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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 721 records · Page 40

Vacancies in graphene: an application of adiabatic quantum optimization

Quantum annealers have grown in complexity to the point that quantum computations involving a few thousand qubits are now possible. In this paper, with the intentions to show the feasibility of quantum annealing to tackle problems of physical relevance, we used a simple model, compatible with the capability of current quantum annealers, to study the relative stability of graphene vacancy defects. By mapping the crucial interactions that dominate carbon-vacancy interchange onto a quadratic unconstrained binary optimization problem, our approach exploits the ground state as well as the excited states found by the quantum annealer to extract all the possible arrangements of multiple defects on the graphene sheet together with their relative formation energies. Furthermore, this approach reproduces known results and provides a stepping stone towards applications of quantum annealing to problems of physical–chemical interest.

36 MATERIALS SCIENCE↗

Biomedical Applications of NASA Science and Technology

During the period 15 September 1968 to 14 December 1968, the NASA supported Biomedical Application Team at the Research Triangle Institute has identified 6 new problems, performed significant activities on 15 of the active problems identified previously, performed 5 computer searches of the NASA aerospace literature, and maintained one current awareness search. As a partial result of these activities, one technology transfer was accomplished. As a part of continuing problem review, 13 problems were classified inactive. Activities during the quarter involved all phases of team activity with respect to biomedical problems. As has been observed in preceding years, it has been exceedingly difficult to arrange meetings with medical investigators during the fourth quarter of the calendar year. This is a result of a combination of factors. Teaching requirements, submission of grant applications and holidays are the most significant factors involved. As a result, the numbers of new problems identified and of transfers and potential transfers are relatively low during this quarter. Most of our activities have thus been directed toward obtaining information related to problems already identified. Consequently, during the next quarter we will follow up on these activities with the expectation that transfers will be accomplished on a number of them. In addition, the normal availability of researchers to the team is expected to be restored during this quarter, permitting an increase in new problem identification activities as well as follow-up with other researchers on old problems. Another activity scheduled for the next quarter is consultation with several interested biomedical equipment manufacturers to explore means of effective interaction between the Biomedical Application Team and these companies.

Brown, James N., Jr.↗

Quantum guidelines for solid-state spin defects

Defects with associated electron and nuclear spins in solid-state materials have a long history relevant to quantum information science going back to the first spin echo experiments with silicon dopants in the 1950s. Since the turn of the century, the field has rapidly spread to a vast array of defects and host crystals applicable to quantum communication, sensing, and computing. From simple spin resonance to long-distance remote entanglement, the complexity of working with spin defects is fast advancing, and requires an in-depth understanding of their spin, optical, charge, and material properties in this modern context. This is especially critical for discovering new relevant systems dedicated to specific quantum applications. In this review, we therefore expand upon all the key components with an emphasis on the properties of defects and the host material,on engineering opportunities and other pathways for improvement. Finally, this review aims to be as defect and material agnostic as possible, with some emphasis on optical emitters,providing a broad guideline for the field of solid-state spin defects for quantum information.

36 MATERIALS SCIENCE↗

Randomized Adiabatic Quantum Linear Solver Algorithm with Optimal Complexity Scaling and Detailed Running Costs

Solving linear systems of equations is a fundamental problem with a wide variety of applications across many fields of science, and there is increasing effort to develop quantum linear solver algorithms. Subaşı et al. [Phys. Rev. Lett. 122, 060504 (2019)] proposed a randomized algorithm inspired by adiabatic quantum computing, based on a sequence of random Hamiltonian simulation steps, with suboptimal scaling in the condition number 𝜅 of the linear system and the target error 𝜖. Here we go beyond these results in several ways. Firstly, using filtering [Lin and Tong, Quantum 4, 361 (2020)] and Poissonization techniques [Cunningham and Roland, ArXiv:2406.03972 (2024)], the algorithm complexity is improved to the optimal scaling 𝑂⁡(𝜅⁢log (1/𝜖))—an exponential improvement in 𝜖, and a shaving of a log 𝜅 scaling factor in 𝜅. Secondly, the algorithm is further modified to achieve constant factor improvements, which are vital as we progress towards hardware implementations on fault-tolerant devices. We introduce a cheaper randomized walk operator method replacing Hamiltonian simulation—which also removes the need for potentially challenging classical precomputations; randomized routines are sampled over optimized random variables; circuit constructions are improved. We obtain a closed formula rigorously upper bounding the expected number of times one needs to apply a block-encoding of the linear system matrix to output a quantum state encoding the solution to the linear system. The upper bound is 837⁢𝜅 at 𝜖 = 10 −10 for Hermitian matrices.

97 MATHEMATICS AND COMPUTING↗

Integration of multi-discipline data processing for earth observing systems

The first steps taken to ensure the controlled evolution of existing facilities toward greater interoperability and sharing of resources among NASA-supported earth science and applications data systems (ESADS) are described. Recommendations made by the various panels during the 1987 ESADS Workshop are presented. The panels were concerned with directories and catalogs, data archives, data manipulation software, computational facilities, data storage media, database management, and networking. Consideration was also given to the tracking and tuning of overall development and management coordination issues.

Kahn, Ralph↗

Nanotechnology: Opportunities and Challenges

Nanotechnology seeks to exploit novel physical, chemical, biological, mechanical, electrical, and other properties, which arise primarily due to the nanoscale nature of certain materials. A key example is carbon nanotubes (CNTs) which exhibit unique electrical and extraordinary mechanical properties and offer remarkable potential for revolutionary applications in electronics devices, computing, and data storage technology, sensors, composites, nanoelectromechanical systems (NEMS), and as tip in scanning probe microscopy (SPM) for imaging and nanolithography. Thus the CNT synthesis, characterization, and applications touch upon all disciplines of science and engineering. This presentation will provide an overview and progress report on this and other major research candidates in Nanotechnology and address opportunities and challenges ahead.

Meyyappan, Meyya↗

Cumulative Index to NASA Tech Briefs 1963-1969

Tech Briefs are short announcements of new technology derived from the research and development activities of the National Aeronautics and Space Administration. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This Cumulative index to NASA Tech Briefs lists those published from 1963 through 1969. The main listing is divided into six categokies: Electrical (Electronic), Physical Sciences (Energy Sources), Materials (Chemistry), Life Sciences, Mechanical, and Computer Programs.

Source record↗

Earth Science Informatics Comes of Age

The volume and complexity of Earth science data have steadily increased, placing ever-greater demands on researchers, software developers and data managers tasked with handling such data. Additional demands arise from requirements being levied by funding agencies and governments to better manage, preserve and provide open access to data. Fortunately, over the past 10-15 years significant advances in information technology, such as increased processing power, advanced programming languages, more sophisticated and practical standards, and near-ubiquitous internet access have made the jobs of those acquiring, processing, distributing and archiving data easier. These advances have also led to an increasing number of individuals entering the field of informatics as it applies to Geoscience and Remote Sensing. Informatics is the science and technology of applying computers and computational methods to the systematic analysis, management, interchange, and representation of data, information, and knowledge. Informatics also encompasses the use of computers and computational methods to support decisionmaking and other applications for societal benefits.

Jodha, Siri↗

NASA Small Spacecraft and Distributed Systems Program - Recent and Upcoming Technology Demonstrations and Development Efforts

NASA’s Small Spacecraft & Distributed Systems (SSDS) program strengthens U.S. ability to conduct unique missions by rapidly developing and demonstrating capabilities for SmallSat exploration, science, and commercial space. In collaboration with NASA Centers, other government agencies, commercial industry, and academia, SSDS advances next generation SmallSat technologies like power, processing, propulsion, communications, autonomous navigation, architectures (swarms), and applications (AI/ML/Edge Computing)—to extend missions beyond LEO into cislunar and planetary space. Various investment mechanisms exist for SSDS to select and fund projects that will ultimately advance NASA’s Moon to Mars Architecture. Presented here are the latest achievements and findings from recently completed SSDS projects, along with updates from ongoing efforts and planned future work. Successful missions like Starling and CAPSTONE continue to demonstrate their capability after several years on-orbit. Advancements in next generation swarm configurations are being implemented by Starling for space traffic monitoring and management applications. Findings from recent SSDS flight projects are discussed: DiskSat, a unique SmallSat platform alternative to canisterized nanosatellites, launched December 2025 and is gathering data; the PTD series of missions concluded in December 2025. Current SSDS efforts are focused on addressing NASA Shortfalls relating to rendezvous and proximity operations, neuromorphic computing, and space situational awareness.

Roger C Hunter↗

NASA Small Spacecraft and Distributed Systems: Recent and Upcoming Technology Demonstrations and Development Efforts

NASA’s Small Spacecraft & Distributed Systems (SSDS) program strengthens U.S. ability to conduct unique missions by rapidly developing and demonstrating capabilities for SmallSat exploration, science, and commercial space. In collaboration with NASA Centers, other government agencies, commercial industry, and academia, SSDS advances next generation SmallSat technologies like power, processing, propulsion, communications, autonomous navigation, architectures (swarms), and applications (AI/ML/Edge Computing)—to extend missions beyond LEO into cislunar and planetary space. Various investment mechanisms exist for SSDS to select and fund projects that will ultimately advance NASA’s Moon to Mars Architecture. Presented here are the latest achievements and findings from recently completed SSDS projects, along with updates from ongoing efforts and planned future work. Successful missions like Starling and CAPSTONE continue to demonstrate their capability after several years on-orbit. Advancements in next generation swarm configurations are being implemented by Starling for space traffic monitoring and management applications. Findings from recent SSDS flight projects are discussed: DiskSat, a unique SmallSat platform alternative to canisterized nanosatellites, launched December 2025 and is gathering data; the PTD series of missions concluded in December 2025. Current SSDS efforts are focused on addressing NASA Shortfalls relating to rendezvous and proximity operations, neuromorphic computing, and space situational awareness.

Roger Hunter↗

Early detection and uncertainty quantification of rapid sea-level rise from Antarctica

Focal Areas: (i) classification and/or anomaly detection methods applied towards identifying critical climate system thresholds; improved emulator design for (ii) reducing computational costs relative to full-physics models and (iii) improved uncertainty quantification workflows. Rationale: The evolution of the Antarctic ice sheet in response to climate change remains the single largest uncertainty in projecting future sea-level rise (SLR), with risk-averse projections for 2100 spanning between zero and a half meter. During the past decade, DOE has made substantial investments in new ice sheet and Earth system models needed to improve both understanding and predictive capability in this area. Yet major challenges remain, including better understanding when and under what circumstances significant increases in SLR from Antarctica may be initiated and better quantifying uncertainties in model-based SLR projections. Here, we discuss the potential for transformative advances in these areas through the application of machine learning and artificial intelligence (ML and AI, respectively).

54 ENVIRONMENTAL SCIENCES↗

Challenges and transformative opportunities in superconductor vortex physics

In superconductors, the motion of vortices introduces unwanted dissipation that is disruptive to applications. Fortunately, material defects can immobilize vortices, acting as vortex pinning centers, which engenders dramatic improvements in superconductor material properties and device operation. This has motivated decades of research into developing methods of tailoring the disorder landscape in superconductors to increase the strength of vortex pinning. Yet, efficacious materials engineering still eludes us. The electromagnetic properties of real (disordered) superconducting materials cannot yet be reliably predicted, such that designing superconductors for applications remains a largely inefficient process of trial and error. This is ultimately due to large gaps in our knowledge of vortex dynamics: the field is challenged by the extremely complex interplay between vortex elasticity, vortex-vortex interactions, and material disorder. Here, we review obstacles and recent successes in understanding and controlling vortex dynamics in superconducting materials and devices. We further identify major open questions and discuss opportunities for transformative research in the field. This includes improving our understanding of vortex creep, determining and reaching the ceiling for the critical current, advanced microscopy to garner accurate structure-property relationships, frontiers in predictive simulations and the benefits of artificial intelligence, as well as controlling and exploiting vortices in quantum information applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Clarifying trust of materials property predictions using neural networks with distribution-specific uncertainty quantification

It is critical that machine learning (ML) model predictions be trustworthy for high-throughput catalyst discovery approaches. Uncertainty quantification (UQ) methods allow estimation of the trustworthiness of an ML model, but these methods have not been well explored in the field of heterogeneous catalysis. Herein, we investigate different UQ methods applied to a crystal graph convolutional neural network to predict adsorption energies of molecules on alloys from the Open Catalyst 2020 dataset, the largest existing heterogeneous catalyst dataset. We apply three UQ methods to the adsorption energy predictions, namely k-fold ensembling, Monte Carlo dropout, and evidential regression. The effectiveness of each UQ method is assessed based on accuracy, sharpness, dispersion, calibration, and tightness. Evidential regression is demonstrated to be a powerful approach for rapidly obtaining tunable, competitively trustworthy UQ estimates for heterogeneous catalysis applications when using neural networks. Recalibration of model uncertainties is shown to be essential in practical screening applications of catalysts using uncertainties.

36 MATERIALS SCIENCE↗

Detector alignment for X-ray crystallography using Millepede-II

I describe a method for accurately refining the geometrical parameters of segmented X-ray area detectors on the basis of serial crystallography data, using 'Millepede' – an algorithm created for a very similar problem in high-energy physics. The Millepede method for serial crystallography builds on the approach of Brewster et al. [Acta Cryst. (2018), D74, 877–894], in which the detector parameters are refined simultaneously with the parameters for each individual crystal. This accounts for the mutual dependency between the parameters and thereby avoids the bias and slow convergence problems that have afflicted older approaches in which the deviations between observed and calculated Bragg peak positions were taken directly as the updates for the detector panel positions. The Millepede method uses the special structure of the least-squares normal equations to reduce them to a much smaller form that can be solved very quickly, even compared with the sparse matrix methods used previously. This makes it practical to refine the detector geometry frequently and thereby maintain accurate calibration without specialized alignment campaigns. Tilts of detector panels out of the plane can be reliably refined, as can the overall distance of the detector in the beam direction. With a simulated test case, the new method produced panel shifts within 7% of the correct values with only one iteration, and produced almost exactly correct shifts after a second iteration. A simulated out-of-plane panel rotation was correctly determined to within 0.001°. Applied to experimental data from an X-ray free-electron laser, the method increased the indexable fraction of frames from 30% to 91% in a single iteration, and to 96% after two further iterations. Computing the geometry updates on the basis of 2060 crystals took only 0.819 s on desktop computing hardware, including the time taken to read the required data from disk. The scaling was found to be very close to linear for up to 100 980 sets of crystal parameters, which took only 78.2 s to process under the same conditions. The method has been applied as part of a real-time feedback system at a synchrotron radiation beamline, in which an out-of-plane detector tilt of 0.04° was detected and corrected. Possible further applications are also described here.

Millepede-II↗

Computational Modeling and Simulation for Nonproliferation: The History (and Present) of Monte Carlo and the MCNP(R) Code at Los Alamos [Slides]

The emergence of the Monte Carlo method as a research tool springs from work done at Los Alamos in the 1940s.Monte Carlo and the MCNP Code have been and continue to be developed at Los Alamos for many decades. From basic science in support of understanding nuclear interaction physics to global security applications, application uses of the code are extensive. Recent R&D projects and code modernization efforts make the MCNP code a great tool for nuclear nonproliferation applications. In collaboration with nuclear safeguards experts, new training has just recently been developed to help new practitioners learn how to use the code for nuclear safeguards applications.

97 MATHEMATICS AND COMPUTING↗

All-silicon quantum light source by embedding an atomic emissive center in a nanophotonic cavity

Silicon is the most scalable optoelectronic material but has suffered from its inability to generate directly and efficiently classical or quantum light on-chip. Scaling and integration are the most fundamental challenges facing quantum science and technology. We report an all-silicon quantum light source based on a single atomic emissive center embedded in a silicon-based nanophotonic cavity. We observe a more than 30-fold enhancement of luminescence, a near-unity atom-cavity coupling efficiency, and an 8-fold acceleration of the emission from the all-silicon quantum emissive center. Our work opens immediate avenues for large-scale integrated cavity quantum electrodynamics and quantum light-matter interfaces with applications in quantum communication and networking, sensing, imaging, and computing.

36 MATERIALS SCIENCE↗