Notice of Pre-AIA or AIA Status
Claims 1-9 and 18-24 are currently presented for Examination.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Election/Restrictions
Applicant’s election without traverse of Group I (claims 1-8 and 18-24) in the reply filed on 08/24/2026 is acknowledged.
Examiner’s Note: Examiner has cited particular columns and line numbers in the references applied to the claims above for the convenience of the applicant. Although the specified citations are representative of the teachings of the art and are applied to specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant in preparing responses, to 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.
In the case of amending the claimed invention, Applicant is respectfully requested to indicate the portion(s) of the specification which dictate(s) the structure relied on for proper interpretation and also to verify and ascertain the metes and bounds of the claimed invention.
Claim Objections
Claim 18 and 21 is objected to because of the following informalities: The claims have numerous issues with antecedent basis. The Examiner suggests amending the claims such that the first recitation of each distinct element uses articles such as “a”/”an”, later recitations referring back to the same distinct element uses articles such as “the”/”said”, to use disambiguating modifiers (e.g., first, second, etc.) when there are multiple distinct elements with the same base term, and that the use of modifiers for each distinct element is kept consistent.
Claim 18 and 21 recites “gradient of the parameters” in its limitation. There is insufficient antecedent basis for this limitation in the claim. No parameters were introduced before. “The parameters” have no clear express antecedent, and their mathematical role is uncertain.
Claim 21 recites “the desired performance” in its limitation. There is insufficient antecedent basis for this limitation in the claim.
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 1-9 and 18-24 are rejected under 35 U.S.C. 101 because the claimed invention are directed to an abstract idea without significantly more.
(Step 1) Is the claims to a process, machine, manufacture, or composition of matter?
Claims: 1-9 are directed to method or process that falls on one of statutory category.
Claims: 18-24 are directed to system or machine that falls on one of statutory category.
Step 1 Prong one
(b) processing the device geometry data based on a boundary element method (BEM) to generate a surface solution of the device behavior and further to generate a first intermediate data; (The Boundary Element Method (BEM) is a numerical method used to solve linear partial differential equations (PDEs) by transforming them into boundary integral equations. Processing data via BEM is fundamentally an execution of mathematical calculations. This falls under the "mathematical concepts" grouping of abstract ideas. As MPEP 2106.04(a)(2)(I) defines this to include mathematical relationships, formulas, and calculations.)
c)applying additional underlying physics rule based on the generated surface solution of the device behavior and generating a second intermediate data;(Taking a mathematical result (the surface solution), applying another mathematical equation (the physics rule), and calculating a new number (the second intermediate data) is viewed as a chain of mathematical calculations. This falls under the "mathematical concepts" grouping of abstract ideas. As MPEP 2106.04(a)(2)(I) defines this to include mathematical relationships, formulas, and calculations.)
d) evaluating performance of the device based on (c), wherein the evaluating generates a third intermediate data; A person can sit down with a pencil, look at data point (c), mentally compare it to a benchmark or run it through an evaluation checklist, and write down a new data point, the step is a mental process. As MPEP 2106.04(a)(2)(III) the “mental processes” abstract idea grouping is defined as concepts performed in the human mind, and examples of mental processes include observations, evaluations, judgments, and opinions.)
e) generating a gradient between the evaluated performance of the device and a desired performance; (A gradient is a calculus concept representing a derivative or a rate of change (often a vector of partial derivatives in multi-dimensional space). Calculating a gradient between two data points—such as "evaluated performance" and "desired performance" requires a mathematical equation or algorithmic optimization function. This falls under the "mathematical concepts" grouping of abstract ideas. As MPEP 2106.04(a)(2)(I) defines this to include mathematical relationships, formulas, and calculations.)
g) applying the additional underlying physics rule to the generated gradient and further to the second intermediate data to generate a gradient of the parameters of the physics rules; (Applying a physics rule to an intermediate data gradient to compute a new gradient of the parameters is a chain of mathematical calculations (such as applying the chain rule in calculus). Because this process manipulates mathematical relationships to output a new numerical value, it is directed to a mathematical concept. This falls under the "mathematical concepts" grouping of abstract ideas. As MPEP 2106.04(a)(2)(I) defines this to include mathematical relationships, formulas, and calculations)
h) processing the gradient of the parameters of the physics rules and the first intermediate data based on the surface solution of device behavior to generate a gradient with respect to the surface solution; (Calculating a gradient (a vector of partial derivatives) is a purely mathematical operation rooted in calculus. Taking "parameters of physics rules," "intermediate data," and "surface solutions" and combining them to output a new gradient is viewed as manipulating mathematical variables through an algorithm. This falls under the "mathematical concepts" grouping of abstract ideas. As MPEP 2106.04(a)(2)(I) defines this to include mathematical relationships, formulas, and calculations)
i) updating the device geometry data based on the gradient of the generated surface solution. (A person sitting at a desk can manually take a set of boundary element method (BEM) calculations, compute the partial derivatives (the gradient) using standard calculus rules, and update a list of physical coordinates on a sheet of paper. Thus, it is the mental process of abstract ideas.)
Step 2A, Prong 2: Does the claim recite additional elements that integrate the judicial exception
into a practical application?
In accordance with Step 2A, Prong 2, the judicial exception is not integrated into a practical application. In particular, claim do not recite the additional elements that integrate the judicial exception into a practical application. The additional element of a) receiving a device geometry data associated with a device is merely receiving data and fall under insignificant extra solution activity as discussed on MPEP 2106.05(g). The additional element of f) storing the first, the second, and the third intermediate data in a memory component also under fall under insignificant extra solution activity as discussed on MPEP 2106.05(g) of storing data. The additional element of a computer implemented method in claim 1 and a system comprising: a processor configured to process data; and a memory component configured to store one or more data; wherein the processor comprises: a boundary element method (BEM) module, a physics rules module and evaluation module in claim 18 are merely including instructions to implement an abstract idea on a computer or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f). The claims are directed to an abstract idea.
Step 2B: Does the claim recite additional elements that amount to significantly more than the
judicial exception?
In view of Step 2B, the claim as a whole does not amount to significantly more than the recited exception, i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. In particular, claim do not recite the additional elements that integrate the judicial exception into a practical application. The additional element of a) receiving a device geometry data associated with a device is merely receiving data and fall under insignificant extra solution activity as discussed on MPEP 2106.05(g) and is well-understood, routine or conventional. ((See MPEP 2106.05 (d)(II)(i))) Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v.Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014). The additional element of f) storing the first, the second, and the third intermediate data in a memory component also under fall under insignificant extra solution activity as discussed on MPEP 2106.05(g) of storing data and is well-understood, routine or conventional. ((See MPEP 2106.05 (d)(II) (iv)) Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93; The additional element of a computer implemented method in claim 1 and a system comprising: a processor configured to process data; and a memory component configured to store one or more data; wherein the processor comprises: a boundary element method (BEM) module, a physics rules module and evaluation module in claim 18 are merely including instructions to implement an abstract idea on a computer or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f). The claims are directed to an abstract idea. Thus, claim 1 and 18 are not patent eligible.
Claim 2 further recite repeating steps (a)-(i) for a number of iterations. It is combination of mathematical concepts and a mental process that can be performed using a pen and paper as explained in rejection 1above. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 3 and 19 further recite applying a mesh smoothing operation subsequent to performing (i) and after a predetermined number of iterations. Mesh smoothing (such as Laplacian smoothing see Published spec [0042]) relies entirely on algorithms, geometric calculations, and numerical formulas to recalculate vertex positions. This falls under the "mathematical concepts" grouping of abstract ideas. As MPEP 2106.04(a)(2)(I) defines this to include mathematical relationships, formulas, and calculations. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 4 and 20 further recite wherein the additional underlying physics rule is a Verlet integration for charged particles. Verlet integration is a numerical method used to integrate Newton's equations of motion. It is a set of algebraic equations used to calculate the next position of a particle based on its current position, previous position, and acceleration. This falls under the "mathematical concepts" grouping of abstract ideas. As MPEP 2106.04(a)(2)(I) defines this to include mathematical relationships, formulas, and calculations. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 5 further recite wherein the additional underlying physics rule is received from a user. A human can easily receive information (e.g., a user writing down a physics rule) using pen and paper. It is merely receiving data and fall under insignificant extra solution activity as discussed on MPEP 2106.05(g) and is well-understood, routine or conventional. ((See MPEP 2106.05 (d)(II)(i))) Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v.Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014). Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 6 and 21 further recite wherein at least one of the desired performance or the device geometry data is received from a user. A human can easily receive information on device performance using pen and paper. It is merely receiving data and fall under insignificant extra solution activity as discussed on MPEP 2106.05(g) and is well-understood, routine or conventional. ((See MPEP 2106.05 (d)(II)(i))) Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v.Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014). Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 7 and 24 further recite wherein the BEM processes a partial differential equation of a Laplace type or a Maxwell equation or Helmholtz equation. This falls under the "mathematical concepts" grouping of abstract ideas. Merely taking a known mathematical method (BEM) and applying it to standard physical equations (Maxwell, Laplace, Helmholtz) is viewed as claiming the mathematical concept itself. This falls under the "mathematical concepts" grouping of abstract ideas. As MPEP 2106.04(a)(2)(I) defines this to include mathematical relationships, formulas, and calculations. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 8 and 22 further recite wherein the device geometry data describes a shape associated with the device. It is merely receiving data and fall under insignificant extra solution activity as discussed on MPEP 2106.05(g) and is well-understood, routine or conventional. ((See MPEP 2106.05 (d)(II)(i))) Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v.Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014). Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 9 and 23 further recite wherein the device geometry data is in a triangular mesh format. A person can be given a list of 3D coordinates (vertices) and a list of which points connect to form triangles (faces). Using a pen and paper, the person can plot those points on a 2D graph representing 3D space and draw lines to connect them into a mesh. It is also merely receiving data and fall under insignificant extra solution activity as discussed on MPEP 2106.05(g) and is well-understood, routine or conventional. ((See MPEP 2106.05 (d)(II)(i))) Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v.Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014). Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
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 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.
Claim(s) 1-4, 7-9, 18-20 and 22-24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Neustock, Lars Thorben, et al. ("Inverse design tool for ion optical devices using the adjoint variable method." Scientific Reports 9.1 (2019): 11031) in view of Bandara, Kosala, et al. "Boundary element based multiresolution shape optimisation in electrostatics." Journal of computational physics 297 (2015): 584-598.
Regarding claim 1
Neustock teaches a computer implemented method comprising: (see abstract- We present a computer-aided design tool for ion optical devices using the adjoint variable method.)
a) receiving a device geometry data associated with a device; (see page 1- The geometry of a device is represented numerically first. see page 5- The AVM we have shown here allows choosing any arbitrary initial geometry, initial incoming particle distribution as well as objective function. Any of these can be changed in the setup and a optimization program can be run. Thus, many other ion optical devices with more intricate geometries or particle beams than an Einzel lens can be optimized using AVM. see page 2-We simultaneously optimized shapes, positions and voltages of several N-element Einzel lens systems with freeform shapes. The shapes of the electrodes are polygons of N points)
b) processing the device geometry data based on a ;(see page 9 and fig 10-11- The finite element method (FEM) approximates the exact solution of a PDE (partial differential equation), e.g. the Laplace equation (2), on a mesh. We choose an unstructured triangular mesh created by the software gmsh, for simplicity. Inside each triangle, the field is approximated by a polynomial and represented by its value at a fixed number of points called nodes distributed on the corners, edges and interiors of the triangles. We chose Lagrange polynomials as our basis. With these restrictions, the problem can be posed as a linear system: Mφ = f (10) wherein the system matrix M consists of the discretizations of the Laplace equation and f describes the boundary values of the problem. The boundaries can satisfy either a Neumann or a Dirichlet condition. The solution of this linear system φ, is the vector of the electrostatic potentials at every node. The values of φ in combination with the Lagrange basis functions are used to interpolate the values of the electrostatic field onto a 2D cartesian grid of field values as required for the particle tracer.)
c)applying additional underlying physics rule based on the generated surface solution of the device behavior and generating a second intermediate data; (see page 10 and fig 11- The particle equations of motion are solved with SVM. The acceleration vector a is interpolated from the grid of electrostatic field values. Here, the vector s contains positions and velocities of the trajectory at all simulated time steps)
d) evaluating performance of the device based on (c), wherein the evaluating generates a third intermediate data; (see page 10 and fig 11- After calculating the trajectories, the forward simulation is complete and the device performance can be evaluated. See page 7 and fig 11- The size of this spot determines the quality of the lens. A smaller spot has a smaller objective function Q(s).)
e) generating a gradient between the evaluated performance of the device and a desired performance;(see page 7- where s* describes the desired focal point at a focal plane defined by the position s1 = sf . For a beam of several particles, we calculate the RMS of s − s* over all particles. The partial derivatives of Q under changes in the element geometry and voltage are the design sensitivities of the Einzel lens illustrated in Fig. 10. See page 10 and fig 11- The inhomogeneous term in (14) can be obtained by differentiating equation (4).)
f) storing the first, the second, and the third intermediate data in a memory component;(see page 8-9- We implemented fully discrete adjoint systems for both components to ensure accurate gradients to machine precision. To reduce memory requirements and allow our system to run on a simple laptop computer, we calculated equation (9) in a step-wise approach for each FEM element and only using relevant sub-matricies. see page 10- The values of the electric field are stored in a vector E calculated by the electrostatics solver. With the forward solution of the non-linear SVM, we can determine a interpolation matrix I used to represent the interpolation of the electric field required to obtain the acceleration vector a.)
Examiner note: Neustock stores electric field data and uses forward results in adjoint calculations. Retaining the other required forward intermediates in ordinary memory would permit reuse without re-computation.
g) applying the additional underlying physics rule to the generated gradient and further to the second intermediate data to generate a gradient of the parameters of the physics rules; (see fig 11 and page 10- To find dQ/dE, we pose an adjoint SVM system. With the forward solution of the non-linear SVM, we can determine a interpolation matrix I used to represent the interpolation of the electric field required to obtain the acceleration vector a. Through differentiation of the equations (12) and (13) with respect to the electric field values on a grid, we can pose an adjoint system in the form of (8) We can then calculate the adjoint system and reach the design sensitivities with equation 16)
h) processing the gradient of the parameters of the physics rules and the first intermediate data based on the surface solution of device behavior to generate a gradient with respect to the surface solution; (see page 8 and fig 11- Using an adjoint electrostatics solver, we can backpropagate again and calculate how the error depends on different parts of the system, e.g. the shape or applied voltage. Since we can analytically determine the influence of the system parameters to the system, we can calculate the design sensitivities dQ/dp using computationally cheap vector-matrix-vector products [Eqs (9) & (16)].)
and i) updating the device geometry data based on the gradient of the generated surface solution. (see page 2-3-During optimization the electrode centers xc, yc, the boundary displacements ri and Δθi and the applied voltages are designable. The step size for the gradient descent is recalculated at each iteration using the Barzilai-Borwein method. As visible from Fig. 4, only about ten iterations of the gradient-descent method are required for a converged result. At each iteration, a sensitivity analysis using AVM is performed. The optimizations converged with a similar number of iterations independently of the number of elements of the initial geometry)
Neustock does not teach processing the device geometry data based on a boundary element method (BEM) to generate a surface solution of the device behavior and further to generate a first intermediate data.
In the related field of invention, Bandara teaches b) processing the device geometry data based on a boundary element method (BEM) to generate a surface solution of the device behavior and further to generate a first intermediate data;(see page 584- First of all, BEM relies only on a surface discretisation so that there is no need to maintain an analysis-suitable volume discretisation during the shape optimisation process. See page 591- Solve the primal boundary element system (12a) and the adjoint boundary element system (12b) using the computational mesh with ℓc =n.)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of computer-aided design tool for electrostatic ion optical devices using the adjoint variable method as disclosed by Neustock to include processing the device geometry data based on a boundary element method (BEM) to generate a surface solution of the device behavior and further to generate a first intermediate data as taught by Bandara in the system of Neustock in order to provide shape optimisation of high-voltage devices subject to electrostatic field equations by combining fast boundary elements with multiresolution subdivision surfaces. (see abstract, Bandara)
Regarding claim 18
Neustock teaches a system comprising: a processor configured to process data; and a memory component configured to store one or more data: (see abstract-We present a computer-aided design tool for ion optical devices using the adjoint variable method. Numerical methods have been essential for the development of ion optical devices such as electron microscopes and mass spectrometers. see page 8-9- We implemented fully discrete adjoint systems for both components to ensure accurate gradients to machine precision. To reduce memory requirements and allow our system to run on a simple laptop computer. see page 10- The values of the electric field are stored in a vector E calculated by the electrostatics solver.)
wherein the processor comprises: ; (see page 1- The geometry of a device is represented numerically first. see page 5- The AVM we have shown here allows choosing any arbitrary initial geometry, initial incoming particle distribution as well as objective function. Any of these can be changed in the setup and a optimization program can be run. Thus, many other ion optical devices with more intricate geometries or particle beams than an Einzel lens can be optimized using AVM. see page 2-We simultaneously optimized shapes, positions and voltages of several N-element Einzel lens systems with freeform shapes. The shapes of the electrodes are polygons of N points)
process the device geometry data based on a ;(see page 9 and fig 10-11- The finite element method (FEM) approximates the exact solution of a PDE (partial differential equation), e.g. the Laplace equation (2), on a mesh. We choose an unstructured triangular mesh created by the software gmsh, for simplicity. Inside each triangle, the field is approximated by a polynomial and represented by its value at a fixed number of points called nodes distributed on the corners, edges and interiors of the triangles. We chose Lagrange polynomials as our basis. With these restrictions, the problem can be posed as a linear system: Mφ = f (10) wherein the system matrix M consists of the discretizations of the Laplace equation and f describes the boundary values of the problem. The boundaries can satisfy either a Neumann or a Dirichlet condition. The solution of this linear system φ, is the vector of the electrostatic potentials at every node. The values of φ in combination with the Lagrange basis functions are used to interpolate the values of the electrostatic field onto a 2D cartesian grid of field values as required for the particle tracer.)
a physics rules module configured to apply additional underlying physics rule based on the generated surface solution of the device, wherein the physics module is further configured to generate a second intermediate data; and (see page 10 and fig 11- The particle equations of motion are solved with SVM. The acceleration vector a is interpolated from the grid of electrostatic field values. Here, the vector s contains positions and velocities of the trajectory at all simulated time steps)
evaluation module configured to evaluate performance of the device based on an output from the physics rule module, wherein the evaluation module is further configured to generate a third intermediate data; (see page 10 and fig 11- After calculating the trajectories, the forward simulation is complete and the device performance can be evaluated. See page 7 and fig 11- The size of this spot determines the quality of the lens. A smaller spot has a smaller objective function Q(s).)
wherein the first, the second, and the third intermediate data are stored in the memory component;(see page 8-9- We implemented fully discrete adjoint systems for both components to ensure accurate gradients to machine precision. To reduce memory requirements and allow our system to run on a simple laptop computer, we calculated equation (9) in a step-wise approach for each FEM element and only using relevant sub-matricies. see page 10- The values of the electric field are stored in a vector E calculated by the electrostatics solver. With the forward solution of the non-linear SVM, we can determine a interpolation matrix I used to represent the interpolation of the electric field required to obtain the acceleration vector a.)
Examiner note: Neustock stores electric field data and uses forward results in adjoint calculations. Retaining the other required forward intermediates in ordinary memory would permit reuse without re-computation.
wherein result generated by the evaluation module is input to the physics rules module, and wherein the physics rules module further receives the second intermediate data from the memory component and generates a gradient of the parameters based on the additional underlying physics rules; (see fig 11 and page 10- To find dQ/dE, we pose an adjoint SVM system. With the forward solution of the non-linear SVM, we can determine a interpolation matrix I used to represent the interpolation of the electric field required to obtain the acceleration vector a. Through differentiation of the equations (12) and (13) with respect to the electric field values on a grid, we can pose an adjoint system in the form of (8) We can then calculate the adjoint system and reach the design sensitivities with equation 16)
Neustock does not teach a boundary element method (BEM) module configured to receive a device geometry data associated with a device and process the device geometry data to generate a surface solution of device behavior, wherein the BEM module is further configured to generate a first intermediate data and wherein the gradient of the parameters generated by the physics rules module is input to the BEM module, and wherein the BEM module is further configured to receive the first intermediate data from the memory component, wherein the BEM is configured to generate an updated device geometry data based on the gradient of the parameters and further based on the first intermediate data.
wherein the gradient of the parameters generated by the physics rules module is input to the from the memory component, (see page 8 and fig 11- Using an adjoint electrostatics solver, we can backpropagate again and calculate how the error depends on different parts of the system, e.g. the shape or applied voltage. Since we can analytically determine the influence of the system parameters to the system, we can calculate the design sensitivities dQ/dp using computationally cheap vector-matrix-vector products [Eqs (9) & (16)].)
In the related field of invention, Bandara teaches a boundary element method (BEM) module configured to receive a device geometry data associated with a device and process the device geometry data to generate a surface solution of device behavior, wherein the BEM module is further configured to generate a first intermediate data;(see page 584- First of all, BEM relies only on a surface discretisation so that there is no need to maintain an analysis-suitable volume discretisation during the shape optimisation process. See page 591 and fig 8- Solve the primal boundary element system (12a) and the adjoint boundary element system (12b) using the computational mesh with ℓc =n.)
wherein the gradient of the parameters generated by the physics rules module is input to the BEM module, and wherein the BEM module is further configured to receive the first intermediate data from the memory component, wherein the BEM is configured to generate an updated device geometry data based on the gradient of the parameters and further based on the first intermediate data; (see abstract- The primal and adjoint problems are discretised with the boundary element method using a sufficiently fine control mesh. See page 591 and fig 8- Solve the primal boundary element system (12a) and the adjoint boundary element system (12b) using the computational mesh with ℓc =n. . Evaluate the cost functional J(Ωℓc, uℓc), i.e., the discrete counterpart to (3), and the shape derivative kernel gℓc
i at each vertex xi according to (13). See page 592 and fig 8- Perturb the vertex coordinates of the optimisation mesh according to equation (5))
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of computer-aided design tool for electrostatic ion optical devices using the adjoint variable method as disclosed by Neustock to include a boundary element method (BEM) module configured to receive a device geometry data associated with a device and process the device geometry data to generate a surface solution of device behavior, wherein the BEM module is further configured to generate a first intermediate data and wherein the gradient of the parameters generated by the physics rules module is input to the BEM module, and wherein the BEM module is further configured to receive the first intermediate data from the memory component, wherein the BEM is configured to generate an updated device geometry data based on the gradient of the parameters and further based on the first intermediate data as taught by Bandara in the system of Neustock in order to provide shape optimisation of high-voltage devices subject to electrostatic field equations by combining fast boundary elements with multiresolution subdivision surfaces. (see abstract, Bandara)
Regarding claim 2
The combination of Neustock and Bandara teaches the computer-implemented method of claim 1. The combination of Neustock and Bandara further teaches repeating steps (a)-(i) for a number of iterations. (See page 3-At each iteration, a sensitivity analysis using AVM is performed. The optimizations converged with a similar number of iterations independently of the number of elements of the initial geometry.)
Examiner note: Bandara teaches step (b) is supplied to Neustock. See rejection of claim 1.
Regarding claim 3
The combination of Neustock and Bandara teaches the computer-implemented method of claim 2. Neustock does not teach applying a mesh smoothing operation subsequent to performing (i) and after a predetermined number of iterations
Bandara further teaches applying a mesh smoothing operation subsequent to performing (i) and after a predetermined number of iterations. (See Bandara section 4 and fig 2- Next, we introduce the multiresolution subdivision surfaces for describing the geometry of the computational domain. Subdivision is a powerful geometric modeling technique for generating smooth surfaces on arbitrary connectivity meshes. The smooth surface is recursively generated through repeated refinement of an initial coarse control mesh.)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of computer-aided design tool for electrostatic ion optical devices using the adjoint variable method as disclosed by Neustock to include applying a mesh smoothing operation subsequent to performing (i) and after a predetermined number of iterations as taught by Bandara in the system of Neustock in order to provide shape optimisation of high-voltage devices subject to electrostatic field equations by combining fast boundary elements with multiresolution subdivision surfaces. (see abstract, Bandara)
Regarding claim 4
The combination of Neustock and Bandara teaches the computer-implemented method of claim 1. \ Neustock further teaches wherein the additional underlying physics rule is a Verlet integration for charged particles. (see page 1 and fig 11-Here, we show how to employ the adjoint variable method on the finite-element method and Störmer-Verlet method for electrostatic charged particle devices. Next, the equation of motion for the charged particles is solved, most commonly with a Runge-Kutta method or a Störmer-Verlet method (SVM). We can then calculate the design sensitivities by solving another set of systems posed using AVM.)
Regarding claim 7
The combination of Neustock and Bandara teaches the computer-implemented method of claim 1. Neustock does not teach wherein the BEM processes a partial differential equation of a Laplace type or a Maxwell equation or Helmholtz equation
However, Bandara further teaches wherein the BEM processes a partial differential equation of a Laplace type or a Maxwell equation or Helmholtz equation. (see section 6- In all examples, the Dirichlet boundary value problem for the Laplace equation (1) is considered. See equation 1)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of computer-aided design tool for electrostatic ion optical devices using the adjoint variable method as disclosed by Neustock to include wherein the BEM processes a partial differential equation of a Laplace type or a Maxwell equation or Helmholtz equation as taught by Bandara in the system of Neustock in order to provide shape optimisation of high-voltage devices subject to electrostatic field equations by combining fast boundary elements with multiresolution subdivision surfaces. (see abstract, Bandara)
Regarding claim 8
The combination of Neustock and Bandara teaches the computer-implemented method of claim 1. Neustock further teaches wherein the device geometry data describes a shape associated with the device. (see page 2-We simultaneously optimized shapes, positions and voltages of several N-element Einzel lens systems with freeform shapes. The shapes of the electrodes are polygons of N points)
Regarding claim 9
The combination of Neustock and Bandara teaches the computer-implemented method of claim 1. Neustock further teaches wherein the device geometry data is in a triangular mesh format. (see page 9 and fig 12-We choose an unstructured triangular mesh, created by the software gmsh, for simplicity. Inside each triangle, the field is approximated by a polynomial and represented by its value at a fixed number of points called nodes distributed on the corners, edges and interiors of the triangles.)
Regarding claim 19
Claim 19 is rejected for the same reasons as Claim 3, as they share the same elements.
Regarding claim 20
Claim 20 is rejected for the same reasons as Claim 4, as they share the same elements.
Regarding claim 22
Claim 22 is rejected for the same reasons as Claim 8, as they share the same elements.
Regarding claim 23
Claim 23 is rejected for the same reasons as Claim 9, as they share the same elements.
Regarding claim 24
Claim 24 is rejected for the same reasons as Claim 7, as they share the same elements.
Claim(s) 5-6 and 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Neustock, Lars Thorben, et al. ("Inverse design tool for ion optical devices using the adjoint variable method." Scientific Reports 9.1 (2019): 11031) in view of Bandara, Kosala, et al. "Boundary element based multiresolution shape optimisation in electrostatics." Journal of computational physics 297 (2015): 584-598. and further in view of Jensen et al. (PAT NO: US 11893318 B1)
Regarding claim 5
The combination of Neustock and Bandara teaches the computer-implemented method of claim 1. The combination of Neustock and Bandara does not teach wherein the additional underlying physics rule is received from a user
In the related field of invention, Jensen teaches wherein the additional underlying physics rule is received from a user. (see col 8 line 8-10- For example, in certain implementations, a user can combine one or more physical phenomena into a multiphysics model, as part of, for example, an engineering analysis. see col 20 line 27-31-Referring now to FIGS. 5, 6A, and 6B, exemplary GUIs are depicted where one or more physics features may be selected and a physics model constructed. The constructed physics model may include physics, constraints, and conditions, such as one or more boundary condition
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of computer-aided design tool for electrostatic ion optical devices using the adjoint variable method as disclosed by Neustock to include wherein the additional underlying physics rule is received from a user as taught by Bandara in the system of Neustock and Bandara in order to for topology and shape optimization of a geometrical representation of a physical object being modeled. (see abstract, Jensen)
Regarding claim 6
The combination of Neustock and Bandara teaches the computer-implemented method of claim 1. The combination of Neustock and Bandara does not teach wherein at least one of the desired performance or the device geometry data is received from a user.
In the related field of invention, Jensen teaches wherein at least one of the desired performance or the device geometry data is received from a user. (see col 15 line 55-56-The optimization objective expression is defined by a user to either be maximized or minimized. See col 11 line 9-13-In one illustrative aspect, user input may be received via the GUI 53 of the client processing system 50 based on a user selecting an option via the GUI 53 to create an exemplary geometry, such as a cylinder geometry. See col 11 line 33-36-a logics component 64 can receive user input in the form of input data and input commands for generating a cylinder and send these data and commands to a geometry component that is part of component 65.)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of computer-aided design tool for electrostatic ion optical devices using the adjoint variable method as disclosed by Neustock to include wherein at least one of the desired performance or the device geometry data is received from a user as taught by Bandara in the system of Neustock and Bandara in order to for topology and shape optimization of a geometrical representation of a physical object being modeled. (see abstract, Jensen)
Regarding claim 21
Claim 21 is rejected for the same reasons as Claim 6, as they share the same elements.
Conclusion
9. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Schubert et al. US11900026B1
Discussing the design tools for optical and electromagnetic devices. The method includes receiving training data including pre-fabrication structures and post-fabrication, training a fabrication constraint model by optimizing parameters of the fabrication constraint model based on the training data to model the fabrication constraints of the fabrication process, receiving an input design corresponding to a physical device, and generating a fabricability metric of the input design via the fabrication constraint model.
10. All claims 1-9 and 18-24 are rejected.
11. Any inquiry concerning this communication or earlier communications from the examiner should be directed to PURSOTTAM GIRI whose telephone number is (469)295-9101. The examiner can normally be reached 7:30-5:30 PM, Monday to Friday.
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/PURSOTTAM GIRI/
Examiner, Art Unit 2186
Prosecution Insights