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
Claims 1-19 and 20 are pending.
Drawings
The drawings filed on 05/18/2023 are accepted.
Oath/Declaration
4. For the record, the Examiner acknowledges that the Oath/Declaration submitted on 05/18/2023 has been received.
Information Disclosure Statement
5. The information disclosure statements (IDS) submitted on 05/18/2023 has been considered. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, an initialed and dated copy of Applicant's IDS form SB08 filed 05/18/2023 is attached to the instant Office action.
Preliminary Amendment
6. Applicants filed Preliminary Amendment dated 05/18/2023. Claims 20 and 22-30 have been cancelled by the Applicants.
Examiner Notes
7. Examiner cites particular columns, paragraphs, figures and line numbers in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner. The entire reference is considered to provide disclosure relating to the claimed invention. The claims & only the claims form the metes & bounds of the invention. Office personnel are to give the claims their broadest reasonable interpretation in light of the supporting disclosure. Unclaimed limitations appearing in the specification are not read into the claim. Prior art was referenced using terminology familiar to one of ordinary skill in the art. Such an approach is broad in concept and can be either explicit or implicit in meaning. Examiner's Notes are provided with the cited references to assist the applicant to better understand how the examiner interprets the applied prior art. Such comments are entirely consistent with the intent & spirit of compact prosecution.
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.
8. Claims 1-19, and 21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite a mathematical calculation; see MPEP 2106.04(a)(2)(I).
Step 1
The claims under Step 1 are directed towards a method (claims 1-10), a device or apparatus (claims 11-19) and a system (claim 21).
Claim 1 recites:
A method, implemented on a computer, of simulating performance of a semiconductor device model, (field of use) (See Step 2A Prong 2 and Step 2B)
the method comprising: establishing a carrier distribution function of the semiconductor device model, which indicates a distribution of carriers having a state of having particular energy at a particular position in a real space; (Mathematical Concepts)
computing one or more values corresponding to a solution of an approximate Boltzmann transport equation, as [Equation 1] below, with respect to the carrier distribution function, (Mathematical Concepts)
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outputting a performance value of the semiconductor device model, which corresponds to the one or more values that correspond to the solution of the approximate Boltzmann transport equation, as a simulation result value. (insignificant post solution action, outputting data)
Step 2A, prong 1:
The limitations of claim 1: “establishing a carrier distribution function of the semiconductor device model, …; computing one or more values corresponding to a solution of an approximate Boltzmann transport equation, as [Equation 1] …” recite an abstract idea because mathematical relationships and equations and then performing the calculations of those equations based on the variables, that fall within the Mathematical Concepts enumerated category of abstract ideas. According to conventional meaning in the art the claim element “carrier distribution function” describes “the probability that charge carriers (electrons and holes) occupy specific quantum states in terms of energy and momentum”. Further, the Boltzmann transport equation is purely ‘math equation’. Accordingly, at step 2A, prong one, claim 1 as a whole is found to recite a judicial exception and is drawn to an abstract idea.
Step 2A, Prong 2:
This judicial exception is not integrated into a practical application because the limitations fall within the Mathematical Concepts enumerated category of abstract ideas. Claim 1 has no additional limitations that integrate the abstract idea into a practical application. The limitation: “A method implemented on a computer, of simulating performance of a semiconductor device model” is recitation of field of use using generic computing components. The above limitation, that amount to merely indicating a field of use or technological environment and cannot integrate a judicial exception into a practical application. Additionally, the last limitation “outputting a performance value of the semiconductor device model, which corresponds to the one or more values that correspond to the solution of the approximate Boltzmann transport equation, as a simulation result value” is recitation of insignificant extra/post solution activity i.e., outputting data, which does not integrate a judicial exception into a practical application.
Step 2B:
The claim 1 as a whole does not include any further additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with in the Step 2A, Prong Two analysis, with respect to integration of the abstract idea into a practical application. The additional element: “A method implemented on a computer, of simulating performance of a semiconductor device model” is recitation of field of use using generic computing components. The above limitation, that amount to merely indicating a field of use or technological environment and does not amount to significantly more than the judicial exception. Additionally, the last limitation “outputting a performance value of the semiconductor device model, which corresponds to the one or more values that correspond to the solution of the approximate Boltzmann transport equation, as a simulation result value” is recitation of insignificant extra/post solution activity i.e., outputting data, which does not amount to significantly more than the judicial exception. Therefore, this limitation recite insignificant extra-solution activity activities are “well-understood, routine, conventional activity” according to Berkheimer v. HP, Inc., 881 F.3d 1360, 1368, 125 USPQ2d 1649, 1654 (see MPEP §2106.05(d)(ii) Example: “The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity: i. Receiving or transmitting data over a network, e.g., using the Internet to gather data … iv. Storing and retrieving information in memory”). Therefore, the abovementioned limitations of claim 1 do not amount to significantly more than the judicial exception.
Therefore, the claim 1 is not patent eligible under 35 USC 101.
Independent Claims 11 and 21 are substantially similar to claim 1 and therefore are rejected under the same rationale as stated above. Additionally, the claim elements in claim 11 having “A device comprising: a memory configured to store code data indicating …; a processor configured to execute machine-readable instructions that, when executed by the processor, cause the processor to simulate performance …”; and further claim 21 having claim elements “A system comprising: a semiconductor device; a measurement device …; a simulation device comprising a processor configured to execute machine-readable instructions that, when executed by the processor, cause the simulation device to simulate performance …” are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer. Accordingly, these additional elements do not integrate the abstract idea into a practical application because these generic computer elements do not impose any meaningful limits on practicing the abstract idea. See MPEP §2106.05(b) (“Merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection. Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 573 U.S. 208, 223-24, 110 USPQ2d 1976, 1983-84 (2014).”).
Claims 2-10 are rejected as a Judicial Exception (JE) since they do not add significantly more than the abstract idea or a practical application.
Claims 2-5 are dependent on independent claim 1 and include all the limitations of claim 1. These claims recite Mathematical Concepts enumerated category of abstract ideas.
Claims 6 and 7 are dependent on independent claim 1 and include all the limitations of claim 1. These claims recite non-functional data descriptions which do not add anything more to overcome the abstract idea.
Claims 8-10 are dependent on independent claim 1 and include all the limitations of claim 1. Claims 8-10 recite an abstract idea because limitations having mathematical relationships and equations, that fall within the Mathematical Concepts enumerated category of abstract ideas.
Dependent claims 12-19 are substantially similar to claims 2-4 and 6-10 respectively, therefore are rejected under the same rationale as stated above.
Therefore, the claims 1-19 and 21 are not patent eligible.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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 set forth in Graham, v. John Deere Co., 383 U.S.1.148 USPQ 459 (1966), that are applied 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 non-obviousness.
9. Claims 1-6 and 8-10 are rejected under 35 U.S.C. 103 as being unpatentable over an NPL paper “A review of recent advances in the spherical harmonics expansion method for semiconductor device simulation” by K. Rupp et al. (hereinafter Rupp, NPL published online: 2016) and in view of a Journal “2D semiconductor device simulations by WENO-Boltzmann schemes: Efficiency, boundary conditions and comparison to Monte Carlo methods” by Jose´ A. Carrillo et al. (hereinafter Carrillo, journal available online in 2005).
Regarding Claim 1, Rupp teaches a method, implemented on a computer, of simulating performance of a semiconductor device model, (Examiner would construe the claim element “performance” as “the carrier velocity and density may be the performance value of the semiconductor device model” according to Specification of current application para [0100].
Rupp disclosed in page 939 under ‘Abstract’: “The Boltzmann transport equation is commonly considered to be the best semi-classical description of carrier transport in semiconductors, providing precise information about the distribution of carriers with respect to time (one dimension), location (three dimensions), and momentum (three dimensions). … As a remedy, the higher accuracy provided by solutions of the Boltzmann transport equation is often exchanged for lower computational expense by using simpler models based on macroscopic quantities such as carrier density and mean carrier velocity.” In page 951 section 4.3 (right col.), it has been discussed that the distribution function obtained from a solution of the BTE is translated into a carrier density via the relation in Eq. (45). Further, in page 948 section 3.5 Fig. 8 shown “one-dimensional simulations of metal-oxide-semiconductor structures”).
the method comprising: Rupp teaches establishing a carrier distribution function of the semiconductor device model, which indicates a distribution of carriers having a state of having particular energy at a particular position in a real space; (Rupp disclosed in page 942 section 2 and 2.1: “In semi-classical transport theory, the spatial and temporal evolution of particles is described by a distribution function f (x, p, t). The distribution function then obeys the BTE … where v denotes the group velocity, F =−∇x(qψ + εb) is the force due to the particle charge q (negative for electrons, positive for holes), ψ is the electrostatic potential obtained either through self-consistent solutions with the Poisson equation … the distribution function is isotropic on equienergy surfaces in equilibrium and many scattering rates are in good approximation independent of the angles. Thus, spherical coordinates (k, θ, ϕ) in k-space are mapped to spherical coordinates (ε, θ, ϕ) in energy space, where we keep the angles unchanged and require the mapping to be unique in both directions.”).
Rupp teaches computing one or more values corresponding to a solution of an approximate Boltzmann transport equation, as [Equation 1] below, with respect to the carrier distribution function,
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Rupp disclosed in page 941-942 section 2 and 2.4: “In semi-classical transport theory, the spatial and temporal evolution of particles is described by a distribution function f (x, p, t). The distribution function then obeys the BTE … where v denotes the group velocity, F =−∇x (qψ + εb) is the force due to the particle charge q (negative for electrons, positive for holes), … and Q refers to the scattering operator. … The SHE method allows for accounting for spherical symmetries with respect to momentum. … A SHE can in principle be carried out for constant modulus k =∥k∥ of the transformed wave vector, or for constant kinetic energy ε. … A SHE of an arbitrary function u in energy space reads … for any given function u on the unit sphere with mild regularity requirements, the expansion coefficients ul,m are obtained from a projection onto the respective spherical harmonic: … The important detail in (6) is the generalized density of states entering the integrand. If the generalized density of states is modeled as spherically symmetric, … a system of equations for the unknown expansion coefficients fl,m needs to be derived from the BTE. Such a system is obtained by projecting (2) on to the spherical harmonics Yl,m. … and directly state the resulting set of equations: Eq. (8) … where we set g:= fZ motivated by (6), ˆj is the generalized current density given by … we combine ∇x and ∂/∂ε to yield a divergence in (x, ε)-space: …”. Further, in page 943-944 section 2.3: “The partial derivatives with respect to the spatial variable x and the kinetic energy ε describe the motion of carriers in free flight. … Therefore, the trajectories of carriers in free flight in (x, ε)-space mirror the potential profile throughout the device. … in order to address the exponential decay of the distribution function with kinetic energy and to better follow the trajectory of carriers in free flight. This ultimately results in a Scharfetter-Gummel-like stabilization of the discrete system. … The essence of the H-transformation is to apply a change of coordinates from kinetic energy ε to total energy H …”.
The Equation (8) in page 942 section 2.1 (left col.) is equivalent to the “Equation 1” in claim limitation. The disclosure above “distribution function”, “Q refers to the scattering operator” correspond to claim element “carrier distribution function and scattering term related to scattering of the carriers”, respectively. Further, the disclosure above “essence of the H-transformation is to apply a change of coordinates from kinetic energy ε to total energy H” correspond to claim element “total energy”).
However, Rupp doesn’t explicitly teach the limitation “outputting a performance value of the semiconductor device model, which corresponds to the one or more values that correspond to the solution of the approximate Boltzmann transport equation, as a simulation result value”.
Carrillo teaches outputting a performance value of the semiconductor device model, which corresponds to the one or more values that correspond to the solution of the approximate Boltzmann transport equation, as a simulation result value. (Carrillo disclosed in page 67-69 section 2.5: “In this section, we report the results of the simulation of a MOSFET whose geometry is sketched in Fig. 10 in which the contacts are doped with an electron density given by n+ =3 x 1017 cm-3. No doping is given in the n domain. Here, we have solved the Boltzmann–Poisson system disregarding completely the dynamics of the holes. The origin of the potential is set at the source and we consider applied biases of Vgate = 0.4 V at the gate and Vdrain = 1 V at the drain, respectively. … The steady-state results are reported in Figs. 11 and 12 which are quite clear about the qualitative transport of electrons through the device. The main difference with respect to the MESFET device relies on the fact that the singularities of the field and the square-root behavior of changing data points on the electric potential are in the oxide region where the transport of electrons is not computed through the Boltzmann equation. Thus, the appearance of the singularities of the force field does not affect the CFL condition in the area in which the transport equation is solved.” In page 70 Fig. 11 shown the MOSFET device BTE results t=5ps.Top left: the charge density ρ(10-17cm-3).
Rupp and Carrillo are analogous art because they are related to performing simulating performance of a semiconductor device using Boltzmann transport equation. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Rupp and Carrillo, to modify carrier distribution function of the semiconductor device in Rupp’s teaching, to include outputting the solution as performance value related to the Boltzmann transport equation in Carrillo’s teaching. The suggestion/motivation for doing so would have been obvious by Carrillo because “We develop and demonstrate the capability of a high-order accurate finite difference weighted essentially non-oscillatory (WENO) solver for the direct numerical simulation of transients for a two space dimensional Boltzmann transport equation (BTE) coupled with the Poisson equation modelling semiconductor devices such as the MESFET and MOSFET. We compare the simulation results with those obtained by a direct simulation Monte Carlo solver for the same geometry. The classical widespread method to investigate transport processes in semiconductor devices at the microscopic level is based on the direct simulation Monte Carlo (DSMC) method. The main advantage of this approach consists in the simple way to take into account different forces acting on the electrons. In this paper, we have focused our attention on solving the BTE equation deterministically and on using the DSMC scheme, to check the accuracy, the performance of the deterministic numerical scheme and the agreement, except for small spatial regions, with stochastic solutions”. (Carrillo disclosed in page 55 (under ‘Abstract’), page 70 (section 3, 1st para), and page 79 (last para)).
Regarding Claim 2, Rupp and Carrillo teach the method of claim 1, even Rupp teaches about “electrostatic potential” (in page 951), however Rupp doesn’t explicitly teach the whole limitation “~V is determined based on a value closest to a potential set for the semiconductor device model”.
wherein Carrillo teaches ~V is determined based on a value closest to a potential set for the semiconductor device model. (Carrillo discussed in page 56 section 1 (under Equations 1.3 and 1.4) that Eqs. (1.1), (1.3) and (1.4) give the Boltzmann–Poisson system for electron transport in semiconductors, where V is the electric potential (in Eqs. (1.3) and (1.4)). In page 61 section 2.2.1 (last para): “In the particular case of the jump of a boundary condition in a flat boundary surface (zero curvature), such as in the boundary given by y0 = 0.2, the angle is v = π which makes the electric potential V = r1/2sin(b/2) + C0.” Further, in page 67 section 2.5: “In this section, we report the results of the simulation of a MOSFET whose geometry is sketched in Fig. 10 in which the contacts are doped with an electron density given by n+ =3 x 1017 cm-3. … Here, we have solved the Boltzmann–Poisson system disregarding completely the dynamics of the holes. The origin of the potential is set at the source and we consider applied biases of Vgate = 0.4 V at the gate and Vdrain = 1 V at the drain, respectively.”).
Rupp and Carrillo are analogous art because they are related to performing simulating performance of a semiconductor device using Boltzmann transport equation. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Rupp and Carrillo, to modify carrier distribution function of the semiconductor device in Rupp’s teaching, to include outputting the solution as performance value related to the Boltzmann transport equation in Carrillo’s teaching. The suggestion/motivation for doing so would have been obvious by Carrillo because “We develop and demonstrate the capability of a high-order accurate finite difference weighted essentially non-oscillatory (WENO) solver for the direct numerical simulation of transients for a two space dimensional Boltzmann transport equation (BTE) coupled with the Poisson equation modelling semiconductor devices such as the MESFET and MOSFET. We compare the simulation results with those obtained by a direct simulation Monte Carlo solver for the same geometry. The classical widespread method to investigate transport processes in semiconductor devices at the microscopic level is based on the direct simulation Monte Carlo (DSMC) method. The main advantage of this approach consists in the simple way to take into account different forces acting on the electrons. In this paper, we have focused our attention on solving the BTE equation deterministically and on using the DSMC scheme, to check the accuracy, the performance of the deterministic numerical scheme and the agreement, except for small spatial regions, with stochastic solutions”. (Carrillo disclosed in page 55 (under ‘Abstract’), page 70 (section 3, 1st para), and page 79 (last para)).
Regarding Claim 3, Rupp and Carrillo teach the method of claim 2, even Rupp teaches about “electrostatic potential” (in page 951), however Rupp doesn’t explicitly teach the whole limitation “~V is determined based on a value closest to a potential set for the semiconductor device model and is within a range”.
wherein Carrillo teaches ~V is determined based on a value closest to a potential set for the semiconductor device model and is within a range. (Carrillo discussed in page 56 section 1 (under Equations 1.3 and 1.4) that Eqs. (1.1), (1.3) and (1.4) give the Boltzmann–Poisson system for electron transport in semiconductors, where V is the electric potential (in Eqs. (1.3) and (1.4)). In page 61 section 2.2.1 (last para): “In the particular case of the jump of a boundary condition in a flat boundary surface (zero curvature), such as in the boundary given by y0 = 0.2, the angle is v = π which makes the electric potential V = r1/2sin(b/2) + C0.” Further, in page 67-69 section 2.5: “In this section, we report the results of the simulation of a MOSFET whose geometry is sketched in Fig. 10 in which the contacts are doped with an electron density given by n+ =3 x 1017 cm-3. … Here, we have solved the Boltzmann–Poisson system disregarding completely the dynamics of the holes. The origin of the potential is set at the source and we consider applied biases of Vgate = 0.4 V at the gate and Vdrain = 1 V at the drain, respectively. … The steady-state results are reported in Figs. 11 and 12 which are quite clear about the qualitative transport of electrons through the device. The main difference with respect to the MESFET device relies on the fact that the singularities of the field and the square-root behavior of changing data points on the electric potential are in the oxide region”. In page 70 Fig. 11 shown MOSFET device BTE results t=5ps, bottom left the electric potential V. Fig. 11 has shown the electric potential values within range).
Rupp and Carrillo are analogous art because they are related to performing simulating performance of a semiconductor device using Boltzmann transport equation. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Rupp and Carrillo, to modify carrier distribution function of the semiconductor device in Rupp’s teaching, to include outputting the solution as performance value related to the Boltzmann transport equation in Carrillo’s teaching. The suggestion/motivation for doing so would have been obvious by Carrillo because “We develop and demonstrate the capability of a high-order accurate finite difference weighted essentially non-oscillatory (WENO) solver for the direct numerical simulation of transients for a two space dimensional Boltzmann transport equation (BTE) coupled with the Poisson equation modelling semiconductor devices such as the MESFET and MOSFET. We compare the simulation results with those obtained by a direct simulation Monte Carlo solver for the same geometry. The classical widespread method to investigate transport processes in semiconductor devices at the microscopic level is based on the direct simulation Monte Carlo (DSMC) method. The main advantage of this approach consists in the simple way to take into account different forces acting on the electrons. In this paper, we have focused our attention on solving the BTE equation deterministically and on using the DSMC scheme, to check the accuracy, the performance of the deterministic numerical scheme and the agreement, except for small spatial regions, with stochastic solutions”. (Carrillo disclosed in page 55 (under ‘Abstract’), page 70 (section 3, 1st para), and page 79 (last para)).
Regarding Claim 4, Rupp and Carrillo teach the method of claim 3, however Rupp doesn’t explicitly teach the limitation “the range comprises discretized potentials, and ~V is determined based on a value closest to the potential set for the semiconductor device model among the discretized potentials included in the range”.
wherein Carrillo teaches the range comprises discretized potentials, and ~V is determined based on a value closest to the potential set for the semiconductor device model among the discretized potentials included in the range. (Examiner would construe the claim element “discretized” as “a boundary condition of a semiconductor device operation condition is applied to a discretized time scale” according to Specification of current application para [0099].
Carrillo disclosed in page 55-56 section 1.: “Electron transport in semiconductors, with space inhomogeneities at a tenth micron scale orders under long-range interactions due to strong applied bias, needs to be modelled … One such type of models is the semiclassical approximation given by the Boltzmann transport equation (BTE) for semiconductors: … Following standard notation for statistical descriptions of electron transport, f represents the electron probability density function (pdf) in phase space k at the physical location x and time t.” In page 60 heading ‘Gate contact’: “We first describe the boundary condition for the MESFET simulation. Here we set a condition that yields an incoming mean velocity entering through the gate which is equivalent to decaying density in space and time due to the conservation of charge.” In page 65 section 2.3: “The Poisson equation (1.3) for the potential V and the electric field (1.4) are solved by the standard central difference scheme, with the given Vbias boundary conditions at the source, drain and gate. The time discretization is by the third-order TVD Runge–Kutta method.”
Further, in page 72 section 72 (3rd and 5th para): “it is useful to recall two aspects of DSMC methods. The first one, which relates to the boundary conditions, is the rule that is used when an electron must be injected into the device. The second one relates to the length of the free flight time. … a well-accepted starting point to decide how many particles must be injected is called charge neutrality. In practice, after every time step of DSMC, we consider the cells in the vicinity of the contacts, usually those including boundaries, where it is possible to inject electrons, and we evaluate the charge density in each of these cells”. The disclosure above “time step” is related to the limitation “discretized potentials included in the range”. Further, the disclosure “statistical descriptions of electron transport, f represents the electron probability density function (pdf) at the physical location x and time t; an incoming mean velocity entering through the gate which is equivalent to decaying density in space and time due to the conservation of charge; Poisson equation (1.3) for the potential V and the electric field (1.4) are solved with the given Vbias boundary conditions at the source, drain and gate, the time discretization is by the third-order TVD Runge–Kutta method; a well-accepted starting point to decide how many particles must be injected is called charge neutrality. In practice, after every time step of DSMC, we consider the cells in the vicinity of the contacts” correspond to claim limitation “the range comprises discretized potentials, and ~V is determined based on a value closest to the potential set for the semiconductor device model among the discretized potentials included in the range”).
Rupp and Carrillo are analogous art because they are related to performing simulating performance of a semiconductor device using Boltzmann transport equation. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Rupp and Carrillo, to modify carrier distribution function of the semiconductor device in Rupp’s teaching, to include outputting the solution as performance value related to the Boltzmann transport equation in Carrillo’s teaching. The suggestion/motivation for doing so would have been obvious by Carrillo because “We develop and demonstrate the capability of a high-order accurate finite difference weighted essentially non-oscillatory (WENO) solver for the direct numerical simulation of transients for a two space dimensional Boltzmann transport equation (BTE) coupled with the Poisson equation modelling semiconductor devices such as the MESFET and MOSFET. We compare the simulation results with those obtained by a direct simulation Monte Carlo solver for the same geometry. The classical widespread method to investigate transport processes in semiconductor devices at the microscopic level is based on the direct simulation Monte Carlo (DSMC) method. The main advantage of this approach consists in the simple way to take into account different forces acting on the electrons. In this paper, we have focused our attention on solving the BTE equation deterministically and on using the DSMC scheme, to check the accuracy, the performance of the deterministic numerical scheme and the agreement, except for small spatial regions, with stochastic solutions”. (Carrillo disclosed in page 55 (under ‘Abstract’), page 70 (section 3, 1st para), and page 79 (last para)).
Regarding Claim 5, Rupp and Carrillo teach the method of claim 4, however Rupp doesn’t explicitly teach the limitation “a size of the range is less than or equal to a reference size”.
wherein Carrillo teaches a size of the range is less than or equal to a reference size. (Carrillo disclosed in page 77-78 section 3: “We denote by P[k(t)] dt the probability that an electron in the state k encounters a collision during the time interval dt. When considering the motion of this single electron, k(t) denotes the wave vector k as a function of the time t. Let t = 0 be the time of the last collision. Then, the probability P(t) that the electron will encounter its next collision during dt is given by … We remark that we must use the above formula after every collision and for any particle, that is, if we consider another electron, then its motion will be different and therefore it will have a different probability P[k(t)]dt. … Then approximate P[k(t)] from (3.1) with the constant Γ. So, we obtain … Since r = P/Γ is a random number distributed uniformly between 0 and 1, we can choose the free flight duration tr according to the rule tr = -1/Γ log (r). Therefore, every electron has a proper time tr which is again generated after every collision drawing the random number r.”
The disclosure “P[k(t)] dt the probability that an electron in the state k encounters a collision during the time interval dt; t = 0 be the time of the last collision, the probability P(t) that the electron will encounter its next collision during dt; we can choose the free flight duration tr; every electron has a proper time tr which is again generated after every collision drawing the random number r” correspond to claim limitation “a size of the range is less than or equal to a reference size”).
Rupp and Carrillo are analogous art because they are related to performing simulating performance of a semiconductor device using Boltzmann transport equation. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Rupp and Carrillo, to modify carrier distribution function of the semiconductor device in Rupp’s teaching, to include outputting the solution as performance value related to the Boltzmann transport equation in Carrillo’s teaching. The suggestion/motivation for doing so would have been obvious by Carrillo because “We develop and demonstrate the capability of a high-order accurate finite difference weighted essentially non-oscillatory (WENO) solver for the direct numerical simulation of transients for a two space dimensional Boltzmann transport equation (BTE) coupled with the Poisson equation modelling semiconductor devices such as the MESFET and MOSFET. We compare the simulation results with those obtained by a direct simulation Monte Carlo solver for the same geometry. The classical widespread method to investigate transport processes in semiconductor devices at the microscopic level is based on the direct simulation Monte Carlo (DSMC) method. The main advantage of this approach consists in the simple way to take into account different forces acting on the electrons. In this paper, we have focused our attention on solving the BTE equation deterministically and on using the DSMC scheme, to check the accuracy, the performance of the deterministic numerical scheme and the agreement, except for small spatial regions, with stochastic solutions”. (Carrillo disclosed in page 55 (under ‘Abstract’), page 70 (section 3, 1st para), and page 79 (last para)).
Regarding Claim 6, Rupp and Carrillo teach the method of claim 1, however Rupp doesn’t explicitly teach the limitation “the performance value of the semiconductor device model comprises a dynamic parameter indicating a characteristic transient with time”.
wherein Carrillo teaches the performance value of the semiconductor device model comprises a dynamic parameter indicating a characteristic transient with time. (Carrillo disclosed in page 77-78 section 3: “the free flight duration, is based on the total scattering rate. There is a theoretical formula to evaluate this parameter. We denote by P[k(t)] dt the probability that an electron in the state k encounters a collision during the time interval dt. When considering the motion of this single electron, k(t) denotes the wave vector k as a function of the time t. Let t = 0 be the time of the last collision. Then, the probability P(t) that the electron will encounter its next collision during dt is given by … We remark that we must use the above formula after every collision and for any particle, that is, if we consider another electron, then its motion will be different and therefore it will have a different probability P[k(t)]dt. … Then approximate P[k(t)] from (3.1) with the constant Γ. So, we obtain … Since r = P/Γ is a random number distributed uniformly between 0 and 1, we can choose the free flight duration tr according to the rule tr = -1/Γ log (r). Therefore, every electron has a proper time tr which is again generated after every collision drawing the random number r.”
The disclosure “P[k(t)] dt the probability that an electron in the state k encounters a collision during the time interval dt; t = 0 be the time of the last collision, the probability P(t) that the electron will encounter its next collision during dt; we can choose the free flight duration tr; every electron has a proper time tr which is again generated after every collision drawing the random number r” correspond to claim limitation “a dynamic parameter indicating a characteristic transient with time”).
Rupp and Carrillo are analogous art because they are related to performing simulating performance of a semiconductor device using Boltzmann transport equation. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Rupp and Carrillo, to modify carrier distribution function of the semiconductor device in Rupp’s teaching, to include outputting the solution as performance value related to the Boltzmann transport equation in Carrillo’s teaching. The suggestion/motivation for doing so would have been obvious by Carrillo because “We develop and demonstrate the capability of a high-order accurate finite difference weighted essentially non-oscillatory (WENO) solver for the direct numerical simulation of transients for a two space dimensional Boltzmann transport equation (BTE) coupled with the Poisson equation modelling semiconductor devices such as the MESFET and MOSFET. We compare the simulation results with those obtained by a direct simulation Monte Carlo solver for the same geometry. The classical widespread method to investigate transport processes in semiconductor devices at the microscopic level is based on the direct simulation Monte Carlo (DSMC) method. The main advantage of this approach consists in the simple way to take into account different forces acting on the electrons. In this paper, we have focused our attention on solving the BTE equation deterministically and on using the DSMC scheme, to check the accuracy, the performance of the deterministic numerical scheme and the agreement, except for small spatial regions, with stochastic solutions”. (Carrillo disclosed in page 55 (under ‘Abstract’), page 70 (section 3, 1st para), and page 79 (last para)).
Regarding Claim 8, Rupp and Carrillo teach the method of claim 1, wherein Rupp teaches h denotes total energy based on [Equation 2] below, h = ε + ~V the total energy comprising carrier kinetic energy ε and ~V. (Rupp disclosed in page 943-944 section 2.3: “The partial derivatives with respect to the spatial variable x and the kinetic energy ε describe the motion of carriers in free flight. … Therefore, the trajectories of carriers in free flight in (x, ε)-space mirror the potential profile throughout the device. … in order to address the exponential decay of the distribution function with kinetic energy and to better follow the trajectory of carriers in free flight. … The essence of the H-transformation is to apply a change of coordinates from kinetic energy ε to total energy H = ε +εb +qψ(x), through which the derivative with respect to energy in (18) … It is important to note that the variable transformation results in an additional term containing the derivative of the SHE expansion coefficients with respect to total energy H and the time derivative of the potential.” It has been disclosed in page 941 section 2 (left col.): “F =−∇x (qψ + εb) is the force due to the particle charge q (negative for electrons, positive for holes), ψ is the electrostatic potential obtained …εb identifies the band edge (minimum for electrons, maximum for holes),”
The disclosure above “ψ is the electrostatic potential obtained” corresponds to claim element “~V denotes the potential set for the semiconductor device model”).
Regarding Claim 9, Rupp and Carrillo teach the method of claim 8, wherein Rupp teaches F denotes an electric force with respect to a potential set for the semiconductor device model based on [Equation 3] below, [Equation 3] F = -∇V where V denotes the potential set for the semiconductor device model. (Rupp disclosed in page 941 section 2 (left col.): “F =−∇x (qψ + εb) is the force due to the particle charge q (negative for electrons, positive for holes), ψ is the electrostatic potential obtained …εb identifies the band edge (minimum for electrons, maximum for holes), …”.
The disclosure “F =−∇x (qψ + εb)” relates to the [Equation 3] F = -∇V, where the term (qψ + εb) is equivalent to term V which denotes the potential set for the semiconductor device model).
Regarding Claim 10, Rupp and Carrillo teach the method of claim 8, wherein Rupp teaches Al,l’ and Bl,l’, variably change according to the real space and the total energy, respectively. (Rupp disclosed in page 943-944 section 2.3: “The partial derivatives with respect to the spatial variable x and the kinetic energy ε describe the motion of carriers in free flight. … Therefore, the trajectories of carriers in free flight in (x, ε)-space mirror the potential profile throughout the device. … in order to address the exponential decay of the distribution function with kinetic energy and to better follow the trajectory of carriers in free flight. … The essence of the H-transformation is to apply a change of coordinates from kinetic energy ε to total energy H = ε +εb +qψ(x), …”.
Further, in page 954 section 5.2 (left col.): “Small-signal analysis requires that the BTE is linearized together with the Poisson equation at the bias point under inspection, hence fluctuations of the electrostatic potential play a role. Such fluctuations can be considered directly through the force term when using a formulation based on kinetic energy ε as in (18), but additional attention is required when using the H-transformation. Since the location of the band edge in (x, H)-space depends on the electrostatic potential, a naive application of the SHE method for small-signal analysis yields time-varying coefficients.”).
Claims 11-19 and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Enda (Patent No. US6304834B1) and in view of Rupp and Carrillo.
Regarding Claim 11, Enda teaches a device comprising: a memory configured to store code data indicating an approximate Boltzmann transport equation and characteristics data indicating characteristics of a semiconductor device model; (Enda disclosed in col. 5 lines 25-28: “another object of the present invention is to provide a recording medium storing a simulation program that can accurately calculate the carrier current density vector and accurately obtain the solutions of the basic equations.” In col. 10 lines 42-47 and 52-65: “the device simulator according to the first embodiment of the present invention has a function of displaying the thus obtained distributions of the potential, the electric field and the current within the semiconductor device, the carrier distributions of electrons and holes within it, … a processor 71 for simulating the device behavior; an output unit 64 for outputting the simulation result, a data memory 62 for storing therein a predetermined data necessary for the analysis of the characteristics of the semiconductor device and the like; and a program memory 63 for storing therein a device simulation program and the like. … The voltage/current setting unit 72 and the characteristics calculation unit 73 may have the dedicated circuits respectively, or may comprise hardware for a general purpose computer system in which the respective functions of the units are given by a software program.”
In col. 2 lines 8-13 disclosed: “The basic equations required to obtain the electrical characteristics of the semiconductor device are simultaneous differential equations of the potential distribution and the carrier concentration (actually, the electron concentration in and the hole concentration p), as represented by the following equations (1) to (3):” Further in col. 3 lines 23-25 discussed about “the Boltzmann's constant (k)”).
and Enda teaches a processor configured to execute machine-readable instructions that, when executed by the processor, cause the processor to simulate performance of the semiconductor device model, based on the code data and the characteristic data, (Enda disclosed in col. 10 lines 49-65: “as shown in FIG. 6A, a device simulator 70 of the present invention at least contains: … a processor 71 for simulating the device behavior; an output unit 64 for outputting the simulation result, a data memory 62 for storing therein a predetermined data necessary for the analysis of the characteristics of the semiconductor device and the like; and a program memory 63 for storing therein a device simulation program and the like. The processor 71 at least contains a voltage/current setting unit 72 for setting the terminal voltages or the terminal currents conditions and a characteristics calculation unit 73. The voltage/current setting unit 72 and the characteristics calculation unit 73 may have the dedicated circuits respectively, or may comprise hardware for a general purpose computer system in which the respective functions of the units are given by a software program”).
However, Enda doesn’t explicitly teach the limitation “the processor is further configured to establish a carrier distribution function of the semiconductor device model, which indicates a distribution of carriers having a state of having particular energy at a particular position in a real space, to compute one or more values corresponding to a solution of an approximate Boltzmann transport equation, as [Equation 1] below, with respect to the carrier distribution function,
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and output a performance value of the semiconductor device model as a simulation result value, to process the performance value of the semiconductor device model, based on the one or more values that corresponds to the solution of the approximate Boltzmann transport equation”.
wherein Rupp teaches the processor is further configured to establish a carrier distribution function of the semiconductor device model, which indicates a distribution of carriers having a state of having particular energy at a particular position in a real space, (Rupp disclosed in page 942 section 2 and 2.1: “In semi-classical transport theory, the spatial and temporal evolution of particles is described by a distribution function f (x, p, t). The distribution function then obeys the BTE … where v denotes the group velocity, F =−∇x(qψ + εb) is the force due to the particle charge q (negative for electrons, positive for holes), ψ is the electrostatic potential obtained either through self-consistent solutions with the Poisson equation … the distribution function is isotropic on equienergy surfaces in equilibrium and many scattering rates are in good approximation independent of the angles. Thus, spherical coordinates (k, θ, ϕ) in k-space are mapped to spherical coordinates (ε, θ, ϕ) in energy space, where we keep the angles unchanged and require the mapping to be unique in both directions.”).
Rupp teaches to compute one or more values corresponding to a solution of an approximate Boltzmann transport equation, as [Equation 1] below, with respect to the carrier distribution function, [Equation 1]
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Rupp disclosed in page 941-942 section 2 and 2.4: “In semi-classical transport theory, the spatial and temporal evolution of particles is described by a distribution function f (x, p, t). The distribution function then obeys the BTE … where v denotes the group velocity, F =−∇x (qψ + εb) is the force due to the particle charge q (negative for electrons, positive for holes), … and Q refers to the scattering operator. … The SHE method allows for accounting for spherical symmetries with respect to momentum. … A SHE can in principle be carried out for constant modulus k =∥k∥ of the transformed wave vector, or for constant kinetic energy ε. … A SHE of an arbitrary function u in energy space reads … for any given function u on the unit sphere with mild regularity requirements, the expansion coefficients ul,m are obtained from a projection onto the respective spherical harmonic: … The important detail in (6) is the generalized density of states entering the integrand. If the generalized density of states is modeled as spherically symmetric, … a system of equations for the unknown expansion coefficients fl,m needs to be derived from the BTE. Such a system is obtained by projecting (2) on to the spherical harmonics Yl,m. … and directly state the resulting set of equations: Eq. (8) … where we set g:= fZ motivated by (6), ˆj is the generalized current density given by … we combine ∇x and ∂/∂ε to yield a divergence in (x, ε)-space: …”. Further, in page 943-944 section 2.3: “The partial derivatives with respect to the spatial variable x and the kinetic energy ε describe the motion of carriers in free flight. … Therefore, the trajectories of carriers in free flight in (x, ε)-space mirror the potential profile throughout the device. … in order to address the exponential decay of the distribution function with kinetic energy and to better follow the trajectory of carriers in free flight. This ultimately results in a Scharfetter-Gummel-like stabilization of the discrete system. … The essence of the H-transformation is to apply a change of coordinates from kinetic energy ε to total energy H …”.
The Equation (8) in page 942 section 2.1 (left col.) is equivalent to the “Equation 1” in claim limitation. The disclosure above “distribution function”, “Q refers to the scattering operator” correspond to claim element “carrier distribution function and scattering term related to scattering of the carriers”, respectively. Further, the disclosure above “essence of the H-transformation is to apply a change of coordinates from kinetic energy ε to total energy H” correspond to claim element “total energy”).
Enda and Rupp are analogous art because they are related to performing simulating performance of a semiconductor device using Boltzmann transport equation. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Enda and Rupp, to modify a measurement device configured to measure characteristics of the semiconductor device of Enda, to include establishing carrier distribution function of the semiconductor device where carriers having a state of having particular energy and real space in Rupp’s teaching. The suggestion/motivation for doing so would have been obvious by Rupp because “Recent developments for the deterministic spherical harmonics expansion (SHE) method have reduced the computational cost for solving the Boltzmann transport equation, enabling the computation of carrier distribution functions even for spatially three-dimensional device simulations. Small-signal analysis requires that the BTE is linearized together with the Poisson equation at the bias point under inspection, hence fluctuations of the electrostatic potential play a role. Such fluctuations can be considered directly through the force term when using a formulation based on kinetic energy. We focus on applications where the SHE method provides significant progress over other methods used in the past.” (Rupp disclosed in page 939 under ‘Abstract’, page 953 section 5 (right col.) and page 954 section 5.2 (left col.)).
However, Enda and Rupp do not explicitly teach the limitation “output a performance value of the semiconductor device model as a simulation result value, to process the performance value of the semiconductor device model, based on the one or more values that corresponds to the solution of the approximate Boltzmann transport equation”.
and Carrillo teaches output a performance value of the semiconductor device model as a simulation result value, to process the performance value of the semiconductor device model, based on the one or more values that corresponds to the solution of the approximate Boltzmann transport equation. (Carrillo disclosed in page 67-69 section 2.5: “In this section, we report the results of the simulation of a MOSFET whose geometry is sketched in Fig. 10 in which the contacts are doped with an electron density given by n+ =3 x 1017 cm-3. No doping is given in the n domain. Here, we have solved the Boltzmann–Poisson system disregarding completely the dynamics of the holes. The origin of the potential is set at the source and we consider applied biases of Vgate = 0.4 V at the gate and Vdrain = 1 V at the drain, respectively. … The steady-state results are reported in Figs. 11 and 12 which are quite clear about the qualitative transport of electrons through the device. The main difference with respect to the MESFET device relies on the fact that the singularities of the field and the square-root behavior of changing data points on the electric potential are in the oxide region where the transport of electrons is not computed through the Boltzmann equation. Thus, the appearance of the singularities of the force field does not affect the CFL condition in the area in which the transport equation is solved.” In page 70 Fig. 11 shown the MOSFET device BTE results t=5ps.Top left: the charge density ρ(10-17cm-3).
Enda, Rupp and Carrillo are analogous art because they are related to performing simulating performance of a semiconductor device using Boltzmann transport equation. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Enda, Rupp and Carrillo, to modify carrier distribution function of the semiconductor device in Rupp’s teaching, to include outputting the solution as performance value related to the Boltzmann transport equation in Carrillo’s teaching. The suggestion/motivation for doing so would have been obvious by Carrillo because “We develop and demonstrate the capability of a high-order accurate finite difference weighted essentially non-oscillatory (WENO) solver for the direct numerical simulation of transients for a two space dimensional Boltzmann transport equation (BTE) coupled with the Poisson equation modelling semiconductor devices such as the MESFET and MOSFET. We compare the simulation results with those obtained by a direct simulation Monte Carlo solver for the same geometry. The classical widespread method to investigate transport processes in semiconductor devices at the microscopic level is based on the direct simulation Monte Carlo (DSMC) method. The main advantage of this approach consists in the simple way to take into account different forces acting on the electrons. In this paper, we have focused our attention on solving the BTE equation deterministically and on using the DSMC scheme, to check the accuracy, the performance of the deterministic numerical scheme and the agreement, except for small spatial regions, with stochastic solutions”. (Carrillo disclosed in page 55 (under ‘Abstract’), page 70 (section 3, 1st para), and page 79 (last para)).
Regarding Claims 12-15, Enda, Rupp and Carrillo teach the device of claim 11, are incorporating the rejections of claims 2-4 and 6 respectively, because claims 12-15 have substantially similar claim language as claims 2-4 and 6, therefore claims 12-15 are rejected under 35 U.S.C. 103 as being unpatentable over Enda, Rupp and Carrillo as discussed above for substantially similar rationale.
Regarding Claims 17-19, Enda, Rupp and Carrillo teach the device of claim 11, are incorporating the rejections of claims 8-10 respectively, because claims 17-19 have substantially similar claim language as claims 8-10, therefore claims 17-19 are rejected under 35 U.S.C. 103 as being unpatentable over Enda, Rupp and Carrillo as discussed above for substantially similar rationale.
Regarding Claim 21, the same ground of rejection is made as discussed in claim 1 for substantially similar rationale, therefore claim 21 is rejected under 35 U.S.C. 103 as being unpatentable over Enda, Rupp and Carrillo as discussed above for substantially similar rationale. In addition, claim 21 recites following limitations:
Enda teaches a system comprising: a semiconductor device; a measurement device configured to measure characteristics of the semiconductor device; (Enda disclosed in col. 2 lines 34-37: “As shown in FIG. 1, in the device simulation, a finite number of grid points (mesh points) are firstly defined inside and around the semiconductor device targeted by the simulation (referred to as an analysis area).” In col. 10 lines 36-41: “A device simulator (device simulation apparatus) according to a first embodiment of the present invention has a function of simulating the behavior of the semiconductor device, after receiving the geometrical structure, the impurity profile and the like obtained by a process simulation, as well as the electric boundary conditions, …”).
and Enda teaches a simulation device comprising a processor configured to execute machine-readable instructions that, when executed by the processor, cause the simulation device to simulate performance of a semiconductor device model corresponding to the semiconductor device, (Enda disclosed in col. 10 lines 49-65: “as shown in FIG. 6A, a device simulator 70 of the present invention at least contains: … a processor 71 for simulating the device behavior; an output unit 64 for outputting the simulation result, a data memory 62 for storing therein a predetermined data necessary for the analysis of the characteristics of the semiconductor device and the like; and a program memory 63 for storing therein a device simulation program and the like. … The voltage/current setting unit 72 and the characteristics calculation unit 73 may have the dedicated circuits respectively, or may comprise hardware for a general purpose computer system in which the respective functions of the units are given by a software program”).
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Rupp and Carrillo and in view of an NPL “Computer-aided system for measuring the static parameters of semiconductor devices” by V. N. Petrov et al. (hereinafter Petrov, NPL published in 1996).
Regarding Claim 7, Rupp and Carrillo teach the method of claim 1, even Carrillo teach the performance value of the semiconductor device model. (Carrillo disclosed in page 67-69 section 2.5: “In this section, we report the results of the simulation of a MOSFET whose geometry is sketched in Fig. 10 in which the contacts are doped with an electron density given by n+ =3 x 1017 cm-3. No doping is given in the n domain. Here, we have solved the Boltzmann–Poisson system disregarding completely the dynamics of the holes. The origin of the potential is set at the source and we consider applied biases of Vgate = 0.4 V at the gate and Vdrain = 1 V at the drain, respectively. … The steady-state results are reported in Figs. 11 and 12 which are quite clear about the qualitative transport of electrons through the device. The main difference with respect to the MESFET device relies on the fact that the singularities of the field and the square-root behavior of changing data points on the electric potential are in the oxide region where the transport of electrons is not computed through the Boltzmann equation. Thus, the appearance of the singularities of the force field does not affect the CFL condition in the area in which the transport equation is solved.” In page 70 Fig. 11 shown the MOSFET device BTE results t=5ps.Top left: the charge density ρ(10-17cm-3).
However, Rupp and Carrillo do not explicitly teach the limitation “the semiconductor device model comprises a static parameter indicating a characteristic independent of time”.
wherein Petrov teaches the semiconductor device model comprises a static parameter indicating a characteristic independent of time. (Examiner would construe the claim element “static parameter” as “DC current” according to Specification of current application para [0084]. That means “static parameter” in a semiconductor circuit or device is a “steady-state characteristic measured under constant DC conditions where voltages and currents do not change over time”.
Petrov disclosed in page 1240 (1st para): “To measure the static characteristics it is first necessary to specify the type of input (current or voltage) and, second, to measure the currents and/or voltages in the input and output circuits of the device being investigated.” In page 1242 (in 6th to 7th para): “To measure the characteristics of bipolar transistors both a voltage source and a current source can be used. The circuit employed to measure the static characteristics of a bipolar transistor connected in the common-emitter configuration is shown in Fig. 1. … The measuring system enables one to measure the following static characteristics of bipolar transistors in the common-emitter and common-base configurations: … the static current transfer factor (normal and inverse) as a function of the collector current for different collector-emitter (collector-base) voltages;” It has been disclosed in page 1243 (in 3rd para): “The areas of application of this computer-aided measuring system are as follows: -measurement and visual observation of the static characteristics of semiconductor devices; -identification of the parameters of devices from the measured dc characteristics;”
The disclosure above “measuring system enables one to measure the following static characteristics of bipolar transistors; the static current transfer factor (normal and inverse) as a function of the collector current for different collector-emitter (collector-base) voltages; identification of the parameters of devices from the measured dc characteristics;” correspond to claim limitation “the semiconductor device model comprises a static parameter indicating a characteristic independent of time”.).
Rupp, Carrillo and Petrov are analogous art because they are related to measuring a variety of characteristics of practical semiconductor devices. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Rupp, Carrillo and Petrov to modify outputting the solution as performance value related to the Boltzmann transport equation in Carrillo’s teaching, to include static parameter indicating a characteristic in semiconductor device in Petrov’s teaching. The suggestion/motivation for doing so would have been obvious by Petrov because “The static characteristics of semiconductor devices are usually measured at the manufacturing stage and at the stage of monitoring the electronic components in order to reject unsuitable devices. Measurements of the dc characteristics of the devices in conjunction with methods for the statistical processing of the results obtained enable not only defective articles to be detected but also enable the reliability of the components during use to be predicted. From the results of dc measurements of the characteristics one can determine a number of important parameters of the physical models of semiconductor devices. The reliability of an estimate of the quality of electronic systems at the design stage using PSPICE computer-aided design is due mainly to the accuracy with which the parameters of the models of the active components of the system are specified”. (Petrov disclosed in page 1239 (1st and 2nd para)).
Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Rupp, Carrillo and Enda and further in view of Petrov.
Regarding Claim 16, Enda, Rupp and Carrillo teach the device of claim 11, is incorporating the rejections of claim 7 respectively, because claim 16 has substantially similar claim language as claims 7, therefore claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Enda, Rupp and Carrillo and further in view of Petrov as discussed above for substantially similar rationale.
Conclusion
10. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. An NPL paper “Boltzmann transport equation-based thermal modeling approaches for hotspots in microelectronics” by Sreekant V. J. Narumanchi et al. presented an overview of the modeling techniques, based on the solution to the Boltzmann transport equation. The transient thermal problem associated with the electrostatic discharge phenomena in a transistor is also considered. Two-dimensional simulations of concurrent electrical and thermal transport in semiconductor devices (GaAs MESFETs and Si MOSFETs) have been reported. In these studies, the approach is to consider hydrodynamic equations for electron transport, and energy conservation equations for electrons and the different phonon modes (polarization branches). These equations are derived by taking moments of the Boltzmann equations and are therefore lower order approximations. Again, single relaxation times are used to describe the energy interaction between the different branches. Particular attention has been given to the phonon dispersion model developed by the authors and the hotspot problem of self-heating in a SOI transistor, as well as the transient electrostatic discharge in an NMOS transistor. Results obtained from the phonon dispersion model are compared to those obtained from simpler BTE-based models as well as Fourier diffusion.
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/NUPUR DEBNATH/Examiner, Art Unit 2186
/RENEE D CHAVEZ/Supervisory Patent Examiner, Art Unit 2186
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