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 Objections
Claim 10 is objected to because of the following informalities.
Claim 10 reads as follows:
10. The system of claim 9, wherein weights of the trained algorithm are determined through training using the reference data and (i) key X-ray emissions parameters, which are derived from X-ray emission data sets of other patterned wafers samples of the same intended design as the inspected patterned wafer, and/or (ii) simulation data, which are derived from simulating impinging of patterned wafers of the same intended design as the inspected patterned wafer with e-beams at each of a plurality of landing energies.
The claim amendments, filed on 2/19/2026, appear to have replaced the words sample and samples with patterned wafer and patterned wafers. The remaining sample terms have been removed from the claim language except for the singular bolded samples term highlighted above. This appears to be grammatically incorrect and believed to be a typo, and should be removed from the claim language to improve the clarity of the clamed invention, as the claim does not previously discuss pattern wafers samples.
Appropriate correction is required.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-3, 6-9, and 13 are rejected on the ground of nonstatutory double patenting as being unpatentable over the claims of U.S. Patent No. 12480898. Although the claims at issue are not identical, they are not patentably distinct from each other.
Current Application 18231567
1. A system for non-destructive depth-profiling of patterned wafers, the system comprising:
an electron beam (e-beam) source configured to project e-beams on an inspected patterned wafer at a plurality of landing energies and at a plurality of lateral locations within a profiled region of the patterned wafer that includes lateral non-uniformity, the e-beams inducing X-ray emitting interactions within respective probed volumes whose depth varies according to the landing energy;
an X-ray sensor configured to measure the emitted X-rays to obtain X-ray emission data sets pertaining to each of the probed volumes, each associated with the landing energy and the lateral location of the inducing e-beam; and
processing circuitry configured to determine a set of structural parameters, which characterizes an internal geometry and/or a composition at a lateral location and depth within the inspected patterned wafer, based on the measured optical X-ray emission data sets and taking into account reference data indicative of an intended design of the inspected patterned wafer.
2. The system of claim 1, wherein the reference data comprise design data of the inspected patterned wafer and/or ground truth (GT) data of other patterned wafers of the same intended design as the inspected patterned wafer and/or GT data of especially prepared patterned wafers exhibiting selected variations with respect to the intended design.
3. The system of claim 1, wherein the set of structural parameters specifies a concentration map quantifying a dependence of a concentration of a target material, which the inspected patterned wafer comprises, on the depth and the lateral location.
6. The system of claim 1, wherein the X-ray sensor is configured to measure an intensity of at least a portion of the respectively emitted X-rays, which has a frequency equal to, or within a frequency range about, a peak characteristic X-ray emission frequency of a target material, which the inspected patterned wafer comprises.
7. The system of claim 6, wherein the X-ray sensor comprises an energy-dispersive X-ray spectrometer or a wavelength-dispersive X-ray spectrometer.
8. The system of claim 3, further configured to allow projecting the e-beams so as to impinge on the inspected patterned wafer at each of controllably selectable lateral locations thereon; and wherein the concentration map is three-dimensional.
9. The system of claim 1, wherein, in order to determine the set of structural parameters, the processing circuitry is configured to execute a trained algorithm, which is configured to receive as inputs key X-ray emission parameters extracted from the X-ray emission data sets.
13. A computer-based method for non-destructive depth-profiling of patterned wafers, the method comprising:
a measurement operation comprising, for each of a plurality of landing energies, selected so as to allow probing an inspected patterned wafer to a plurality of depths, and at a plurality of lateral locations within a profiled region of the patterned wafer that includes lateral non-uniformity, suboperations of:
projecting an electron beam (e-beam) on the inspected patterned wafer at the lateral location, which induces X-ray light-emitting interactions within a respective probed volume of the inspected patterned wafer, whose depth is determined by the landing energy; and
measuring the emitted X-rays to obtain an X-ray emission data set pertaining to the probed volume associated with the corresponding landing energy and lateral location of the inducing e-beam; and
a data analysis operation comprising determining a set of structural parameters, which characterizes an internal geometry and/or a composition at a lateral location and depth within the inspected patterned wafer, based on the measured X-ray emission data sets and taking into account reference data indicative of an intended design of the inspected patterned wafer.
US 12480898
1. A system for non-destructive depth-resolved profiling of patterned wafers, the system comprising:
an electron beam (e-beam) source configured to project e-beams on a patterned wafer at a plurality of landing energies and at a plurality of lateral locations within a profiled region of the patterned wafer that includes lateral non-uniformity, the e-beams inducing X-ray-emitting interactions within respective probed volumes, whose depth varies according to the landing energy;
an X-ray sensing module configured to detect X-rays emitted from the patterned wafer and to generate X-ray emission data sets for the probed volumes, each associated with the landing energy and the lateral location of the inducing e-beam; and
a computational module configured to generate, based on the X-ray emission data sets, a depth-resolved concentration map that quantifies a dependence of a concentration of a profiled material within the profiled region on depth and one or more lateral coordinates, wherein the computational module is configured to execute an algorithm that employs or is at least partially derived from simulated X-ray emission data generated by computer simulation of X-ray emissions predicted for e-beams of varying landing energies incident at a plurality of locations according to intended-design data for the profiled region.
(see claim 1 above utilizes intended-design data)
See also 15. The system of claim 1, wherein the computational module is further configured to use intended-design data of the profiled region as an input when generating the concentration map.
(see claim 1 above: a computational module configured to generate, based on the X-ray emission data sets, a depth-resolved concentration map that quantifies a dependence of a concentration of a profiled material within the profiled region on depth and one or more lateral coordinates)
2. The system of claim 1, wherein the X-ray sensing module is configured to measure an intensity of at least a portion of the respectively emitted X-rays, which have a frequency equal to, or within a frequency range about, a peak characteristic X-ray emission frequency of the profiled material.
3. The system of claim 2, wherein the X-ray sensing module comprises an energy-dispersive X-ray spectrometer or a wavelength-dispersive X-ray spectrometer.
(see claim 1 above, discusses that the e-beam source is configured to project e-beams on the patterned wafer at a plurality of lateral locations)
Also see claim 6. The system of claim 1, wherein the concentration map is three-dimensional and quantifies the dependence of the concentration of the profiled material on depth and two lateral coordinates.
4. The system of claim 1, wherein the computational module is configured to execute a machine-learning derived algorithm trained at least in part using the simulated X-ray emission data, whose output is the concentration map and whose inputs comprise the X-ray emission data sets, each labeled by the respective landing energy.
17. A computer-implemented method for non-destructive depth-resolved profiling of patterned wafers, the method comprising:
for each of a plurality of landing energies and for each of a plurality of lateral locations within a profiled region of the patterned wafer that includes lateral non-uniformity:
(see below: projection incudes various depth and lateral locations of a profiled material region)
projecting an electron beam (e-beam) to induce X-ray-emitting interactions within a respective probed volume whose depth varies according to the landing energy; and (see above wafer is a patterned wafer)
detecting emitted X-rays to obtain an X-ray emission data set labeled by the landing energy and the lateral location; and (see above: discusses probed volume)
generating, based at least on the X-ray emission data sets, a depth-resolved concentration map that quantifies a dependence of a concentration of a profiled material within the profiled region on depth and one or more lateral coordinates, wherein generating the concentration map comprises executing an algorithm that employs or is at least partially derived from simulated X-ray emission data generated by computer simulation of X-ray emissions predicted for e-beams of varying landing energies incident at a plurality of locations according to intended-design data for the profiled region.
Claims 4 is rejected on the ground of nonstatutory double patenting as being unpatentable over the claims of U.S. Patent No. 12480898 in view of Jambunathan (US 20200411513).
Regarding claim 4, U.S. Patent No. 12480898 does not expressly claim wherein the inspected patterned wafer comprises a bulk into which the target material has been introduced, and wherein the bulk is or comprises a semiconductor structure; and/or wherein the target material comprises fluorine, nitrogen, boron, and/or gallium.
Jambunathan discloses wherein the inspected patterned wafer comprises a bulk into which the target material has been introduced, and wherein the bulk is or comprises a semiconductor structure; and/or wherein the target material comprises fluorine, nitrogen, boron, and/or gallium (see Abstract and paragraphs 0021-0022: silicon bulk, discloses materials being evaluated such as gallium, boron, nitrogen, and fluorine; and see paragraph 0021, 0023, 0026, and 0047-0047: discusses patterning process on a substrate/wafer and substrate being imaged using EDX spectroscopy).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the claims of U.S. Patent No. 12480898 with the teachings of Jambunathan, evaluating substrate samples to determine concentrations of the disclosed elements, to see if the substrate has been correctly manufactured, incorrectly manufactured, or damaged during manufacturing.
Claims 5 is rejected on the ground of nonstatutory double patenting as being unpatentable over the claims of U.S. Patent No. 12480898 in view of Campbell (US 9625398).
Regarding claim 5, U.S. Patent No. 12480898 does not expressly claim wherein the set of structural parameters comprises one or more of:
one or more overall concentrations of one or more materials, respectively, that the inspected patterned wafer comprises; and
at least one width of at least one structure, respectively, which is embedded in the inspected patterned wafer; and
when the inspected patterned wafer comprises a plurality of layers:
at least one thickness of at least one of the plurality of layers, respectively;
a combined thickness of at least some of the plurality of layers; and
at least one mass density of at least one of the plurality of layers, respectively (see column 8 lines 11-24: determines thickness of the layer and/or layers; see column 6 lines 53-65 and claim 1 and 3: correlating beam energy with material density, i.e. density is a determined parameter; as such discloses the one of the one or more varieties listed above).
Campbell discloses wherein the set of structural parameters comprises one or more of:
one or more overall concentrations of one or more materials, respectively, that the inspected patterned wafer comprises; and
at least one width of at least one structure, respectively, which is embedded in the inspected patterned wafer; and
when the inspected patterned wafer comprises a plurality of layers:
at least one thickness of at least one of the plurality of layers, respectively;
a combined thickness of at least some of the plurality of layers; and
at least one mass density of at least one of the plurality of layers, respectively (see column 8 lines 11-24: determines thickness of the layer and/or layers; see column 6 lines 53-65 and claim 1 and 3: correlating beam energy with material density, i.e. density is a determined parameter; as such discloses the one of the one or more varieties listed above).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify claims U.S. Patent No. 12480898 of with the teachings of Campbell, determining the respective thickness of the layers, for the advantageous benefit of generating an accurate representation of the imaged wafer.
Claims 10 and 11 are rejected on the ground of nonstatutory double patenting as being unpatentable over the claims of U.S. Patent No. 12480898 in view of Zhang (US 20180107928).
Regarding claim 10, U.S. Patent No. 12480898 claims wherein the trained algorithm is determined through training using the reference data and (i) key X-ray emissions parameters, which are derived from X-ray emission data sets of other patterned wafers samples of the same intended design as the inspected patterned wafer, and/or (ii) simulation data, which are derived from simulating impinging of patterned wafers of the same intended design as the inspected patterned wafer with e-beams at each of a plurality of landing energies (see claims 1 and 4).
U.S. Patent No. 12480898 does not expressly claim wherein weights of the trained algorithm are determined through the training.
Zhang discloses wherein a trained algorithm comprises a neural network, and wherein the trained algorithm is or comprises a linear model-incorporating algorithm (see paragraph 0061-0062: trained neural network).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the claims of U.S. Patent No. 12480898 with the teachings of Zhang, i.e. using a neural network as a machine learning algorithm, for the advantageous benefit of using a proven, conventional machine learning algorithm for accurately analyzing energy-dispersive X-ray data sets.
Regarding claim 11, U.S. Patent No. 12480898 does not expressly claim wherein the trained algorithm is or comprises a neural network, or wherein the trained algorithm is or comprises a linear model-incorporating algorithm.
Zhang discloses wherein a trained algorithm is or comprises a neural network, or wherein the trained algorithm is or comprises a linear model-incorporating algorithm (see paragraph 0061-0062: trained neural network).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the claims of U.S. Patent No. 12480898 with the teachings of Zhang, i.e. using a neural network as a machine learning algorithm, for the advantageous benefit of using a proven, conventional machine learning algorithm for accurately analyzing energy-dispersive X-ray data sets.
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 1-5, 9, and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Campbell (US 9625398) in view of Jambunathan (US 20200411513) and Hlavenka (US 11373839).
Regarding claim 1, Campbell discloses a system for non-destructive depth-profiling of samples (see Abstract and column 2 lines 51-63, column 5 line 45 to column 6 line 11, and column 8 lines 54-67: non-destructive energy-dispersive X-ray spectroscopy used to generate a depth profile, i.e. z-profile of a sample), the system comprising:
an electron beam (e-beam) source configured to project e-beams on an inspected sample at a plurality of landing energies and at a plurality of lateral locations within a profiled region of the sample that includes lateral non-uniformity, the e-beams inducing X-ray emitting interactions within respective probed volumes whose depth varies according to the landing energy (see Fig. 1 and column 5 lines 45-64: SEM system generates an electron beam, directed at sample; and see column 2 lines 50-63 and column 6 lines 52-65: scan are performed at various beam energy levels/landing energies for probing an interaction volume; see column 7 lines 8-27: depth determined by the beams energy level/landing energy; see Fig 5 and column 8 lines 25-44: samples taken at various locations);
an X-ray sensor configured to measure the emitted X-rays to obtain X-ray emission data sets pertaining to each of the probed volumes, each associated with the landing energy and the lateral location of the inducing e-beam (see Abstract, Fig. 1, column 1 lines 21-31, and column 6 lines 11-25: EDS detectors to detect X-rays from the sample; see also column 7 lines 41-61: collect data for a plurality of different energy levels, i.e. forms a set of data; see column 7 lines 8-27: depth determined by the beams energy level/landing energy; see Fig 5 and column 8 lines 25-44: samples taken at various locations); and
processing circuitry configured to determine a set of structural parameters, which characterizes an internal geometry and/or a composition at a lateral location and depth within the inspected sample, based on the measured optical X-ray emission data sets and taking into account reference data indicative of an intended design of the inspected sample (see Figs 1, column 2 line 64 to column 3 line 2, and 5, column 2 lines 4-24, column 6 lines 20-25, and column 8 lines 44-67: processor, generates a composition depth profile for the sample, discusses determining depth, shape, and/or composition of the layers of the sample).
Campbell does not expressly disclose wherein the sample is a patterned wafer; and
wherein the structural parameters are determing taking into account reference data indicative of an intended design of the inspected sample.
Jambunathan discloses wherein the sample is a patterned wafer (see paragraph 0021, 0023, 0026, and 0047-0047: discusses patterning process on a substrate/wafer and substrate being imaged using EDX spectroscopy).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Campbell with the teachings of Jambunathan, evaluating samples such as patterned wafers, for the advantageous benefit of monitoring the manufacture of patterned wafers.
Campbell and Jambunathan do not expressly disclose wherein the structural parameters are determing taking into account reference data indicative of an intended design of the inspected sample.
Hlavenka discloses wherein structural parameters are determing taking into account reference data indicative of an intended design of the inspected sample (see column 2 lines 11-46 and lines 62-66 and column 5 line 62 to column 6 line 2: machine learning estimator may be initiated based on sample information and/or known spectral components. For example, known spectral components of possible compositions of the sample may be used as the initial spectral components, broadly interpreted, sample information and known spectral components and known spectral components of possible compositions of the sample meet limitations of design data of the sample; and see column 10 lines 40-56: determines structural and composition information of the sample).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Campbell with the teachings of Hlavenka, i.e. using sample specific information when evaluating the structural and composition makeup via machine learning, for the advantageous benefit of improving the accuracy of the structural and composition determinations of the machine learning algorithm. Once modified, the modification teaches wherein the reference data comprise design data of the inspected patterned wafer as Jambunathan previously disclosed wherein the sample is a patterned wafer.
Regarding claim 2, Campbell and Jambunathan do not expressly disclose wherein the reference data comprise design data of the inspected patterned wafer and/or ground truth (GT) data of other patterned wafers of the same intended design as the inspected patterned wafer and/or GT data of especially prepared patterned wafers exhibiting selected variations with respect to the intended design.
Hlavenka discloses wherein the reference data comprise design data of the inspected sample (see column 2 lines 11-46 and lines 62-66 and column 5 line 62 to column 6 line 2: machine learning estimator may be initiated based on sample information and/or known spectral components. For example, known spectral components of possible compositions of the sample may be used as the initial spectral components, broadly interpreted, sample information and known spectral components and known spectral components of possible compositions of the sample meet limitations of design data of the sample; and see column 10 lines 40-56: determines structural and composition information of the sample).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Campbell with the teachings of Hlavenka, i.e. using sample specific information when evaluating the structural and composition makeup via machine learning, for the advantageous benefit of improving the accuracy of the structural and composition determinations of the machine learning algorithm. Once modified, the modification teaches wherein the reference data comprise design data of the inspected patterned wafer as Jambunathan previously disclosed wherein the sample is a patterned wafer.
Regarding claim 3, Campbell, previously modified, further discloses wherein the set of structural parameters specifies map of a target material, which the inspected sample, i.e. previously modified patterned waver, comprises, on the depth and the lateral location (see Abstract, Fig. 5, and column 6 lines 11-25: maps out the sample, Fig.5 shows different profiles at lateral locations).
Campbell and Jambunathan do not expressly disclose wherein the map is a concentration map quantifying a dependence of a concentration of a target material.
Hlavenka discloses wherein the map is a concentration map quantifying a dependence of a concentration of a target material (see column 3 lines 6-13 and column 6 lines 12-36: discloses computing the concentration at the measurement location and generating component maps/mapping concentrations).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Campbell with the teachings of Hlavenka, i.e. mapping the concentration values, for the advantageous benefit allowing a user to visually view a map of the determined concentration values at the specific locations.
Regarding claim 4, Campbell does not expressly disclose wherein the inspected patterned wafer comprises a bulk into which the target material has been introduced, and wherein the bulk is or comprises a semiconductor structure; and/or wherein the target material comprises fluorine, nitrogen, boron, and/or gallium.
Jambunathan discloses wherein the inspected patterned wafer comprises a bulk into which the target material has been introduced, and wherein the bulk is or comprises a semiconductor structure; and/or wherein the target material comprises fluorine, nitrogen, boron, and/or gallium (see Abstract and paragraphs 0021-0022: silicon bulk, discloses materials being evaluated such as gallium, boron, nitrogen, and fluorine; and see paragraph 0021, 0023, 0026, and 0047-0047: discusses patterning process on a substrate/wafer and substrate being imaged using EDX spectroscopy).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Campbell with the teachings of Jambunathan, evaluating substrate samples to determine concentrations of the disclosed elements, to see if the substrate has been correctly manufactured, incorrectly manufactured, or damaged during manufacturing.
Regarding claim 5, Campbell, previously modified, further discloses wherein the set of structural parameters comprises one or more of:
one or more overall concentrations of one or more materials, respectively, that the inspected patterned wafer comprises; and
at least one width of at least one structure, respectively, which is embedded in the inspected patterned wafer; and
when the inspected patterned wafer comprises a plurality of layers:
at least one thickness of at least one of the plurality of layers, respectively;
a combined thickness of at least some of the plurality of layers; and
at least one mass density of at least one of the plurality of layers, respectively (see column 8 lines 11-24: determines thickness of the layer and/or layers; see column 6 lines 53-65 and claim 1 and 3: correlating beam energy with material density, i.e. density is a determined parameter; as such discloses the one of the one or more varieties listed above).
Regarding claim 9, Campbell and Jambunathan do not expressly disclose wherein, in order to determine the set of structural parameters, the processing circuitry is configured to execute a trained algorithm, which is configured to receive as inputs key X-ray emission parameters extracted from the X-ray emission data sets.
Hlavenka discloses wherein, in order to determine the set of structural parameters, the processing circuitry is configured to execute a trained algorithm, which is configured to receive as inputs key X-ray emission parameters extracted from the X-ray emission data sets (see column 5 line 55 to column 6 line 35: machine learning estimator compares the input spectrum or spectral component with theoretical spectra of multiple chemical elements, and outputs quantified spectrum or quantified spectral component as well as the concentrations of the chemical elements in the component (or spectral component).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Campbell with the teachings of Hlavenka, i.e. imputing the spectral components into a machine learning algorithm, for the advantageous benefit of using a trained machine leaning algorithm to accurately determine the concentration values of the sample/wafer being analyzed.
Regarding claim 13, Campbell discloses a computer-based method for non-destructive depth-profiling of samples (see Abstract and column 2 lines 51-63, column 5 line 45 to column 6 line 11, and column 8 lines 54-67: non-destructive energy-dispersive X-ray spectroscopy used to generate a depth profile, i.e. z-profile of a sample; and see Fig. 1 and column 3 lines 3-34: computer may implement the method), the method comprising:
a measurement operation comprising, for each of a plurality of landing energies, selected so as to allow probing an inspected sample to a plurality of depths, and at a plurality of lateral locations within a profiled region of the sample that includes lateral non-uniformity (see Fig. 1 and column 5 lines 45-64: SEM system generates an electron beam, directed at sample; and see column 2 lines 50-63 and column 6 lines 52-65: scan are performed at various beam energy levels/landing energies; see column 7 lines 8-27: depth determined by the beams energy level/landing energy; see Fig 5 and column 8 lines 25-44: samples taken at various locations show lateral non-uniformity), suboperations of:
projecting an electron beam (e-beam) on the inspected sample at the lateral location, which induces X-ray light-emitting interactions within a respective probed volume of the inspected sample, whose depth is determined by the landing energy (see Fig. 1 and column 5 lines 45-64: SEM system generates an electron beam, directed at sample; and see column 2 lines 50-63 and column 6 lines 52-65: scan are performed at various beam energy levels/landing energies for probing an interaction volume; see column 7 lines 8-27: depth determined by the beams energy level/landing energy; see Fig 5 and column 8 lines 25-44: samples taken at various locations); and
measuring the emitted X-rays to obtain an X-ray emission data set pertaining to the probed volume associated with the corresponding landing energy and lateral location of the inducing e-beam (see Abstract, Fig. 1, column 1 lines 21-31, and column 6 lines 11-25: EDS detectors to detect X-rays from the sample; see also column 7 lines 41-61: collect data for a plurality of different energy levels, i.e. forms a set of data; see column 7 lines 8-27: depth determined by the beams energy level/landing energy; see Fig 5 and column 8 lines 25-44: samples taken at various locations); and
a data analysis operation comprising determining a set of structural parameters, which characterizes an internal geometry and/or a composition at a lateral location and depth within the inspected sample, based on the measured X-ray emission data sets (see Figs 1, column 2 line 64 to column 3 line 2, and 5, column 2 lines 4-24, column 6 lines 20-25, and column 8 lines 44-67: processor, generates a composition depth profile for the sample, discusses determining depth, shape, and/or composition of the layers of the sample).
Campbell does not expressly disclose wherein the sample is a patterned wafer; and
wherein the structural parameters are determing taking into account reference data indicative of an intended design of the inspected sample.
Jambunathan discloses wherein the sample is a patterned wafer (see paragraph 0021, 0023, 0026, and 0047-0047: discusses patterning process on a substrate/wafer and substrate being imaged using EDX spectroscopy).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Campbell with the teachings of Jambunathan, evaluating samples such as patterned wafers, for the advantageous benefit of monitoring the manufacture of patterned wafers.
Campbell and Jambunathan do not expressly disclose wherein the structural parameters are determing taking into account reference data indicative of an intended design of the inspected sample.
Hlavenka discloses wherein structural parameters are determing taking into account reference data indicative of an intended design of the inspected sample (see column 2 lines 11-46 and lines 62-66 and column 5 line 62 to column 6 line 2: machine learning estimator may be initiated based on sample information and/or known spectral components. For example, known spectral components of possible compositions of the sample may be used as the initial spectral components, broadly interpreted, sample information and known spectral components and known spectral components of possible compositions of the sample meet limitations of design data of the sample; and see column 10 lines 40-56: determines structural and composition information of the sample).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Campbell with the teachings of Hlavenka, i.e. using sample specific information when evaluating the structural and composition makeup via machine learning, for the advantageous benefit of improving the accuracy of the structural and composition determinations of the machine learning algorithm. Once modified, the modification teaches wherein the reference data comprise design data of the inspected patterned wafer as Jambunathan previously disclosed wherein the sample is a patterned wafer.
Claims 6-7 are rejected under 35 U.S.C. 103 as being unpatentable over Campbell (US 9625398) in view of Jambunathan (US 20200411513), Hlavenka (US 11373839), and Sakamae (US 20210356413).
Regarding claim 6, Campbell, previously modified, further discloses the X-ray sensor is configured to measure an intensity of at least a portion of the respectively emitted X-rays which the inspected sample, i.e. previously modified patterned wafer, comprises (see Abstract, Fig. 1, column 1 lines 21-31, and column 6 lines 11-25: EDS detectors to detect X-rays emitted from the sample).
Campbell, Jambunathan, and Hlavenka do not expressly disclose wherein the respective emitted X-rays have a frequency equal to, or within a frequency range about, a peak characteristic X-ray emission frequency of a target material.
Sakamae discloses wherein the portion of the respectively emitted and measured X-rays, have a frequency equal to, or within a frequency range about, a peak characteristic X-ray emission frequency of a target material, i.e. previously discussed profiled material (see paragraph 0045-0046: scanning spectral wavelength/frequency in vicinity of the peak wavelength/frequency of the target element).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Campbell with the teachings of Sakamae, i.e. measuring the wavelength/range of wavelength corresponding to the target material, for the advantageous benefit of obtaining relevant data corresponding the material of interest.
Regarding claim 7, Campbell, previously modified, discloses wherein the X-ray sensor comprises an energy-dispersive X-ray spectrometer or a wavelength-dispersive X-ray spectrometer (see Abstract and paragraph 0034: energy dispersive X-ray spectroscopy (EDX) or wavelength dispersive X-ray spectroscopy (WDX)).
Claims 8 is rejected under 35 U.S.C. 103 as being unpatentable over Campbell (US 9625398) in view of Jambunathan (US 20200411513), Hlavenka (US 11373839), and Sender (US 20160322195).
Regarding claim 8, Campbell discloses wherein the system is configured to allow projecting the e-beams so as to impinge on the inspected patterned wafer at each of controllably selectable lateral locations thereon (see Abstract, Fig. 5, and column 6 lines 11-25: maps out the sample, Fig.5 shows different profiles at lateral locations).
Campbell and Jambunathan do not expressly disclose wherein the concentration map is three-dimensional.
Hlavenka discloses wherein the map is a concentration map (see column 3 lines 6-13 and column 6 lines 12-36: discloses computing the concentration at the measurement location and generating component maps/mapping concentrations).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Campbell with the teachings of Hlavenka, i.e. mapping the concentration values, for the advantageous benefit allowing a user to visually view a map of the determined concentration values at the specific locations.
Campbell, Jambunathan, and Hlavenka do not expressly disclose wherein the concentration map is three-dimensional.
Sender discloses a system that is configured to allow projecting the e-beams so as to impinge on the sample at each of controllably selectable lateral locations thereon; and wherein a generated image from the plurality of scans is three-dimensional image (see Fig. 2 and paragraphs 0047, 0056, and 0083: discloses a scan pattern, controllable in the lateral direction, to scan regions of interest of a sample, and discusses generating a 3D image from the plurality of scan measurement).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Campbell with the teachings of Sender, i.e. scanning a plurality of lateral location and using a plurality of scans to generate a 3D image, for the advantageous benefit of gathering and piecing together a plurality of scans to generate an accurate 3D representation of the sample of interest. Once modified, it would have been obvious to one with ordinary skill in the art to generate a 3D image/map of the concentration data based on the concentration data determined at the different depths.
Claims 10 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Campbell (US 9625398) in view of Jambunathan (US 20200411513), Hlavenka (US 11373839), and Zhang (US 20180107928).
Regarding claim 10, Campbell and Jambunathan do not expressly disclose wherein weights of the trained algorithm are determined through training using the reference data and (i) key X-ray emissions parameters, which are derived from X-ray emission data sets of other patterned wafers samples of the same intended design as the inspected patterned wafer, and/or (ii) simulation data, which are derived from simulating impinging of patterned wafers of the same intended design as the inspected patterned wafer with e-beams at each of a plurality of landing energies.
Hlavenka discloses the trained algorithm is determined through training using the reference data and (i) key X-ray emissions parameters, which are derived from X-ray emission data sets of other patterned wafers samples of the same intended design as the inspected patterned wafer, and/or (ii) simulation data, which are derived from simulating impinging of patterned wafers of the same intended design as the inspected patterned wafer with e-beams at each of a plurality of landing energies (see Fig. 2A and column 2 lines 11-45: machine learning model is updated, i.e. trained, based on the measurement of the sample, known spectra, and/or theoretical spectra of the chemical elements).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Campbell with the teachings of Hlavenka, i.e. using a trained machine learning algorithm, for the advantageous benefit of improving the accuracy of the structural and composition determinations of the machine learning algorithm.
Campbell, Jambunathan, and Hlavenka do not expressly disclose wherein weights of the trained algorithm are determined through the training.
Zhang discloses wherein weights of the trained algorithm are determined through the training (see paragraph 0061-0062: trained neural network).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Campbell with the teachings of Zhang, i.e. using a neural network as a machine learning algorithm, for the advantageous benefit of using a proven, conventional machine learning algorithm for accurately analyzing energy-dispersive X-ray data sets.
Regarding claim 11, Campbell, Jambunathan, and Hlavenka do not expressly disclose wherein the trained algorithm is or comprises a neural network, or wherein the trained algorithm is or comprises a linear model-incorporating algorithm.
Zhang discloses wherein a trained algorithm is or comprises a neural network, or wherein the trained algorithm is or comprises a linear model-incorporating algorithm (see paragraph 0061-0062: trained neural network).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Campbell with the teachings of Zhang, i.e. using a neural network as a machine learning algorithm, for the advantageous benefit of using a proven, conventional machine learning algorithm for accurately analyzing energy-dispersive X-ray data sets.
Allowable Subject Matter
Claim 12 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.
Regarding claim 12, the prior art discloses the limitations discussed above.
However, the prior art fails to disclose the system of claim 11, wherein the set of structural parameters specifies a concentration map quantifying a dependence of a concentration of a target material, which the inspected patterned wafer comprises, at least on the depth; and wherein the neural network is a classification neural network and at each map coordinate the concentration map specifies the density of the target material to a respective density range from a plurality of density ranges.
Relevant Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Geissler (US 20100196296) discloses an EDXS measuring technique using a plurality of landing energies.
Conclusion
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/MICHAEL J DALBO/Primary Examiner, Art Unit 2857