “… SiC wafer having not only a high quality but also a large diameter is obtained. Specifically, by optimizing manufacturing conditions, a high quality SiC wafer having a diameter of not less than 7.5 cm, not less than 10 cm, or not less than 15 cm is obtained …” in paragraph 184 of Gunjishima et al.). It should be noted that “when a patent claims a structure already known in the prior art that is altered by the mere substitution of one element for another known in the field, the combination must do more than yield a predictable results”. KSR International Co. v. Teleflex Inc., 550 U.S. 398 at 416, 82 USPQ2d 1385 (2007) at 1395 (citing United States v. Adams, 383 U.S. 39, 40 [148 USPQ 479] (1966)). See MPEP § 2143. In this case, one of ordinary skill in the art could have substituted a known conventional different wafer (e.g., comprising details such as “high quality SiC wafer having a diameter of not less than 7.5 cm, not less than 10 cm, or not less than 15 cm”) for the unspecified different wafer of Buzaglo and the results of the substitution would have been predictable. Therefore it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to provide known conventional different wafer (e.g., comprising details such as the SiC substrate has a diameter of 145 mm or more) as the unspecified different wafer of Buzaglo.
In regard to claim 9 which is dependent on claim 1, the device of Buzaglo lacks an explicit description of details of the “… different wafer …” such as the SiC substrate has a diameter of 195 mm or more. However, “… different wafer …” details are known to one of ordinary skill in the art (e.g., see “… SiC wafer having not only a high quality but also a large diameter is obtained. Specifically, by optimizing manufacturing conditions, a high quality SiC wafer having a diameter of not less than 7.5 cm, not less than 10 cm, or not less than 15 cm is obtained …” in paragraph 184 of Gunjishima et al.). It should be noted that “when a patent claims a structure already known in the prior art that is altered by the mere substitution of one element for another known in the field, the combination must do more than yield a predictable results”. KSR International Co. v. Teleflex Inc., 550 U.S. 398 at 416, 82 USPQ2d 1385 (2007) at 1395 (citing United States v. Adams, 383 U.S. 39, 40 [148 USPQ 479] (1966)). See MPEP § 2143. In this case, one of ordinary skill in the art could have substituted a known conventional different wafer (e.g., comprising details such as “high quality SiC wafer having a diameter of not less than 7.5 cm, not less than 10 cm, or not less than 15 cm”) for the unspecified different wafer of Buzaglo and the results of the substitution would have been predictable. Therefore it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to provide known conventional different wafer (e.g., comprising details such as the SiC substrate has a diameter of 195 mm or more) as the unspecified different wafer of Buzaglo.
In regard to claim 11 which is dependent on claim 1, the method of Buzaglo lacks an explicit description of details of the “… defects …” such as the basal plane dislocation density of the SiC substrate is 1.0×104/cm2 or less. However, “… defects …” details are known to one of ordinary skill in the art (e.g., see “… wafer having a basal plane dislocation density of 10,000 pieces/cm2 … it is difficult to manufacture a high-performance SiC device by using such a crystal …” in paragraph 7 of Gunjishima et al.). It should be noted that “when a patent claims a structure already known in the prior art that is altered by the mere substitution of one element for another known in the field, the combination must do more than yield a predictable results”. KSR International Co. v. Teleflex Inc., 550 U.S. 398 at 416, 82 USPQ2d 1385 (2007) at 1395 (citing United States v. Adams, 383 U.S. 39, 40 [148 USPQ 479] (1966)). See MPEP § 2143. In this case, one of ordinary skill in the art could have substituted a known conventional defects (e.g., comprising details such as “wafer having a basal plane dislocation density of 10,000 pieces/cm2” “it is difficult to manufacture a high-performance SiC device”) for the unspecified defects of Buzaglo and the results of the substitution would have been predictable. Therefore it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to provide known conventional defects (e.g., comprising details such as the basal plane dislocation density of the SiC substrate is 1.0×104/cm2 or less) as the unspecified defects of Buzaglo.
Allowable Subject Matter
Claim(s) 20 and 21 is/are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter: the instant application is deemed to be directed to a nonobvious improvement over the invention disclosed in US 2021/0334946. The improvement comprises in combination with other recited elements: (a) wherein the learning results include a relationship between respective X-ray topographic images of a plurality of SiC substrates and respective basal plane dislocation densities of the plurality of SiC substrates, and data on which position in a SiC ingot each of the plurality of SiC substrates is cut from; and (b) wherein the output unit is configured to estimate the basal plane dislocation density of the SiC substrate using the compressed X-ray topographic image based on learning results of deep learning, and the learning results include a relationship between respective X-ray topographic images of a plurality of SiC substrates and respective basal plane dislocation densities of the plurality of SiC substrates, and data on which position in a SiC ingot each of the plurality of SiC substrates is cut from.
Response to Arguments
Applicant’s arguments with respect to the amended and new claims have been fully considered but some are moot in view of the new ground(s) of rejection. Applicant's remaining arguments filed 27 May 2026 have been fully considered but they are not persuasive.
Applicant argues that the present invention’s method for evaluating a SiC substrate is not obvious from Buzaglo, Momose et al., Konishi et al., Ophir et al., and Gunjishima et al. because a region cut out from a coarse precision image is analyzed with high precision in Konishi et al. and thus Konishi et al. teach away from the present invention’s image compression, and the present invention’s image compression step effects are not obvious from Konishi et al. In response to applicant's argument that the references fail to show certain features of applicant’s invention, it is noted that the features upon which applicant relies (i.e., an estimation step of estimating defects of the SiC substrate from the compressed X-ray topographic image of the entire first surface of the SiC substrate based on learning results of deep learning) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). Further as discussed above, the specification (e.g., see “… an image obtained by compressing an X-ray topographic image taken to 250x250 pixels may be used for learning …” in paragraph 44) serves as a glossary for the claim term “an image obtained by compressing an X-ray topographic image taken to 250x250 pixels may be used for learning”. Therefore, it is important to recognize that the scope of the limitation “wherein the estimation step is performed using a compressed X-ray topographic image” comprises any usage such as using “a compressed X-ray topographic image” as training data.
Applicant argues that the SiC substrate evaluation device of the present invention is not obvious from Buzaglo, Momose et al., Konishi et al., Ophir et al., and Gunjishima et al. Examiner respectfully disagrees for the reasons discussed above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 2020/0365685 teaches x-ray topography.
US 2022/0025546 teaches x-ray for aligning crystal lattice plane orientation.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/SL/
Examiner, Art Unit 2884
/UZMA ALAM/Supervisory Patent Examiner, Art Unit 2884
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