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 .
DETAILED ACTION
1. The amendment filed on 06/22/2026 has been received and considered. Claims 1-8 and 10-18 are presented for examination.
Claim Objections
2. Claims 1 and 11 are objected to because of the following informalities:
As per Claim 1 and 11, they recite the limitation “the plasma processing conditions” which would be better as “the plasma process conditions” as the claims earlier recite “plasma process conditions.”.
Appropriate correction is required
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
3. Claims 1-8 and 10-18 are rejected under 35 U.S.C. 103 as being unpatentable over Tetiker et al. (US 2017/0176983 A1) in view of Guha (US 20180082826 A1).
As per Claim 1 and 10-11, Tetiker et al. teaches a method/ non-transitory computer readable medium/system (Title, Abstract, [0132]-[0133]) comprising:
(Claim 11) a plasma processing tool (Fig. 6-7, [0104]-[0105], [0132]-[0133]) including: a plasma chamber; a stage disposed in the plasma chamber configured to hold a wafer; and a plasma generation system ([0104]-[0105] “a processing chamber, a substrate holder for holding a substrate within the processing chamber, and a plasma generator for generating a plasma within the processing chamber. The apparatus may further include one or more valve-controlled process gas inlets for flowing one or more process gases into the processing chamber, one or more gas outlets fluidically connected to one or more vacuum pumps for evacuating gases from the processing chamber, etc.”); and
a processor in electronic communication with the plasma processing tool, wherein the processor is configured to ([0104]-[0105], [0132]-[0133] “The instructions may be executed on processor 752”):
(Claim 1 and 10-11) receiving plasma process conditions at a processor ([0038]-[0042] “input parameters include plasma parameters such as ion flux and chemical reaction parameters such as the probability that a particular chemical reaction will occur. These parameters (and particularly, in some embodiments, the plasma parameters) may be obtained from various sources, including other models which calculate them from general reactor configurations and process conditions such as pressure, substrate temperature, plasma source parameters (e.g., power, frequencies, duty cycles provided to the plasma source), reactants, and their flow rates.”, “EPMs employ input variables (a type of independent variables)… local plasma properties such as fluxes and energies of particles such ions, radicals, photons, electrons, excited species, depositor species and their energy and angular distributions etc. ”); and
determining, using the processor, plasma parameters at a surface of a wafer based on the plasma processing conditions with a plasma hypermodel … ([0041]-[0044] “the plasma parameters include local plasma properties such as fluxes and energies of particles”, “EPMs … provide a relationship between the independent and response variables. The relationship may be linear or nonlinear. Generally, an EPM is what is referred to in the art as a cell-based Monte Carlo surface reaction model. These models, in there various forms, operate to simulate a wafer feature's topographical evolution over time in the context of semiconductor wafer fabrication. The models launch pseudo-particles with energy and angular distributions produced by a plasma model or experimental diagnostics for arbitrary radial locations on the wafer. The pseudo-particles are statistically weighted to represent the fluxes of radicals and ions to the surface. The models address various surface reaction mechanisms resulting in etching, sputtering, mixing, and deposition on the surface to predict profile evolution. During a Monte Carlo integration, the trajectories of various ion and neutral pseudo-particles are tracked within a wafer feature until they either react or leave the computational domain.’: a plasma model determines the particle fluxes and energies at locations on the wafer from the reactor process conditions, i.e., the upstream plasma model is the “plasma hypermodel” as claimed);
(Claim 1) exposing the wafer to a plasma with the plasma process conditions in a plasma processing tool ([0104] “optimized EPM may be integrated with an etcher apparatus”; [0105] “The apparatus may further include one or more valve-controlled process gas inlets for flowing one or more process gases into the processing chamber, one or more gas outlets fluidically connected to one or more vacuum pumps for evacuating gases from the processing chamber”: the etcher apparatus generates the plasma and processes the wafer under the received process conditions);
(Claim 11) send instructions to the plasma processing tool to generate a plasma with the plasma process conditions ([0133] “System control instructions may include instructions for controlling the timing, mixture of gaseous and liquid reactants, chamber and/or station pressures”: the processor sends the process-control instructions that set the plasma-generating process conditions on the tool).
However, Tetiker et al. fails to teach explicitly wherein the plasma hypermodel correlates at least two sets of data using at least one matrix.
Guha teaches wherein the plasma hypermodel correlates at least two sets of data using at least one matrix ([0041]-[0044] “In one embodiment, processing state is defined as one or a combination of ions, radicals, electrons and neutral fluxes at a wafer plane with given wall boundary conditions.”; “Any particular data stream might not have all the information but mathematical combination of different data streams can identify the “processing state” of the plasma reactor.”; “Comparison between current and desired “processing state” will generate a “compensation vector” which can be transformed into reactor level variables (i.e., knob ID and amount of change to said knob) through a suitable mathematical transformation. Reactor level variables, in this example, are therefore the tuning knobs on the plasma reactor, e.g., gas flows, pressure, temperature, etc.”: the plasma-state model correlates two sets of data, namely the sensor data streams defining the wafer-plane plasma state and the reactor-level tuning-knob variables (gas flows, pressure, temperature), through a suitable mathematical transformation, i.e., the plasma hypermodel “correlates at least two sets of data using at least one matrix” as claimed). In particular, Guha teaches a plasma-reactor processing-state model in which the processing state, defined as ion, electron and neutral fluxes at a wafer plane, is identified from mathematical combination of sensor data streams and is related to the reactor tuning knobs, e.g., gas flows, pressure, temperature, through a suitable mathematical transformation executed by the reactor’s controller.
Tetiker et al. and Guha are analogous art because they are both from the same field of endeavor, plasma process modeling and control for semiconductor wafer processing.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of cited references. Thus, one of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to incorporate Guha into Tetiker et al.’s invention for the purpose of etch profile matching by surface kinetic model optimization to provide substantial real-time information about a plasma reactor’s processing environment, through which deviations from an ideal behavior are defined and a set of compensation values derived that can be applied to tuning knobs of the plasma reactor to correct for that deviation (Guha: [0038]1).
As per Claim 2 and 13, Tetiker et al. teaches wherein the plasma process conditions include one or more of pressure, gas chemistry, temperature, flow rate, source power, bias power, source power, or a pulse condition ([0038]-[0042] “input parameters include plasma parameters such as ion flux and chemical reaction parameters such as the probability that a particular chemical reaction will occur. These parameters (and particularly, in some embodiments, the plasma parameters) may be obtained from various sources, including other models which calculate them from general reactor configurations and process conditions such as pressure, substrate temperature, plasma source parameters (e.g., power, frequencies, duty cycles provided to the plasma source), reactants, and their flow rates.”).
As per Claim 3 and 14, Tetiker et al. teaches further comprising:
inputting the plasma parameters into a feature-scale profile model ([0037]-[0042] “he etch profile models (EPMs) compute a theoretically determined etch profile from a set of input etch reaction parameters (independent variables)… include plasma parameters such as ion flux and chemical reaction parameters such as the probability that a particular chemical reaction will occur.”, “EPMs take reaction parameters as independent variables and functionally generate etch profiles as response variables. ”); and
predicting, using the processor, a post-processing profile for the surface of the wafer with the feature-scale profile model ([0044] “an EPM is what is referred to in the art as a cell-based Monte Carlo surface reaction model… The models address various surface reaction mechanisms resulting in etching, sputtering, mixing, and deposition on the surface to predict profile evolution.”, [0052]- [0053] “Model Parameter Tuning/Optimization”).
As per Claim 4 and 15, Tetiker et al. teaches further comprising comparing, using the processor, the post-processing profile with an experimental reference ([0024], [0052]- [0054] “Each measured experimental etch profile provides a benchmark for tuning the computerized etch profile model. Accordingly, a series of calculations are performed with the etch profile model by applying the experimental etch profiles to see how the model deviates from reality in its prediction of etch profiles.”, “a tuned and/or optimized model reduces—and in some cases substantially minimizes—a metric which is related to (indicative of, quantifies, etc.) the combined differences between the etch profiles which are measured as a result of performing the etch experiments, and the corresponding computed etch profiles as generated from the model. ”, [0061] “By comparing the experimentally and theoretically generated etch profiles, a set of model parameters used by the etch profile model can be refined”).
As per Claim 5 and 16, Tetiker et al. teaches further comprising recalibrating correlations in the plasma hypermodel using the processor, wherein the post-processing profile is outside a convergence criterion of the experimental reference ([0058]-[0060] “ in operation 350 it is determined whether the currently specified model parameters are such that the error metric calculated in operation 340 is locally minimized (in terms of the space of model parameters), and if not, one or more values of the set of model parameters are modified in operation 360, and then used to generate a new set of etch profiles—repeating operation 335 as schematically indicated in FIG. 3's flowchart—and thereafter a new error metric is calculated in a repeating of operation 340. The process then proceeds again to operation 250 where it is determined whether this new combination of model parameters represents a local minimum over all the sets of input parameters as assessed by the error metric. If so, the optimization procedure concludes, as indicated in the figure. If not, the model parameters are again modified in operation 360 and the cycle repeats.”).
As per Claim 6 and 17, Tetiker et al. teaches wherein the experimental reference is a transmission electron microscopy (TEM) image or a cross-sectional scanning electron microscope (XSEM) image ([0050] “cross-sectional SEM…. SEM (wherein the experiment basically images a feature's etch profile)”).
As per Claim 7 and 18, Tetiker et al. fails to teach explicitly wherein the plasma hypermodel includes a matrix that is multiplied by the plasma process conditions.
Guha teaches wherein the plasma hypermodel includes a matrix that is multiplied by the plasma process conditions ([0083], [0086] “Without limitation, such examples may include linear/nonlinear regression, stepwise regression, decision tree learning”: the suitable mathematical transformation between the tuning-knob (plasma-process-condition) variables and the processing-state values, including linear regression, is a matrix that is multiplied by the plasma process conditions, i.e., the “matrix that is multiplied by the plasma process conditions” as claimed).
As per Claim 8, Tetiker et al. teaches wherein the plasma conditions are for an etch process, a deposition process, or an ion implant process ([0038], [0041] “the etch profile model, these variables are applied… the plasma parameters include local plasma properties such as fluxes and energies of particles such ions, radicals, photons, electrons, excited species, depositor species and their energy and angular distributions etc.”, [0104]-[0105] “ optimized EPM may be integrated with an etcher apparatus”, [0131], [0140] “within a processing chamber during film deposition and/or etching operations on substrates”).
As per Claim 12, Tetiker et al. teaches wherein the plasma processing tool is an etch tool, a deposition tool, or an ion implant tool ([0104]-[0105] “the etcher apparatus my constitute an inductively-coupled plasma (ICP) reactor;”).
Response to Arguments
4. Applicant's arguments filed on 06/22/2026 have been fully considered but they are not persuasive.
Examiner respectfully withdraws Claim Rejections - 35 USC § 101 in view of the amendment and/or applicant’s arguments.
Applicant’s arguments with respect to claims 1 and 11 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument – in view of Guha.
Applicants have argued that:
Amended claim 1 recites "determining, using the processor, plasma parameters at a surface of a wafer based on the plasma processing conditions with a plasma hypermodel, wherein the plasma hypermodel correlates at least two sets of data using at least one matrix." … This is not taught or suggested by Tetiker. Applicant respectfully submits that Tetiker does not teach or suggest such a hypermodel. Tetiker teaches a Monte Carlo model, as conceded in the Office Action. See Office Action at p. 9; Tetiker at [0044]. Tetiker does not disclose a hypermodel or Applicant's at least one matrix as recited in amended claims 1 and 11.
It is noted that Tetiker teaches a hypermodel as a plasma model of Testier determines the particle fluxes and energies at locations on the wafer from the reactor process conditions, i.e., the upstream plasma model is the “plasma hypermodel” as claimed. However, Testier does not teach “wherein the plasma hypermodel correlates at least two sets of data using at least one matrix" which is the limitation added by amendment, a mapping not previously applied for any teaching specifically challenged in the arguments.
Conclusion
5. 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.
6. Any inquiry concerning this communication or earlier communications from the examiner should be directed to EUNHEE KIM whose telephone number is (571)272-2164. The examiner can normally be reached Monday-Friday 9am-5pm ET.
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EUNHEE KIM
Primary Examiner
Art Unit 2188
/EUNHEE KIM/Primary Examiner, Art Unit 2188
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