DETAILED ACTION
This Office Action is sent in response to Applicant’s Communication received 5/18/2026 for application number 17/707,053.
Claims 1-7, 9-10, 12, 14-20 are pending.
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 .
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 1-7, 9-10, 12, 14-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Independent claims 1, 15, and 18 recite(s):
Claim 1: A machine learning (ML) system for material discovery, comprising: a processor; and a memory communicably coupled to the processor and storing machine-readable instructions that, when executed by the processor, cause the processor to: select a dataset representing at least a portion of a material space, the dataset comprising formation energy values as a function of material composition derived from simulation or experimental measurement; train a machine learning model to learn a convex function approximating the dataset in a primal space; duality transform hyperplanes of the learned convex function from the primal space to a dual space; learn a convex hull of the duality transformed convex function hyperplanes in the dual space; duality transform at least one hyperplane of the learned convex hull back to the primal space; and predict, based on the at least one duality transformed hyperplane of the learned convex hull, at least one optimized material composition within the material space with a computation time for predicting the at least one optimized material composition, compared to first-principle material simulations, reduced by iteratively transforming subspaces of the learned convex function between the primal space and dual space.
Claim 15: A material discovery machine learning (ML) system for reducing computation time, the ML system comprising: a processor; and a memory communicably coupled to the processor and storing machine-readable instructions that, when executed by the processor, cause the processor to: select a dataset representing at least a portion of a material space, the dataset comprising formation energy values associated with material compositions obtained from atomistic simulation or experimental data; train a machine learning model comprising a Gaussian process regression model or a Softmax-affine convex function model to learn a convex function approximating the dataset in a first space; learn a first minimum of learned convex function in the first space; transform a subspace of the learned convex function from the first space to a second space, the first learned minimum in the first space being an endpoint in the second space; learn a second minimum of the subspace of the learned convex function in the second space; and predict, based at least in part on the first learned minimum and the second learned minimum a first optimized material composition and a second optimized material composition different than the first optimized material composition within the material space, with the first optimized material composition and the second optimized material composition reinforcing known experimental or calculated data for a stable single-phase compound.
Claim 18: A method for material discovery comprising: selecting a dataset from a candidate dataset, the dataset representing at least a portion of a material space, the dataset comprising formation energy values as a function of a material composition derived from physical measurements or atomistic simulations; training a machine learning model comprising a Gaussian process regression model or convex function model to learn a convex function approximating the dataset in a primal space; duality transforming hyperplanes of the learned convex function from the primal space to a dual space; learning a convex hull of the duality transformed convex function hyperplanes in the dual space; duality transforming at least one hyperplane of the learned convex hull back to the primal space; and predicting, based on the at least one duality transformed hyperplane of the learned convex hull, at least one stable material composition within the material space, the stable material composition corresponding to a minimum formation energy identified from the learned convex function and representing a thermodynamically stable single-phase material and reinforcing known experimental or calculated data for a stable single-phase compound.
(2A, prong 1) The underlined portions of the claims recite an abstract idea, specifically mathematical calculations. The underlined portions of the claims recite a series of mathematical operations / calculations. “It is important to note that a mathematical concept need not be expressed in mathematical symbols, because ‘[w]ords used in a claim operating on data to solve a problem can serve the same purpose as a formula.’ In re Grams, 888 F.2d 835, 837 and n.1, 12 USPQ2d 1824, 1826 and n.1 (Fed. Cir. 1989),” See MPEP 2106.04(a)(2)(I).
(2A, prong 2) This judicial exception is not integrated into a practical application. The independent claims recite the additional elements of (1) generic computer components like a processor and memory, (2) selecting a dataset representing at least a portion of a material space, the dataset comprising formation energy values associated with material compositions obtained from simulations or experiments, (3) stating the computation is reduced (for claim 1) or (4) the optimized material compositions reinforcing known data (for claims 15 and 18). Additional element (1) is a mere instruction to apply the exception on a generic computer. Specifically, the recited memory and processor are merely generic computer components added after the fact to the abstract idea. See MPEP 2106.05(f). Additional element (2) insignificant extra-solution activity because it merely amounts to necessary data gathering for implementation of the abstract idea. Selecting a type of information for analysis is insignificant extra-solution activity. See MPEP 2106.05(g), citing Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016). Additional elements (3) and (4) are field of use limitations: these limitations merely indicates a field of use, material discovery, in which to apply the mathematical calculations. For (3) in claim 1, the limitation specifies the mathematical calculations being faster than first-principle material simulations. For (4) in claims 15 and 18, the limitation states the predicted materials reinforce known experimental or calculated single-phase compound data. Similar to the additional elements in Parker v. Flook, 437 U.S. 584, 198 USPQ 193 (1978), and Electric Power Group, 830 F.3d at 1354, limitations (3) and (4) tie an abstract idea to a particular field, see MPEP § 2106.05(h). Limiting mathematical concepts to material discovery does not integrate the abstract idea into a practical application. Even when all of the additional elements are considered together with the abstract idea, the claim as a whole is not integrated into a practical application because additional elements (1), (2), (3), and (4) merely add instructions to apply the exception, insignificant extra-solution activity, and a field of use limitations to the mathematical calculations.
(2B) The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Additional element (1) is a mere instruction to apply the exception on a generic computer by adding generic computer components after the fact to the abstract idea. See MPEP 2106.05(f). Additional element (2) is well-understood, routine, and conventional activity analogous to “Receiving or transmitting data over a network,” Intellectual Ventures v. Symantec, 838 F.3d 1307, 1321; 120 USPQ2d 1353, 1362 (Fed. Cir. 2016) and, “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). See MPEP 2106.05(d). Additional elements (3) and (4) are field of use limitations that indicates that the material discovery field of use is intended for the mathematical calculations. Even when all of the additional elements are considered together with the abstract idea, the claim as a whole does not amount to significantly more than the judicial exception because additional elements (1), (2), and (3) merely add instructions to apply the exception, insignificant extra-solution activity that is well-understood, routine and conventional, and a field of use limitation to the mathematical calculations. Overall, the additional elements merely specify the mathematical calculations are executed on generic computer hardware that receives data for the calculations, and are intended for material discovery, which does not add up to significantly more than the abstract idea itself.
With respect to dependent claims 2-7, 9-10, 12, 14, 16, and 19, (2A, prong 1) these claims recite additional mathematical calculations, and therefore they merely add to the recited abstract idea in the parent claims.
With respect to dependent claims 17 and 20, these claims recite the additional limitation of, (5) “the dataset comprises formation energy versus composition data and the at least one optimized material composition is a stable single-phase material composition.”
(2A, prong 2). This additional limitation does not integrate the abstract idea into a practical application because it is a field of use limitation. Limiting the analyzed data to, “formation energy versus composition data,” and the prediction to, “a stable single-phase material composition,” only limits the use of the mathematical calculations to a type of material composition data. For example, limiting a mathematical formula to, “a process comprising the catalytic chemical conversion of hydrocarbons,” does not make a concept patentable. See Parker v. Flook, 437 U.S. 584, 586 198 USPQ 193, 196 (1978) and MPEP 2106.05(h). Even when all of the additional elements are considered together with the abstract idea, the claim as a whole is not integrated into a practical application because additional elements (1)-(5) merely add instructions to apply the exception, insignificant extra-solution activity, and field of use limitations to the mathematical calculations.
(2B) This additional limitation does not amount to significantly more than the abstract idea itself because it is a field of use limitation that merely confines the use of the mathematical calculations to a particular type of data and field-of-use. See MPEP 2106.05(h). Even when all of the additional elements are considered together with the abstract idea, the claim as a whole does not amount to significantly more than the judicial exception because additional elements (1)-(5) merely add instructions to apply the exception, insignificant extra-solution activity that is well-understood, routine and conventional, and field-of-use limitations to the mathematical calculations.
Response to Arguments
Applicant's arguments filed 5/18/2026 with respect to the 101 rejection have been fully considered but they are not persuasive. Specifically, Applicant argues that the claims recite physical and structural limitations, the claims are integrated into a practical application at step 2A, prong 2 because they are a technological improvement in materials discovery, and the additional elements in the claim amount to significantly more than the abstract idea itself at step 2B. The Examiner respectfully disagrees.
First, for (1), the applicant argues that, “formation energy is a physical property of materials, is experimentally or simulation-derived for actual material compositions,” and through reduced computation time improve the technological process for materials discovery. See Applicant’s Arguments of 5/18/2026, pages 16-18. As the 101 rejection above explains, the limitations that specify that the input data is physical material property data, and that the output is predicted materials that reinforce known data and predicts more efficiently, are field of use limitations because they merely confine the mathematical calculations to the field of use of materials discovery. The claimed mathematical calculations of duality transformation and learning convex hulls for predictions are general mathematical concepts that are studied in the abstract1, and have applications in different areas, such as housing data2 and policy optimization problems3. Thus, the additional elements limiting the mathematical calculations to represent material formation energy and output stable materials are merely limiting the math to a particular field of use and not integrating the abstract idea into a practical application.
At step 2B, Applicant emphasizes the claims contain unconventional and non-generic calculations and argues the additional elements are more than nominal post-solution activity. Here the Examiner acknowledges the claimed mathematical calculations are novel and non-obvious. However, “The process itself, not merely the mathematical algorithm, must be new and useful. Indeed, the novelty of the mathematical algorithm is not a determining factor at all.” See Parker v. Flook, 437 U.S. at 591. While an improvement to a technical field can furnish an inventive concept, “the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements. … In addition, the improvement can be provided by the additional element(s) in combination with the recited judicial exception.” See MPEP § 2106.05(a). Here, the entirety of the improvement for improved materials discovery lies in the recited mathematical calculations. The additional elements, even when considered in combination with the mathematical calculations, do not amount to significantly more than the abstract idea itself, or provide an improvement to a technical field. In other words, the claimed improvements are to math itself, and improvements would be equally applicable to other fields like housing data or policy optimization; here, however, the additional elements limit the math to the field of materials discovery (as well as adding mere instructions to apply the exception on a generic computer and other insignificant extra-solution activity that well-understood, routine, and conventional, see 101 rejection above), making predicting a new stable material more efficient, rather than more efficiently predicting housing values or other data. Thus, the additional elements do not amount to significantly more than the abstract idea itself at step 2B.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Andrew T. Chiusano whose telephone number is (571)272-5231. The examiner can normally be reached M-F, 10am-6pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Tamara Kyle can be reached at 571-272-4241. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ANDREW T CHIUSANO/Primary Examiner, Art Unit 2144
1 See Artstein-Avidan et al, A new duality transform, cited in IDS of 3/29/2022
2 See Boţ et al., Regression tasks in machine learning via Fenchel duality at page 13, cited in Non-Final action of 7/30/2025
3 See Nachum et al., Reinforcement Learning via Fenchel-Rockafellar Duality at page 2, cited in Non-Final action of 7/30/2025
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