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 .
Response to Arguments
Applicant's arguments filed on 05/18/2026 have been fully considered but they are not persuasive.
The objections to drawings of record are withdrawn in light of applicant’s amendments.
The objections to specifications of record are withdrawn in light of applicant’s amendments.
The claim objections of record are withdrawn in light of applicant’s amendments.
The indefiniteness rejections of record are withdrawn in light of applicant’s amendments.
The 102 rejections of record are withdrawn in light of applicant’s amendments.
101 rejections:
Applicant argues that claim 1 is directed to a specific semiconductor metrology improvement because the claim uses electron-beam acquisition signals to identify lateral edges of buried semiconductor layers based on depth-dependent width, slope, or amplitude characteristics. Applicant’s arguments have been considered but are not persuasive. The claimed improvement resides in interpreting signal patterns, not in improving the electron beam examination system, beam scanning, detector structure, landing energy control, or signal acquisition mechanism. The claim merely obtains an acquisition signal from an electron beam examination system and then compares characteristics of signal patterns to infer which pattern corresponds to which buried-layer edge.
Under Step 2A, Prong One, the claim recites an abstract idea because the identification step is a mental process and/or mathematical data analysis. A human reviewing the acquisition signal or derivative signal could observe that one pattern is wider, has a smaller slope, or has a smaller amplitude, and infer that the pattern corresponds to a deeper layer. The fact that the signal originated from a physical semiconductor specimen does not remove the claim from the abstract idea category, because the claim uses the physical signal merely as information to be analyzed.
Under Step 2A, Prong Two, the claim does not integrate the abstract idea into a practical application. The recited semiconductor specimen, electron beam examination system, acquisition signal, derivative signal, and processing circuitry merely provide a field of use and data-gathering environment for the abstract analysis. The claimed determination of edge position is the result of the abstract analysis itself, not a separate technological improvement. The claim does not recite any specific improvement to the electron beam tool, detector, scan operation, signal generation, or landing energy control.
Under Step 2B, Applicant’s assertion that the claimed approach is unconventional is not persuasive because the alleged unconventional aspect, discriminating buried-layer edge patterns based on width, slope, or amplitude relationships, is the abstract idea itself. The remaining additional elements are generic and conventional at the level claimed: processing circuitry for processing data, an electron beam examination system for obtaining an acquisition signal, and a semiconductor specimen as the object being measured. Thus, the claim does not recite significantly more than the abstract idea.
Accordingly, the 101 rejections of record are maintained.
103 rejections:
Applicant’s arguments with respect to references Mack and Villarrubia 2005 not teaching the amended claim 1 have been considered but are moot because the new ground of rejection does not rely on either reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-2, 8-16, and 21-25 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea (i.e., mental processes and mathematical concepts for analyzing data), and the claims do not recite additional elements that integrate the abstract idea into a practical application or amount to significantly more than the judicial exception.
Step 2A, Prong One – Judicial exception (Abstract Idea)
The courts consider a mental process (thinking) that “can be performed in the human mind, or by a human using a pen and paper” to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, “methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’” 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same). Further, the courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer. As the Federal Circuit has explained, "[c]ourts have examined claims that required the use of a computer and still found that the underlying, patent-ineligible invention could be performed via pen and paper or in a person’s mind." Versata Dev. Group v. SAP Am., Inc., 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015). See also Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1318, 120 USPQ2d 1353, 1360 (Fed. Cir. 2016) (‘‘[W]ith the exception of generic computer-implemented steps, there is nothing in the claims themselves that foreclose them from being performed by a human, mentally or with pen and paper.’’); Mortgage Grader, Inc. v. First Choice Loan Servs. Inc., 811 F.3d 1314, 1324, 117 USPQ2d 1693, 1699 (Fed. Cir. 2016) (holding that computer-implemented method for "anonymous loan shopping" was an abstract idea because it could be "performed by humans without a computer").
In the instant case, the independent claims recite limitations that, when considered in their broadest reasonable interpretation, fall within the abstract idea of (i) mental process (concepts formed in the human mind such as observation, evaluation, and judgment) and/or (ii) mathematical concepts (relationships, comparisons, and mathematical operations such as determining variations/derivatives, comparing amplitudes/widths/slopes, and selecting based on criterial). For instance, the independent claim 1 recites (independent claims 24 and 25 recite similar limitations):
obtain an acquisition signal informative of a semiconductor specimen comprising at least a first layer located at a first depth in the specimen, and a second layer located at a second depth in the specimen, which is deeper than the first depth,
wherein the acquisition signal has been acquired by an electron beam examination system operative to scan the specimen with an electron beam associated with a landing energy enabling generating, in at least one of the acquisition signal or in a derivative signal of the acquisition signal, patterns informative of lateral edges of the first and second layers,
identify in at least one of the acquisition signal or in the derivative signal, a first pattern of said patterns, that is informative of a lateral edge of the first layer, and a second pattern of said patterns, that is informative of a lateral edge of the second layer,
said identification comprising determining that: the second pattern has a larger width than the first pattern in the derivative signal, due to the second layer being deeper in the specimen than the first layer, or the second pattern has a smaller slope than the first pattern in the acquisition signal, due to the second layer being deeper in the specimen than the first layer, or the second pattern has a smaller amplitude than the first pattern in the derivative signal, due to the second layer being deeper in the specimen than the first layer, and
determine, based on the identified first and second patterns, at least one property of the first layer or the second layer, the at least one property comprising at least one of a position of the lateral edge of the first layer or a position of the lateral edge of the second layer.
These limitations collectively recite analyzing measurement data by applying comparisons/relationships (including derivative/variation analysis) to infer layer edge locations properties and select landing energy. Such evaluation and selection is fundamentally a form of data analysis and mathematical evaluation that can be characterized as an abstract idea.
Step 2A, Prong Two – Integration into a Practical Application
The claims are not integrated into a practical application because in practice, executing all of the steps is indistinguishable from: (i) mere data acquisition from a conventional instrument environment, and (ii) generic computer implementation of the abstract analysis. That is to say that integration into a practical application is lacking where, as here, the abstract idea has no effect on the material world or the execution of the process.
Although the claims include additional elements (e.g., “one or more processing circuities,” “electron beam examination system tool,” a “semiconductor specimen” with layers), these additional elements do not integrate the abstract idea into a practical application. For example, the electron beam examination system/tool and acquisition signal limitations function as data gathering steps without reciting a specific improvement to the electron beam tool itself, the scan hardware, or the signal formation mechanism, but instead recites post-acquisition analysis and interpretation of an acquired signal using generic processing circuitry. Likewise, the recited “processing circuitry” performs generic functions such as obtain/determine/compare/identify/select, which amounts to using a computer as a tool to perform the abstract data analysis more quickly or efficiently.
Therefore, the claims as a whole are directed to an abstract idea.
Step 2B– Significant More (Inventive Concept)
The claims do not include additional elements, either individually or as an ordered combination, that amount to significant more than the abstract idea. The “processing circuitries” (recited in claims 1, 21, 23, 25), the “non-transitory computer readable medium” (recited in claim 24) limitations are generic computer elements performing routine functions such as receiving and processing data. The “electron beam examination system/tool” (recited in claims 1, 11, 15-16, 24-25) and acquiring signals at landing energies are conventional measurement activities used as input to the abstract analysis. As such, the recited system is a well-known system and a routine part of data acquisition and analyzing, and the addition of the system is done at such a high level of generality that the claimed system would effectively prevent anyone using any system from thinking the claimed abstract idea.
Dependent claims 2, 8, 14 include additional limitations (e.g., derivative signals, using expected amplitudes, using width/amplitude/slope differences) merely add further details of the abstract analysis, and as such not overcome the above noted issues.
Dependent claims 9-13 add “landing energy selection using simulations” limitations yet still amount to evaluating and selecting based on mathematical relationships and comparisons of data patterns. Tying this evaluation to the SEM context, without more, is an invocation of a technological environment rather than a practical application that meaningfully limits the abstract idea.
Dependent claim 15 adds an “electronic beam” to the invention. Adding an electronic beam to the claimed abstract idea does not meaningfully limit the claim, since the electronic beam only acts as a nominally claimed data-gathering step in the larger context of an abstract idea.
Taken alone or as ordered combination, claims 1-2, 8-16, and 21-25 fail to recite patent eligible subject matter.
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 1-2 and 24-25 are rejected under 35 U.S.C. 103 as being unpatentable over US 2021/0383529 A1 [hereinafter Kris] in view of Guan, A., et al., (2020). Optical coherence tomography modeling incorporating scattering, absorption, and multiple reflections. Journal of the Optical Society of America A, 37(3), 391. [hereinafter Guan].
Regarding Claims 1, 24 and 25:
Kris teaches a system comprising one or more processing circuitries (para. [0015]): “A system ...comprise at least one processor configured for performing metrology) configured to:
non-transitory computer readable medium comprising instructions that, when executed by one or more processors, cause the one or more processors to (para. [0048]) and a method comprising performing, by one or more processing circuitries (Abstract):
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obtain an acquisition signal informative of a semiconductor specimen comprising at least a first layer located at a first depth in the specimen, and a second layer located at a second depth in the specimen, higher which is deeper than the first depth obtain an acquisition signal informative of a semiconductor specimen comprising at least a first layer located at a first depth in the specimen, and a second layer located at a second depth in the specimen, higher than the first depth (annotated Fig. 4a and Fig. 4b; paras. [0013, 0020, 0124, 0127]: obtaining SEM measurement data for a 3D-VNAND staircase having plural steps in a vertically tiered/multilayer structure; the measurement data is represented as a 1-D SEM signal/profile where “the vertical axis… comprises SEM signal intensity” and “the horizontal axis may be the x-SEM image coordinate”; for example, “Fig. 4b shows the SEM signal corresponding to the steps of Fig. 4a, ” under a broad reasonable interpretation, different steps correspond to different vertical levels/depths within the multilayer structure, i.e., first and second “layers” at different depths (See annotated Fig. 4a)),
wherein the acquisition signal has been acquired by an electron beam examination system operative to scan the specimen with an electron beam associated with a landing energy (paras. [0013 and 0015]: the system operates in conjunction with a SEM and acquires an image “generated by scanning the semiconductor structure with a charged particle beam and collecting signals emanating from the semiconductor structure”; an SEM electron beam that impinges on the specimen is necessarily associated with a beam energy at the specimen (landing energy), as recited),
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enabling generating, in at least one of the acquisition signal, or in a derivative signal of the acquisition signal, patterns informative of lateral edges of the first and second layers (Claim 12, Fig. 3C, paras. [0111-0114]: conventional 3D CD SEM metrology includes scan, line detect, contour detect, linear fit, and CD results; fine edge/topopoints estimation is used; line detection algorithms assume a line has two physical edges). Kris defining “a pair of coarse edges and a pair of fine edges” and using the coarse/fine edges to determine a parameter, also in Fig. 3C, “Top” and “Bottom” edge signal features and “Fine Edges for measurement”).
identify in at least one of the acquisition signal or in the derivative signal, a first pattern of said patterns, that is informative of a lateral edge of the first layer, and a second pattern of said patterns, that is informative of a lateral edge of the second layer (Fig. 4b, annotated figs. 4a and 4d, paras. [0124, 0127-0130]: the 1-D SEM signal (Fig. 4b) corresponds to the staircase steps (Fig. 4a) and contains edge-related features; Fig. 4d shows coarse edges and pairs of fine edges defining left and right boundaries of each step; these step boundaries are lateral terminations/boundaries along the x-direction (i.e., “lateral edges”) and appear in/are extracted from the 1-D SEM signal (or a signal derived therefrom). Different steps (different layer levels under BRI) have different corresponding boundary patterns (at minimum at different x-positions), such that the second pattern differs from the first pattern),
determine, based on the identified first and second patterns, at least one property of the first layer or the second layer, the at least one property comprising at least one of a position of the lateral edge of the first layer or a position of the lateral edge of the second layer (paras. [0054, 0131, 0133]: processing the SEM image/signal of the staircase for metrology control, including measuring one or more steps as an individual feature and using the detected fine edges/boundaries for CD results such as estimating distances between fine contours/boundaries (dimensional properties), thereby determining one or more properties of the measured step/layer level).
However, Kirs doers not specifically note that said identification comprising determining that the second pattern has a larger width than the first pattern in the derivative signal, due to the second layer being deeper in the specimen than the first layer, or the second pattern has a smaller slope than the first pattern in the acquisition signal, due to the second layer being deeper in the specimen than the first layer, or the second pattern has a smaller amplitude than the first pattern in the derivative signal, due to the second layer being deeper in the specimen than the first layer.
Guan teaches that an acquired A-scan is a one-dimensional amplitude signal containing peaks associated with interfaces between layers, and that the height of the peaks corresponding to sample interfaces is reduced, with the reduction being more pronounced for deeper interfaces because light traveling to deeper layers undergoes more scattering (See Pages 1-2 and 6: for “a sample contains m-1 layers, then this sample will have m interfaces”, and uses A-scan “to measure the axial length of the investigating tissue,” the results “contain numerous peaks associated with the tissue layer interfaces.” “The results show that the absorption and scattering processes have significant impact on the height of the peaks in the simulated A-scans.” “The height of the interference peaks corresponding to sample interfaces reduced with the incorporation of scattering and was more pronounced from deeper interfaces. This makes sense given that light traveling to deeper layers undergoes more scattering than light traveling to layers closer to the surface”).
As such, in light of Guan’s teaching, the multiple peaks in Kris’s signal can be used to identify the depth of each layer, i.e., a peak with a smaller amplitude indicating its corresponding layer has a greater depth. Therefore, Kris in view of Guan teaches that said identification comprising determining that the second pattern has a smaller amplitude than the first pattern in the derivative signal, due to the second layer being deeper in the specimen than the first layer.
Kris teaches the semiconductor/SEM edge-metrology context and first/second layer-edge patterns. Guan teaches the straightforward depth-based signal principle that deeper layer/interface patterns have reduced amplitude. Therefore, it would have been obvious for an ordinary skilled person in the art, before the effective time of filing, to perform SEM staircase metrology as in Kris by applying Guan’s known teaching that layer/amplitude scan responses have a measurable lateral extent/width to use peak amplitude differences, as an additional, predictable discriminator for identifying which edge-related pattern corresponds to which layer edge, to improve reliable edge identification across staircase levels.
Regarding Claim 2:
Kris in view of Guan teaches the system of claim 1. Kris further teaches wherein the one or more properties include at least one of: a width of the first layer, or a width of the second layer (para. [0024]: “measuring the individual step relative to the line … yields leftmost and rightmost portions of the step, which may then be used for CD Results estimation”).
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Kris in view of Guan, further in view of US20110147948A1 [hereinafter Chen].
Regarding Claim 8:
Kris in view of Guan teaches the system of claim 1. However, the combined references do not specifically note that wherein the second layer is separated from the first layer by a layer which has a density which is smaller than a density of the first layer and than a density of the second layer. Chen teaches the second layer is separated from the first layer by a layer which has a density which is smaller than a density of the first layer and than a density of the second layer (claims 1 and 14:: teaches a porous low-k layer structure has three layers (from top to bottom) as top portion, body portion and bottom portion, “a porous bottom portion and a body portion… wherein… the porous bottom portion has a density higher than a density of the body portion,” “further comprising a top portion… located on the body portion and has a density higher than the density of the body portion”).
Kris teaches obtaining and processing a SEM-derived signal/profile for metrology of a semiconductor specimen having vertically varying structure, where the steps represent different vertical levels within the specimen. Chen teaches a semiconductor dielectric layer stack formed on a substrate and used in an interconnect structure, where a body portion is between a top portion and a bottom portion, and each of the top and bottom portions has a density higher than the density of the body portion. Thus, it would have been obvious for an ordinary skilled person in the art, before the effective time of filing, to apply Kris’s SEM-metrology system to a semiconductor specimen having the density-ranked three-layer configuration taught by Chen, resulting in a system that operates on a specimen where the first and second layers are separated by an intermediate layer whose density is smaller than the densities of both the first and second layers, as applying a known SEM/CD metrology approach to a known multilayer semiconductor stack to yield predictable result.
Claims 9-13 are rejected under 35 U.S.C. 103 as being unpatentable over Kris in view of Guan, further in view of Villarrubia et al., NIST Simulation of E-beam Inspection and CD-SEM in-line metrology: Final Report. NIST (2011) [hereinafter Villarrubia 2011].
Regarding Claim 9:
Kris in view of Guan teaches the system of claim 1. However, the combined references do not specifically note that wherein the landing energy has been selected using one or more simulations.
Villarrubia 2011 teaches wherein the landing energy has been selected using one or more simulations (Pages 5 and 14 of 39: teaches optimization questions arise because there are choices in tool settings including landing energy, and a simulation framework in which beam energy is varied in a simulation loop and has application “for deciding the best landing energy to use”).
Kris teaches metrology using SEM/charged particle scan signals of VNAND staircase steps and determining dimensional results based on detected coarse/fine edges. Villarrubia 2011 teaches using simulations to support selection of operating settings for e-beam tools. Therefore, it would have been obvious for an ordinary skilled person in the art, before the effective time of filing, to combine the teachings, such that the system of Kris would select the landing energy using simulations as taught by Villarrubia 2011, because Kris’s metrology output (edge detection) depends on the quality/behavior of the SEM signal used for edge assignment, and Villarrubia 2011 teaches using simulation sweeps over beam/landing energy specifically to decide the best landing energy setting.
Regarding Claim 10:
Kris in view of Guan, further in view of Villarrubia 2011 teaches the system of claim 9.
Kris further teaches an acquisition signal or a signal derived from the acquisition signal includes a first pattern informative of the lateral edge of the first layer and a second pattern informative of the lateral edge of the second layer, wherein the first pattern differs from the second pattern (as previously discussed)
Villarrubia 2011 further teaches:
determining data informative of variations of a simulated acquisition signal of the specimen for different landing energies of the simulated acquisition signal (Pages 31-32 of 39- Section 4.3.3 and Figs. 26, 27: simulations were performed at multiple beam landing energies “Simulations were performed for… four beam landing energies from 500 eV to approximately 4.95 keV…”and obtained curves of yield vs. landing energy (i.e., the simulated signal changes as landing energy changes) “A sample of three of the resulting curves is shown in Fig. 26…” and Fig. 26 is “Secondary electron yields vs. landing energy…” also discusses different shapes of intensity profiles predicted by simulation modeling “An example of the different shapes of intensity profiles predicted… is shown in Fig. 27”), and
selecting a given landing energy for which a given simulated acquisition signal associated with this given landing energy, or a given signal derived from this given simulated acquisition signal, according to a criterion (Page 14- Section 2.2.3: such nested-loop simulations have application “for deciding the best landing energy to use for defect detection,” and by describing selection using objective criteria/cost functions as “Conditional statements… might be used to minimize user-defined cost functions (e.g., defect detection failures or CD measurement uncertainty) for solving optimization problems”).
Accordingly, applying Villarrubia 2011’s simulation-and-selection workflow to Kris’s SEM/linescan-based edge metrology yields a system that (i) determines simulated signal variations at different landing energies and (ii) selects a landing energy according to a criterion (e.g., minimizing CD measurement uncertainty / defect detection failures) while operating in the same SEM edge/step context where the first and second edge-related patterns are present in the signal used for CD metrology.
Regarding Claim 11:
Kris in view of Guan teaches the system of claim 1. Kris further teaches:
obtain a first/second acquisition signal informative of the specimen, wherein the first/second acquisition signal has been acquired by the electron beam examination system operative to scan the specimen with an electron beam associated with a landing energy (as previously discussed),
determine first/second data informative of variations of the first/second acquisition signal (determining variation/edge information from the SEM signal for step detection and metrology, including use of an “edge width parameter” in the context of “step detection” in the SEM signal corresponding to the steps), and
use the first/second data to determine at least one of a position of the lateral edge of the first layer or a position of the lateral edge of the second layer (determine the position of boundaries of each step based on the obtained data).
However, the combined references do not specifically note that the first acquisition signal is obtained by an electron beam with a first landing energy, the second acquisition signal is obtained by an electron beam with a second landing energy, higher than the first landing energy.
Villarrubia2011 teaches:
first and second signal has been acquired by the electron beam examination system operative to scan the specimen with an electron beam associated with a first landing energy and a second landing energy, higher than the first landing energy (Page 31 of 39- Section 4.3.3: teaches performing SEM-related signal/image simulations at specified beam landing energies, including multiple landing energies spanning low-to-high values “four beam landing energies from 500 eV to approximately 4.95 keV…”), which provides a first landing energy and a second landing energy higher than the first).
Therefore, it would have been obvious for an ordinary skilled person in the art, before the time of effective filing, to obtain and use first and second dataset at different landing energies (as taught in Villarrubia 2011) as a predictable way to improve robustness/accuracy for edge-position determinization (as taught by Kris) by comparing how the profile/variation data changes with landing energy), with a reasonable expectation of success because Villarrubia 2011’s approach expressly analyzes and compares profile behavior across landing energy conditions for edge assignment.
Regarding Claim 12:
Kris in view of Guan teaches the system of claim 1. Kris further teaches the specimen includes N vertically stacked layers L1 to LN, with N≥2, wherein each layer has a different width (teaches a staircase specimen having plural steps/levels (Fig.4a and paras. [0013, 0020]: teaches multiple vertically-stacked levels in a 3D NAND staircase context, and teaches metrology on those steps as distinct measurable features with boundaries used for CD results (“boundaries of Steps” used for CD measurements; “pairs of fine edges… defining left and right boundaries… of each step”, also see fig. 4a, an example of three steps and each step with different width), wherein the system is configured to:
determine one or more properties of one or more of the layers L1 to LN (teaches determining properties of staircase steps/layers via CD measurements based on boundary location, stating “Fine Contour defines the most accurate and precise location of real feature boundaries (e.g. boundaries of Steps) … to be used for CD Measurements,” and “CD Results assume estimation of distance between two fine contours ….”).
However, the combined references do not specifically note that the system is configured to obtain different acquisition signals at different landing energies, determine a derivative signal informative of variations of the given acquisition signal for each given acquisition signal data, thereby obtaining a set of derivative signals, and the layer properties are determined using the set of derivative signals.
Villarrubia teaches:
obtain a plurality of different acquisition signals acquired at different landing energies (Page 31 of 39- Section 4.3.3: acquiring/producing results under multiple landing-energy conditions, stating: “Simulations were performed for… four beam landing energies from 500 eV to approximately 4.95 keV (Si) or 5 keV (Cu)….),
determine, for each given acquisition signal data, a derivative signal informative of variations of the given acquisition signal, thereby obtaining a set of derivative signals (Page 33 of 39- Section 4.3.3: metrology measurement values are determined by algorithms applied to images/signals, and specifically teaches that some CD algorithms use slopes “[Some CD algorithms] … are based upon intensity thresholds or slopes ….”). A “derivative signal informative of variations” encompasses a derived representation that emphasizes variation of the acquisition signal versus position, such as slope/gradient-type information. As such, Villarrubia 2011 ’s express teaching of slope-based CD algorithms provides that, for each acquisition signal (at each landing energy), the system determines such variation-emphasizing derived data, thereby obtaining a set of derived variation signals corresponding to the set of acquisition signals),
use the set of derivative signals to determine edges (Pages 31 and 33 of 39- Section 4.3.3: teaches that the slope/derived-variation information is used in CD algorithms to determine edge/measurement outputs, and that edge position defines a measured property, stating: “[Some CD algorithms are] … based upon… slopes …,” and “The position of left and right edges of a feature defines its width”).
Accordingly, modify Kris in view of Villarrubia 2011 would entail that, when a set of derived variation signals (slope/derivative-type signals) is obtained for the plurality of landing-energy acquisition signals, the set of derived variation signals is used within the CD/edge algorithm to determine properties (e.g., edge locations and widths) of one or more of the staircase steps/layers L1 to LN, as recited.
Therefore, it would have been obvious for an ordinary skilled person in the art, before the effective time of filing, to use a set of derivatives/variation signals from the SEM profiles (as taught in Villarrubia 2011) for CD/edge metrology in Kris, because derivative/slope-based processing is a known and predictable way to obtain robust edge/measurement outputs from SEM profile data.
Regarding Claim 13:
Kris in view of Guan, further in view of Villarrubia 2011 teaches the system of claim 12.
Kris further teaches determine a position of one or more lateral edges of one or more of the layers L1 to LN (CD metrology determines positions/locations of real feature boundaries (lateral edges) via fine contours/fine edges used for CD measurements).
Villarrubia 2011 further teaches compare a first derivative signal obtained at a first landing energy and a second derivative signal obtained at a second landing energy, higher than the first landing energy (teaches running at multiple landing energies, including a higher energy than a lower one: “four beam landing energies from 500 eV to approximately 4.95 keV …” and doing an explicit comparison between signal-profile “shapes” by alignment (“shifting and scaling”) to best agree with a reference model “different shapes of intensity profiles …” and “judged by shifting and scaling the test model to best agree … with a reference model), and
determine a position edge(s) based on a comparison between patterns that appear in the first/second derivative signals and one or more patterns that appear in the first derivative signal (edge position assignment is determined by comparing profile shapes (using “shifting and scaling” to best agree), and “Differences in edge position … judged by shifting and scaling …” “The position of left and right edges of a feature defines its width.”
Accordingly, modify Kris in view of Villarrubia 2011entails that, when the first and second derivative (variation) signals correspond to first and second landing energies (second higher than first), the system determines edge position based on comparing the patterns in those derived signals.
Claims 14-16 are rejected under 35 U.S.C. 103 as being unpatentable over Kris in view of Guan, further in view of Villarrubia et al., Simulation study of repeatability and bias in the critical dimension scanning electron microscope. Journal of Micro/Nanolithography, MEMS, and MOEMS, 4(3), 033002 (2005) [hereinafter Villarrubia 2005].
Regarding Claim 14:
Kris in view of Guan teaches the system of claim 1. However, the combined references do not specifically note that obtain a first/second expected amplitude for the first/second pattern and identifying the first/second pattern based on this first/second expected amplitude.
Villarrubia 2005 teaches obtain an expected amplitude for a pattern and identifying the pattern based on this expected amplitude (Fig. 4 and Page 3 of 10- Section 2.3: calculating a simulated linescan in which the intensity at each point on the linescan (i.e., the signal level of the simulated linescan versus position) is determined by modeled secondary-electron emission, stating that “the total number of secondary electrons emitted from the sample at each beam position determines the intensity at the corresponding point on the linescan,” and further shows (Fig.4) a “match between simulated and measured linescans,” thereby providing an expected (predicted) signal level profile for a linescan pattern).
Kris teaches the measured SEM signal intensity-versus-position profile containing the first pattern. Villarrubia 2005 teaches a simulated linescan intensity vs position profile that supplies an expected (predicted) signal level for the corresponding pattern. Therefore, it would have been obvious for an ordinary skilled person in the art, to use Villarrubia 2005’s simulated linescan as a reference for Kris’s measured SEM linescan, such that a “pattern” in the acquisition signal has a measurable signal level (magnitude) in the SEM signal intensity profile, in order to provide an expected signal level profile for identifying edge-related patterns in the measured SEM signal.
Regarding Claim 15:
Kris in view of Guan teaches the system of claim 1.
Kris further teaches the specimen includes N vertically stacked layers L1 to LN, with N≥2, wherein each layer has a different width (a VNAND / 3D NAND structure with plural vertically stacked layers and a staircase having plural steps, for example, Fig. 4a shows a structure with 3 vertical levels and each level has a different width), wherein the system is configured to:
obtain an acquisition signal informative of the specimen, wherein the acquisition signal has been acquired by an electron beam examination system operative to scan the specimen with an electron beam (obtaining an SEM acquisition signal/profile for the staircase steps with a SEM system, stating “FIG. 4b shows the SEM signal corresponding to the steps”)
determine data informative of variations of the acquisition signal (determining variation/edge information from the SEM signal for step detection and metrology, including use of an “edge width parameter” in the context of “step detection” in the SEM signal corresponding to the steps), and
use the data to determine one or more properties of at least one of the layers L1 to LN (using measured fine edges to generate dimensional metrology results for each step).
However, the combined references do not specifically note that the specimen is scanned with an electron beam associated with a width which expands from a depth of a layer Li to a depth of the next layer Li+1, with i from 1 to N-1.
Villarrubia 2005 teaches the specimen is scanned with an electron beam associated with a width which expands from a depth of a layer Li to a depth of the next layer Li+1, with i from 1 to N-1 (Page 3 of 10- Section 2.2: the effective spot/beam width can be larger at deeper locations than at shallower locations, stating that certain conditions “correspond respectively to spot sizes 10 nm and 20 nm larger at the bottom of the line than at the top” ).
Kris teaches CD-SEM metrology on vertically stacked staircase structures using SEM signal profiles of the steps. Villarrubia 2005 addresses CD-SEM linescan behavior and teaches that effective spot size can increase from top to bottom due to depth-of-focus/beam distribution. Therefore, it would have been obvious for an ordinary skilled person in the art, before the effective time of filing, to apply Villarrubia 2005’s depth-dependent spot-size behavior in Kris’s multilayer staircase scanning context to account for the beam width expansion with depth when determining step/edge measurements across layers, in order to improve measurement reliability/accuracy across layers (i.e., to address depth-dependent changes in resolution/edge response).
Regarding Claim 16:
Kris in view of Guan teaches the system of claim 1. Kris further teaches wherein the at least one acquisition signal has been acquired by the electron beam examination tool operative to scan the specimen with an electron beam associated, in at least part of the scan of the specimen (paras. [0013 and 0015]: the system operates in conjunction with a SEM and acquires an image “generated by scanning the semiconductor structure with a charged particle beam and collecting signals emanating from the semiconductor structure”).
However, the combined references do not specifically note that the electron beam associated with a width which is larger at a second depth of the second layer than at a first depth of the first layer.
Villarrubia 2005 teaches the electron beam associated with a width which is larger at a second depth of the second layer than at a first depth of the first layer (Page 3 of 10- Section 2.2: the effective spot/beam width can be larger at deeper locations than at shallower locations, stating that certain conditions “correspond respectively to spot sizes 10 nm and 20 nm larger at the bottom of the line than at the top”).
Kris teaches CD-SEM metrology on vertically stacked staircase structures using SEM signal profiles of the steps, while Villarrubia 2005 is directed to CD-SEM linescan modeling and explicitly teaches that the effective landing spot/beam width can be larger at a deeper location (“bottom”) than at a shallower location (“top”) due to instrument/beam conditions. Therefore, it would have been obvious for an ordinary skilled person in the art, before the effective time of filing, to operate Kris’s SEM acquisition under the known depth-dependent spot-size condition taught by Villarrubia 2005 so that SEM signals collected from features at different depths within the stacked structure are interpreted and measured with appropriate consideration of the beam width change with depth, thereby improving accuracy/consistency of edge/dimension metrology across layers.
Claims 21-23 are rejected under 35 U.S.C. 103 as being unpatentable over Kris in view of Guan, further in view of Mack et al., Analytical linescan model for SEM metrology. Proceedings of SPIE (2015) [hereinafter Mack].
Regarding Claim 21:
Kris in view of Guan teaches the system of claim 1. Kris further teaches:
the semiconductor specimen includes N vertically stacked layers L1 to LN, with N>2, wherein each layer has a different width (Kris expressly states that “3D NAND flash” has memory cells “stacked vertically in multiple layers,” and the reference is directed to 3D-NAND CDSEM metrology. Fig. 4A shows a 3D-NAND staircase/internal step structure having plural step levels with different lateral extents.
However, the combined references do not specifically note that wherein the one or more processing circuitries are configured to obtain a plurality of N different acquisition signals S1 to SN of the semiconductor specimen, acquired at different landing energies.
Mack teaches wherein the one or more processing circuitries are configured to obtain a plurality of N different acquisition signals S1 to SN of the semiconductor specimen, acquired at different landing energies (teaches SEM linescans/images generated by scanning a sample with an electron beam and recording detected electrons at each pixel. Mack also teaches that the SEM parameters include beam energy, and specifically models/simulates SEM linescans at 300 V, 500 V, and 800 V electron landing voltage.)
As such, the combined references further teachers use the plurality of different acquisition signals to determine one or more properties of one or more of the layers L1 to LN (Kris teaches using SEM image/acquisition data to determine properties of the 3D-NAND staircase, including measuring steps as individual features and determining CD/metrology results. Mack likewise teaches that analysis of SEM images/linescans is used to measure properties of the sample, such as feature width/CD. Thus, Kris in view of Mack teaches using the plurality of different SEM acquisition signals to determine one or more properties of the layers/features.)
Therefore, it would have been obvious for an ordinary skilled person in the art, before the effective time of filing, to modify Kris to obtain SEM acquisition signals at multiple landing energies, as taught by Mack, because Mack teaches that SEM image/linescan behavior depends on electron beam parameters including landing voltage, and that different landing voltages are useful in modeling and evaluating SEM edge/feature signals. Using multiple landing energies in Kris’s 3D-NAND metrology would have predictably provided additional depth/interaction information for distinguishing and measuring vertically stacked staircase layers/features.
Regarding Claim 22:
The combined references teach the system of claim 21. Kris further teaches wherein each acquisition signal Si of the plurality of the N acquisition signals Si to SN, comprises a number I of peaks, informative of lateral edges of first I top layers of the specimen (Kris teaches SEM signal/linescan peaks corresponding to edges/steps of a 3D NAND staircase. Kris Fig. 3B/3C and Fig. 4B-4D show signal peaks/edge regions, “maximal edge width parameter,” and “fine edges for measurement.” Kris also teaches detecting 3D steps and determining the most left line in each 3D step for measurement).
The combined references further teach each acquisition signal Si ...without including peaks informative of lateral edges of deeper layers, with I from 1 to N. Kris recognizes that “SEMs have a depth limitation thus each SEM image typically includes far less than the plural number of steps in the entire staircase” (para. [0021]). Mack teaches obtaining/modeling SEM linescans using different electron landing voltages, including 300 V, 500 V, and 800 V. Thus, it would have been obvious to select different landing energies so that each signal reaches a corresponding depth range. A signal acquired with a landing energy sufficient to reach the first I top layers, but not deeper layers, would include peaks from those first I layers and would not include peaks from deeper layers that are outside the interaction depth.
Regarding Claim 23:
The combined references teach the system of claim 21. The combined references further teach wherein the one or more processing circuitries are configured to identify patterns in the different acquisition signals to determine edge position of each of the layers L1 to L (Kris teaches identifying patterns in SEM acquisition signals/images, including detecting 3D steps, detecting lines/fine contours, and using fine edges for measurement in a 3D NAND staircase. Kris further teaches determining the most left line in each 3D step and using it for measurement, including measuring distances of steps in the SEM image. Mack likewise teaches that SEM image/linescan analysis is used to measure feature widths/CDs and that the analytical linescan model can be used as an edge-detection algorithm. Therefore, Kris in view of Mack teaches identifying patterns in the different acquisition signals to determine edge positions of the layers L1 to LN).
Conclusion
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JING WANG whose telephone number is (571)272-2504. The examiner can normally be reached M-F 7:30-17:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, ROBERT KIM can be reached at 571 272 2293. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JING WANG/ Examiner, Art Unit 2881
/WYATT A STOFFA/ Primary Examiner, Art Unit 2881
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