DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of the Claims
Claims 1-15 are currently pending and under exam herein.
Claims 1-15 are rejected.
Priority
The instant application claims priority from provisional application 63/453,788 filed on 3/22/2023. Thus, the effective filing date of the instant application is 3/22/2023.
Drawings
The Drawings filed on 05/26/2023 were considered.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 08/28/2023 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement has been considered by the examiner.
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 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite: (a) mathematical concepts, (e.g., mathematical relationships, formulas or equations, mathematical calculations); and (b) mental processes, i.e., concepts performed in the human mind, (e.g., observation, evaluation, judgement, opinion).
Subject matter eligibility evaluation in accordance with MPEP 2106:
Eligibility Step 1: Claims 1-15 are directed to a method to improve particle simulation.
[Step 1: YES]
Eligibility Step 2A: First it is determined in Prong One whether a claim recites a judicial exception, and if
so, then it is determined in Prong Two whether the recited judicial exception is integrated into a
practical application of that exception.
Eligibility Step 2A Prong One: In determining whether a claim is directed to a judicial exception,
examination is performed that analyzes whether the claim recites a judicial exception, i.e., whether a
law of nature, natural phenomenon, or abstract idea is set forth or described in the claim.
Independent claim 1 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
inputting an initial condition into an evolution model to predict a first condition at a next time step; (mathematical concept, inputting numbers into a mathematical formula under BRI)
inputting the initial condition into a molecular dynamics model to predict a second condition at the next time step (mathematical concept, inputting numbers into a mathematical formula under BRI)
and determining whether to use the first condition or the second condition as a prediction in the molecular dynamics simulation based on an estimated uncertainty associated with the evolution model. (mathematical concept, mental process)
Dependent claim 2 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein the initial condition includes coordinate and velocity information of a particle and corresponding surrounding particles at an initial time step, and the first and second condition each include a prediction of a position and a velocity of the particle at a next time step (mathematical concept – this just limits what the math is done on)
Dependent claim 3 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein the estimated uncertainty associated with the evolution model is based on a global uncertainty (mathematical concept – this just limits what the math is done on)
Dependent claim 4 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein the global uncertainty is associated with a global model, and wherein the global model accepts particle information and computes the global uncertainty based on a change in a global geometry of the particle (mathematical concept)
Dependent claim 5 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein the global uncertainty and the uncertainty associated with the evolution model are input to an uncertainty model, and wherein the uncertainty model performs an evaluation of the global uncertainty and the uncertainty associated with the evolution model by comparing to an uncertainty threshold. (mathematical concept)
Dependent claim 6 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein the determination of whether to use the first condition or the second condition is based on the evaluation by the uncertainty model, (mathematical concept)
and wherein the first condition is used as the prediction in the molecular dynamics simulation based on a combination of the global uncertainty and the uncertainty associated with the evolution model being lower than the uncertainty threshold (mathematical concept)
Dependent claim 7 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein the uncertainty model produces a Boolean value as a result of the evaluation (mathematical concept)
Dependent claim 8 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein the global model is a trained neural network (mathematical concept)
wherein the global model is trained to estimate an uncertainty of global-geometrical changes (mathematical concept)
Dependent claim 9 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein a global uncertainty estimation rule is calculated for the global model (mathematical concept)
wherein the global uncertainty estimation rule is based on a distance calculated between the particle and a target particle in the global model or a local potential energy of the particle (mathematical concept)
Dependent claim 10 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein determining whether to use the first condition or the second prediction as the prediction in the molecular dynamics simulation is based on the distance between the particle and the target particle or the local potential energy of the particle being either greater than or less than a target threshold (mathematical concept)
Dependent claim 11 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein the target threshold is calculated as a numerical multiple of a size of the target particle (mathematical concept)
Dependent claim 12 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
wherein the molecular dynamics simulation is a Monte Carlo simulation (mathematical concept)
Independent claim 14 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
inputting an initial condition into an evolution model to predict a first condition at a next time step;
inputting the initial condition into a molecular dynamics model to predict a second condition at the next time step;
and determining whether to use the first condition or the second condition as a prediction in the molecular dynamics simulation based on an estimated uncertainty associated with the evolution model.
Independent claim 15 recites the following steps which fall within the mental processes and/or mathematical concepts groupings of abstract ideas:
inputting an initial condition into an evolution model to predict a first condition at a next time step; (mathematical concept)
inputting the initial condition into a molecular dynamics model to predict a second condition at the next time step; and (mathematical concept)
determining whether to use the first condition or the second condition as a prediction in the molecular dynamics simulation based on an estimated uncertainty associated with the evolution model (mathematical concept, mental process)
The abstract ideas recited in the claims are evaluated under the broadest reasonable interpretation (BRI) of the claim limitations when read in light of and consistent with the specification. As noted in the foregoing section, the claims are determined to contain limitations that can practically be performed in the human mind with the aid of a pencil and paper, and therefore recite judicial exceptions from the mental process grouping of abstract ideas. Additionally, the recited limitations that are identified as judicial exceptions from the mathematical concepts grouping of abstract ideas are abstract ideas irrespective of whether or not the limitations are practical to perform in the human mind.
Therefore, claims 1-15 recite an abstract idea as the dependent claims will inherit the abstract ideas from the independent claims.
[Step 2A Prong One: YES]
Eligibility Step 2A Prong Two: In determining whether a claim is directed to a judicial exception, further
examination is performed that analyzes if the claim recites additional elements that when examined as a
whole integrates the judicial exception(s) into a practical application (MPEP 2106.04(d)). A claim that
integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception
in a manner that imposes a meaningful limit on the judicial exception. The claimed additional elements
are analyzed to determine if the abstract idea is integrated into a practical application (MPEP
2106.04(d)(I); MPEP 2106.05(a-h)). If the claim contains no additional elements beyond the abstract
idea, the claim fails to integrate the abstract idea into a practical application (MPEP 2106.04(d)(III)).
The judicial exceptions identified in Eligibility Step 2A Prong One are not integrated into a practical application because of the reasons noted below.
The additional element in independent claim 1 includes:
A computer-implemented method for performing a molecular dynamics simulation, the method comprising:
The additional element in dependent claim 13 includes:
wherein the evolution model is a trained neural network, and
wherein the evolution model is trained using experimental and/or simulation data including the prediction used in the molecular dynamics simulation.
The additional element in independent claim 14 includes:
A computer system programmed for performing a molecular dynamics simulation, the computer system comprising one or more hardware processors which, alone or in combination, are configured to provide for execution of the following steps
The additional element in independent claim 15 includes:
A tangible, non-transitory computer-readable medium for performing a molecular dynamics simulation having instructions thereon, which, upon being executed by one or more processors, provides for execution of the following steps
The additional elements of a computer-implemented method for performing a molecular dynamics simulation, the method comprising (Claim 1), A computer system programmed for performing a molecular dynamics simulation, the computer system comprising one or more hardware processors which, alone or in combination, are configured to provide for execution of the following steps (Claim 14), a tangible, non-transitory computer-readable medium for performing a molecular dynamics simulation having instructions thereon, which, upon being executed by one or more processors, provides for execution of the following steps (Claim 15) wherein the evolution model is a trained neural network, and wherein the evolution model is trained using experimental and/or simulation data including the prediction used in the molecular dynamics simulation (Claim 13) fail to integrate a judicial exception into a practical application merely reciting the words "apply it" (or an equivalent) with the judicial exception, or 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). It also does not improve the function of a generic computer, as discussed in MPEP § 2106.05(a).
Thus, the additionally recited elements merely invoke a computer as a tool, and/or amount to insignificant extra-solution data gathering activity, and as such, when all limitations in claims 1-15 have been considered as a whole, the claims are deemed to not recite any additional elements that would integrate a judicial exception into a practical application, and therefore claims 1-15 are directed to an abstract idea (MPEP 2106.04(d)).
[Step 2A Prong Two: NO]
Eligibility Step 2B: Because the claims recite an abstract idea, and do not integrate that abstract idea into a practical application, the claims are probed for a specific inventive concept. The judicial exception alone cannot provide that inventive concept or practical application (MPEP 2106.05). Identifying whether the additional elements beyond the abstract idea amount to such an inventive concept requires considering the additional elements individually and in combination to determine if they amount to significantly more than the judicial exception (MPEP 2106.05A i-vi).
The claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception(s) because of the reasons noted below.
The additional elements recited in claims 1-15 are identified above, and carried over from Step 2A: Prong Two along with their conclusions for analysis at Step 2B. Any additional element or combination of elements that was considered to be insignificant extra-solution activity at Step 2A: Prong Two was re-evaluated at Step 2B, because if such re-evaluation finds that the element is unconventional or otherwise more than what is well-understood, routine, conventional activity in the field, this finding may indicate that the additional element is no longer considered to be insignificant; and all additional elements and combination of elements were evaluated to determine whether any additional elements or combination of elements are other than what is well-understood, routine, conventional activity in the field, or simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, per MPEP 2106.05(d).
The additional elements of a computer-implemented method for performing a molecular dynamics simulation, the method comprising (Claim 1), A computer system programmed for performing a molecular dynamics simulation, the computer system comprising one or more hardware processors which, alone or in combination, are configured to provide for execution of the following steps (Claim 14), a tangible, non-transitory computer-readable medium for performing a molecular dynamics simulation having instructions thereon, which, upon being executed by one or more processors, provides for execution of the following steps (Claim 15) wherein the evolution model is a trained neural network, and wherein the evolution model is trained using experimental and/or simulation data including the prediction used in the molecular dynamics simulation (Claim 13) are conventional fail to integrate a judicial exception into a practical application merely reciting the words "apply it" (or an equivalent) with the judicial exception, or 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). It also does not improve the function of a generic computer, as discussed in MPEP § 2106.05(a). Evidence for conventionality is shown by Noe et al. (Noé, F.; Tkatchenko, A.; Müller, K.-R.; Clementi, C. Machine Learning for Molecular Simulation. Annual Review of Physical Chemistry 2020, 71 (1), 361–390) which is a review that discusses machine learning with an emphasis on deep neural networks showing it is conventional to use neural networks in molecular dynamics (abstract)
When taken alone, all additional elements in claims 1-15 do not amount to significantly more than the above-identified judicial exception(s). Even when evaluated as a combination, the additional elements fail to transform the exception(s) into a patent-eligible application of that exception. Thus, claims 1-15 are deemed to not contribute an inventive concept, i.e., amount to significantly more than the judicial exception(s) (MPEP 2106.05(II)).
[Step 2B: NO]
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 2, 14, 15 are rejected under 35 U.S.C. 102 as being anticipated by Vandermause et al. (Vandermause, J.; Torrisi, S. B.; Batzner, S.; Xie, Y.; Sun, L.; Kolpak, A. M.; Kozinsky, B. On-the-Fly Active Learning of Interpretable Bayesian Force Fields for Atomistic Rare Events. npj Computational Materials 2020, 6 (1)) The italicized text corresponds to the instant claim limitations.
With respect to the limitations of Claims 1, 13, 14, 15, Vandermause et al. teaches the algorithm takes an arbitrary structure as input and begins with a call to DFT, which is used to train an initial GP model on the forces acting on an arbitrarily chosen subset of atoms in the structure. The GP then proposes an MD step by predicting the forces on all atoms, at which point a decision is made about whether to accept the predictions of the GP or to perform a DFT calculation (pg. 3, col. 1, paragraph 2). The specification of the instant application describes an evolution defines the evolution model as a model accepts the coordinate and velocity information of a particle and surrounding ones, and estimates either (coordinate, velocity) at the next timestep or the force value on those particles which is exactly what Vandermause et al. does. (A computer-implemented method for performing a molecular dynamics simulation, the method comprising: (Claim 1) inputting an initial condition into an evolution model to predict a first condition at a next time step; (Claim 1), inputting the initial condition into a molecular dynamics model to predict a second condition at the next time step; (Claim 1) and determining whether to use the first condition or the second condition as a prediction in the molecular dynamics simulation based on an estimated uncertainty associated with the evolution model (Claim 1) wherein the evolution model is a trained neural network, and wherein the evolution model is trained using experimental and/or simulation data including the prediction used in the molecular dynamics simulation (Claim 13) A computer system programmed for performing a molecular dynamics simulation, the computer system comprising one or more hardware processors which, alone or in combination, are configured to provide for execution of the following steps: inputting an initial condition into an evolution model to predict a first condition at a next time step; inputting the initial condition into a molecular dynamics model to predict a second condition at the next time step; and determining whether to use the first condition or the second condition as a prediction in the molecular dynamics simulation based on an estimated uncertainty associated with the evolution model. (Claim 14), A tangible, non-transitory computer-readable medium for performing a molecular dynamics simulation having instructions thereon, which, upon being executed by one or more processors, provides for execution of the following steps: inputting an initial condition into an evolution model to predict a first condition at a next time step; inputting the initial condition into a molecular dynamics model to predict a second condition at the next time step; and determining whether to use the first condition or the second condition as a prediction in the molecular dynamics simulation based on an estimated uncertainty associated with the evolution model (Claim 15)
With respect to the limitations of Claims 2, Vandermause et al. teaches simulating the set of atoms within the cutoff distance (pg. 8, col. 2, paragraph 3) and independent NVE molecular dynamics trajectories of duration 10 ps were generated (pg. 7, col. 2, paragraph 2) wherein the initial condition includes coordinate and velocity information of a particle and corresponding surrounding particles at an initial time step, and the first and second condition each include a prediction of a position and a velocity of the particle at a next time step (Claim 2)
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.
Claims 3-10 are rejected under 35 U.S.C. 103 as being unpatentable over Vandermause et al. as applied to claims 1, 2, 13, 14, 15 above in further view of Zhang et al. Z(hang, L.; Wang, H.; E, W. Reinforced Dynamics for Enhanced Sampling in Large Atomic and Molecular Systems. The Journal of Chemical Physics 2018, 148 (12).) The limitations of claims 1, 2, 13, 14, 15 have been taught by Vandermause et al. above.
With respect to the limitations of Claims 5, Vandermause et al. teaches any σiα exceeds a chosen multiple of the current noise uncertainty σn of the model, a call to DFT is made and the training set is augmented (pg. 20, col. 2, paragraph 1) and the decision is also based on uncertainty of each GP component force prediction (and the uncertainty associated with the evolution model are input to an uncertainty model, and wherein the uncertainty model performs an evaluation of the global uncertainty and the uncertainty associated with the evolution model by comparing to an uncertainty threshold (Claim 5))
With respect to the limitations of Claims 6, 10, Vandermause et al. teaches a model makes a decision is made about whether to accept the predictions of the GP or to perform a DFT calculation. Accepting or rejecting is a Boolean value (pg. 20, col. 1) wherein the determination of whether to use the first condition or the second condition is based on the evaluation by the uncertainty model (Claim 6) the uncertainty associated with the evolution model being lower than the uncertainty threshold (Claim 6) wherein determining whether to use the first condition or the second prediction as the prediction in the molecular dynamics simulation (Claim 10)
Vandermause et al. does not explicitly teach wherein the estimated uncertainty associated with the evolution model is based on a global uncertainty (Claim 3), wherein the global uncertainty is associated with a global model, and wherein the global model accepts particle information and computes the global uncertainty based on a change in a global geometry of the particle (Claim 4) wherein the global uncertainty (Claim 5), wherein the first condition is used as the prediction in the molecular dynamics simulation based on a combination of the global uncertainty (Claim 6) wherein the global model is a trained neural network, and wherein the global model is trained to estimate an uncertainty of global-geometrical changes(Claim 8) wherein a global uncertainty estimation rule is calculated for the global model, and wherein the global uncertainty estimation rule is based on a distance calculated between the particle and a target particle in the global model or a local potential energy of the particle (Claim 9) is based on the distance between the particle and the target particle or the local potential energy of the particle being either greater than or less than a target threshold (Claim 10)
With respect to the limitations of Claims 3, 4, 5, 6, 8, 9, 10, Zhang et al. teaches a the use of the standard deviation of the prediction of ensemble models which is based on the difference of structural coordinates (which is equivalent to geometry) in an MD simulation for the purpose of accepting or rejecting the particle information. The model is used is a neural network (pgs. 148 – 149, wherein the estimated uncertainty associated with the evolution model is based on a global uncertainty (Claim 3), wherein the global uncertainty is associated with a global model, and wherein the global model accepts particle information and computes the global uncertainty based on a change in a global geometry of the particle (Claim 4) wherein the global uncertainty (Claim 5), wherein the first condition is used as the prediction in the molecular dynamics simulation based on a combination of the global uncertainty (Claim 6) wherein the global model is a trained neural network, and wherein the global model is trained to estimate an uncertainty of global-geometrical changes(Claim 8) wherein a global uncertainty estimation rule is calculated for the global model, and wherein the global uncertainty estimation rule is based on a distance calculated between the particle and a target particle in the global model or a local potential energy of the particle (Claim 9) is based on the distance between the particle and the target particle or the local potential energy of the particle being either greater than or less than a target threshold (Claim 10)
A person of ordinary skill would be motivated to combine Vandermause et al. with Zhang et al. as both are in the same field of endeavor of using machine learning to improve molecular dynamics. Vandermause et al. has use atom forces while Zhang et al. uses global molecular geometry. It would be obvious to combine these two known works in order to improve an MD simulation. In addition, there is a reasonable expectation of success because adding an additional restraint to a machine learning function does not change how it operates it simply just changes the cost function it is trying to minimize so it is expected to continue to work combined as they did separately as nothing fundamentally changes in the method and math allows for successful combination of each.
Claims 11-12 are rejected under 35 U.S.C. 103 as being unpatentable over Vandermause et al. view of Zhang et al. as applied to claims 1-10, 13-15 above in further view of Nedea et al. (Nedea, S. V.; Frijns, A. J. H.; van Steenhoven, A. A.; Markvoort, A. J.; Hilbers, P. A. J. Hybrid Method Coupling Molecular Dynamics and Monte Carlo Simulations to Study the Properties of Gases in Microchannels and Nanochannels. Physical Review E 2005, 72 (1)) The italicized text corresponds to the instant claim limitations. The limitations of claims 1-10, 13-15 have been taught by Vandermause et al. view of Zhang et al. above
Vandermause et al. in view of Zhang et al. does not explicitly teach wherein the target threshold is calculated as a numerical multiple of a size of the target particle (Claim 11) wherein the molecular dynamics simulation is a Monte Carlo simulation (Claim 12)
However, these limitations were known in the art at the time of the effective filing date of the invention, as taught by Nedea et al. teaches
With respect to the limitations of Claims 11, 12, Nedea et al. teaches to combine molecular dynamics (MD) and Monte Carlo (MC) simulations to study the properties of gas molecules confined between two hard walls of a microchannel or nanochannel. The coupling between MD and MC simulations is introduced by performing MD near the boundaries for accuracy and MC in the bulk because of the low computational cost. We characterize the influence of different densities and molecule sizes on the equilibrium properties of the gas in the microchannel. The effect of the particle size on the simulation results is very small in the case of a dilute gas and increases with the density. The hybrid MD-MC simulation method is validated by comparing the results for density and temperature profiles with those of pure MD and pure MC simulations (abstract, wherein the target threshold is calculated as a numerical multiple of a size of the target particle (Claim 11) wherein the molecular dynamics simulation is a Monte Carlo simulation (Claim 12)
A person of ordinary skill would be motivated to combine Vandermause et al. in view of Zhang et al. with Nedea et al. As all works deal in the same field of endeavor of molecular dynamic simulation. Nedea et al. adds the standard Monte Carlo simulation which is common and well known in molecular dynamics. There is a reasonable expectation of success because Monte Carlo is a well known algorithm which is known to work in molecular dynamics. So it is expected to work. All a Monte Carlo is a mathematical technique that uses random sampling to model the probability of different outcomes in a complex system which is known to work in MD.
Conclusion
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/C.H.B./Examiner, Art Unit 1687
/Karlheinz R. Skowronek/Supervisory Patent Examiner, Art Unit 1687
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