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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

SA-GAT-SR: self-adaptable graph attention networks with symbolic regression for high-fidelity material property prediction

Recent advances in machine learning have demonstrated an enormous utility of deep learning approaches, particularly Graph Neural Networks (GNNs) for materials science. These methods have emerged as powerful tools for high-throughput prediction of material properties, offering a compelling enhancement and alternative to traditional first-principles calculations. While the community has predominantly focused on developing increasingly complex and universal models to enhance predictive accuracy, such approaches often lack physical interpretability and insights into materials behavior. Here, we introduce a novel computational paradigm—Self-Adaptable Graph Attention Networks integrated with Symbolic Regression (SA-GAT-SR)—that synergistically combines the predictive capability of GNNs with the interpretative power of symbolic regression. Our framework employs a self-adaptable encoding algorithm that automatically identifies and adjust attention weights so as to screen critical features from an expansive 180-dimensional feature space while maintaining O(n) computational scaling. The integrated SR module subsequently distills these features into compact analytical expressions that explicitly reveal quantum-mechanically meaningful relationships, achieving 23 × acceleration compared to conventional SR implementations that heavily rely on first-principle calculations-derived features as input. This work suggests a new framework in computational materials science, bridging the gap between predictive accuracy and physical interpretability, offering valuable physical insights into material behavior.

36 MATERIALS SCIENCE↗
NASA NTRS1979

A new approach to data management and its impact on frequency control requirements

A new approach to data management consisting of spacecraft and data/information autonomy and its impact on frequency control requirements is presented. An autonomous spacecraft is capable of functioning without external intervention for up to 72 hr by enabling the sensors to make observations, maintaining its health and safety, and by using logical safety modes when anomalies occur. Data/information are made autonomous by associating all relevant ancillary data such as time, position, attitude, and sensor identification with the data/information record of an event onboard the spacecraft. This record is so constructed that the record of the event can be physically identified in a complete and self-contained record that is independent of all other data. All data within a packet will be time tagged to the needed accuracy, and the time markings from packet to packet will be coherent to a UTC time scale.

Blanchard, D. L.↗
NASA NTRS1982

Detection of interstellar sodium hydroxide in self-absorption toward the galactic center

A weak self-absorbed emission line, which is identified as the J = 4-3 transition of sodium hydroxide, has been detected in the direction of Sgr B2(OH). The correspondingly weak Sgr B2(QH) emission line U75406, previously reported as an unidentified spectral feature by other investigators, is consistent with the J = 3-2 transition of sodium hydroxide. This detection may represent the first evidence of a grain reaction formation mechanism for simple metal hydroxides. The detection of H62 Delta toward Orion A is also reported.

Hollis, J. M.↗
DOE OSTI2026

A procedure for rule extraction from a Self-Organising plasma disruption predictor for JET

In a previous paper, a Self-Organizing Map had proven to be able to identify the regions of the plasma operative space characterizing the pre-disruptive phase at JET without relying on any a priori information. One of the strengths of this disruption predictor lies in its inherent self-organization capability. The Self-Organizing Map discovers non-trivial relationships and captures the complicated interplay of device diagnostics on the internal plasma states directly from the experimental data. Moreover, the provided model allows the visualization of high-dimensional plasma parameters and facilitates easy interrogation of the model to understand the reasons behind its correlations. In this paper, an additional step is taken towards the interpretability of models for predicting disruptions by training a Decision Tree to classify the plasma states according to the interpretation provided by the Self-Organizing Map (stable or at high risk of disruptions). The Decision tree provides a set of rules which describe the transition of the plasma towards the pre-disruptive phase as visualized in the Self-Organizing Map. The obtained rules for the database explored in the study identify four regions in the map, two of which are at risk of disruption. These regions correspond to partitions of a 3D space based on the peaking factors of the core and divertor radiation, as well as the Locked Mode. The agreement between the Self-Organizing Map answers and the rules supplied by the Decision Tree is confirmed by the comparison of the performance exhibited by the two models in the prediction of disruptions.

Setzu, Samuele [Univ. of Cagliari, Monserrato, Cag↗
NASA NTRS1972

Computer program documentation: ISOCLS iterative self-organizing clustering program, program C094

The author has identified the following significant results. This program implements an algorithm which, ideally, sorts a given set of multivariate data points into similar groups or clusters. The program is intended for use in the evaluation of multispectral scanner data; however, the algorithm could be used for other data types as well. The user may specify a set of initial estimated cluster means to begin the procedure, or he may begin with the assumption that all the data belongs to one cluster. The procedure is initiatized by assigning each data point to the nearest (in absolute distance) cluster mean. If no initial cluster means were input, all of the data is assigned to cluster 1. The means and standard deviations are calculated for each cluster.

Minter, R. T.↗
NASA NTRS2007

Next Generation Wiring

Wiring is a major operational component on aerospace hardware that accounts for substantial weight and volumetric space. Over time wire insulation can age and fail, often leading to catastrophic events such as system failure or fire. The next generation of wiring must be reliable and sustainable over long periods of time. These features will be achieved by the development of a wire insulation capable of autonomous self-healing that mitigates failure before it reaches a catastrophic level. In order to develop a self-healing insulation material, three steps must occur. First, methods of bonding similar materials must be developed that are capable of being initiated autonomously. This process will lead to the development of a manual repair system for polyimide wire insulation. Second, ways to initiate these bonding methods that lead to materials that are similar to the primary insulation must be developed. Finally, steps one and two must be integrated to produce a material that has no residues from the process that degrades the insulating properties of the final repaired insulation. The self-healing technology, teamed with the ability to identify and locate damage, will greatly improve reliability and safety of electrical wiring of critical systems. This paper will address these topics, discuss the results of preliminary testing, and remaining development issues related to self-healing wire insulation.

Medelius, Petro↗
DOE OSTI2023

Technical Specification Surveillance Interval Extension Using Self-Diagnostics

As part of the Light Water Reactor Sustainability program, an ongoing research effort is being conducted on technical specifications surveillance interval extension of digital equipment in nuclear power plants. The research team is led by Idaho National Laboratory and includes Pacific Northwest National Laboratory, Technology Resources, and Oak Ridge National Laboratory. This research focuses on developing methods for applying the U.S. Nuclear Regulatory Commission (NRC)–approved guidance to implement a licensee-controlled, risk-informed surveillance frequency change program in digital instrumentation and control (I&C) systems that include self-diagnostics and online monitoring (OLM) capabilities. Although approved methods exist for extending technical specifications (TS) surveillance test intervals (STIs) for general equipment, including analog I&C equipment, gaps remain in technology and guidance on crediting newer digital equipment’s internal self-diagnostics and OLM characteristics. Previous research described a general methodology for crediting internal self-diagnostics for extending surveillance test intervals. The methodology used self-diagnostics to detect—and credited recovery from—failure. Self-diagnostics were also applied for performance monitoring during the extended surveillance interval. This report discusses the status of recent activities to evaluate the previously developed methodology using a pilot study. Although both a utility partner for a pilot study and a specific digital asset were identified in FY2020, delays in obtaining proprietary information resulted in a limited ability to fully evaluate the methodology, and further interactions were complicated by the COVID pandemic. Therefore, at that time, the use of public-domain information—along with current processes for surveillance interval extension through a surveillance frequency control program—identified the need to fully assess diagnostic coverage as part of the pilot study. Furthermore, self-diagnostics were also identified as a potential option to replace the drift analyses conducted as part of current STI extension procedures. In FY2022, the project was reconstituted with the industry partner, and information and data were made available by the industry partner to the research team for review. The shared information included failure event descriptions and data for a digital I&C system since its implementation, as well as recent STI extension interval reports developed by the utility partner on that digital I&C system. This report presents an evaluation of this information and data and describes an application of the proposed methodology cited above. The methodology seeks to take advantage of the self-diagnostics and OLM capabilities to reduce risk or reduce the level of qualitative monitoring assessment needed to perform a risk-informed STI extension using existing NRC approved guidance or both. Addressing these issues of STI extension by crediting self-diagnostics is likely to result in benefits for current and future nuclear power plant (NPP) operations, including lowering the barriers to adoption of digital I&C systems and increasing cost savings by deferring or eliminating unneeded preventive maintenance (tasks or checks or activities). Specifically, self-diagnostic and OLM capabilities of newer digital equipment being installed in non-safety and safety applications are designed to detect failures, provide early warning of potential failures, and notify plant operators to take appropriate action to reduce out of service (OOS) time thus protecting safety margins. Moreover, the equipment is expected to provide information that time-related operational degradation is identified early to ensure timely and planned corrective actions instead of a reactive and unplanned approach ahead of an extended-surveillance interval.

42 ENGINEERING↗
DOE OSTI2023

Structure, Function, and Application of Self–Healing Adhesives from Mistletoe Viscin

Berries from the European Mistletoe (Viscum album) possess a sticky tissue called viscin that facilitates adhesion and germination onto host trees. Recent studies of viscin have demonstrated its adhesive capacity on a range of natural and synthetic surfaces including wood, skin, metals, and plastic. Yet, the underlying mechanisms remain poorly understood. Here, an investigation of the adhesive performance of mistletoe viscin is performed, demonstrating its hygroscopic nature and ability to self-heal following adhesive failure. It is identified that adhesion originates from a water-soluble adhesive component that can be extracted, isolated, and characterized independently. Lap shear mechanical testing indicates that the mistletoe adhesive extract (MAE) outperforms native viscin tissue, as well as gum arabic and arabinogalactan—common plant-based adhesives. Furthermore, humidity uptake experiments reveal that MAE can reversibly absorb nearly 100% of its mass in water from the atmosphere. In-depth spectroscopic and mass spectrometry investigations reveal a composition consisting primarily of an atypical arabinogalactan, with additional sugar alcohols. Finally, several proof-of-concept applications are demonstrated using MAE for hygro-responsive reversible adhesion between various surfaces including skin, plastic, PDMS, and paper, revealing that MAE holds potential as a biorenewable and reusable adhesive for applications in cosmetics, packaging, and potentially, tissue engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Optimized matching conditions for self-guided laser wakefield accelerators

We revisit the matching conditions for self-guided laser pulse propagation in plasma and refine their formulation to maximize the energy of electrons produced via laser wakefield acceleration. Bayesian optimization, combined with particle-in-cell simulations carried out in a quasi-three-dimensional geometry and a Lorentz-boosted frame, is employed. The optimization identifies the maximum electron energy that a self-guided laser wakefield accelerator, driven by a laser of a given energy, can produce, together with the corresponding acceleration distance. Our results further demonstrate that electrons with energies close to the maximum value can be obtained across a relatively wide range of input parameters and without the need for their precise tuning. This provides substantial flexibility for experimental implementation and significantly relaxes the operational constraints associated with self-guided laser wakefield accelerators.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Resummation of QED radiative corrections in a strong constant crossed field

By considering radiative corrections of up to 3rd-loop order, Ritus and Narozhny conjectured that the proper expansion parameter for QED in a strong constant crossed field is $g=\alpha\chi^{2/3}$, where the dynamical quantum parameter $\chi=e\sqrt{-(Fp)^2}/m^3$ combines the particle momentum $p$ with the external field strength tensor $F$. Here we present and discuss the first non-perturbative result in this context, the resummed bubble-type polarization corrections to the electron self-energy in a constant crossed field. Our analysis confirms the relevance of the scaling parameter $g$ to the enhancement of bubble-type radiative corrections. This parameter actually represents the characteristic value of the ratio of the 1-loop polarization bubble to the photon virtuality. After an all-order resummation we identify and discuss two contributions to the self-energy with different formation regions and asymptotic behavior for $g\gg1$. Whereas the breakdown of perturbation theory occurs already for $g\gtrsim1$, the leading-order result remains dominant until the asymptotic regime $g\gg 1$ is reached. However, the latter is specific to processes like elastic scattering or photon emission and does not have to remain true for general higher-order QED processes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Quantitative evaluations of subtropical westerly jet simulations over East Asia based on multiple CMIP5 and CMIP6 GCMs

As a salient feature of the Asian monsoon system, the East Asian subtropical westerly jet (EASWJ) exerts significant impacts on weather and climate changes in China and even throughout East Asia. In this paper, we applied a new self-adaptive algorithm to detect the EASWJ, identify its boundaries, and then represent its characteristics by defining three indices: the intensity index, meridional displacement index, and width index. Compared to the reanalysis data, we carried out a comprehensive, objective, and quantitative EASWJ evaluation using historical experiments from multiple global climate models (GCMs) in the Coupled Model Intercomparison Project Phases 5 and 6 (CMIP5 and CMIP6). The results show that the multimodel ensemble mean (MME) of both CMIP5 and CMIP6 can simulate the characteristics of winter EASWJ well. While for the other three seasons, the MME of both phase models underestimate the 200-hPa zonal wind (U200) strength in the jet coverage area and overestimate the U200 outside the jet area, such simulation results weaken the meridional shear of the wind field. The EASWJ simulations from the CMIP5 GCMs had no consistent intensity or location characteristic tendencies, and most CMIP5 GCMs tended to simulate relatively wide-coverage jets. In contrast, most CMIP6 GCMs are inclined to simulate significantly weaker, wider, and more-northward jets. Compared to the predecessors in CMIP5, about half of CMIP6 GCMs significantly minimized the jet intensity bias, but remarkable errors were still observed in their jet location and coverage representations. Furthermore, the comparative analysis performed by classifying models based on their evaluated simulation results suggested that the simulated performance of the meridional temperature gradient was important for capturing the EASWJ characteristics. Further in-depth study of the causes of model differences is warranted to improve simulation results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Autonomous phase mapping of gold nanoparticles synthesis with differentiable models of spectral shape

Autonomous experimentation–or self-driving labs–offers a systematic approach to accelerate materials discovery by integrating automated synthesis, characterization, and data-driven decision-making. We present a closed-loop workflow for the on-demand synthesis and structural characterization of colloidal gold nanoparticles, enabling direct mapping from composition to nanoscale structure. Our framework leverages differentiable models of spectral shape to address two central tasks in self-driving labs: (a) phase mapping, or identifying compositional regions with distinct structural behavior; and (b) material retrosynthesis, or optimizing compositions for target structure. Using functional data analysis, we develop a data-driven model with generative pre-training, active learning, and high-throughput experiments to predict spectral responses across composition space. We demonstrate the approach on seed-mediated growth of gold nanoparticles, showcasing its ability to extract design rules, reveal secondary interactions, and efficiently navigate morphology space. Gradient-based optimization of the models enables inverse design, making this a unified platform.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Smart quantum statistical imaging beyond the Abbe-Rayleigh criterion

The wave nature of light imposes limits on the resolution of optical imaging systems. For over a century, the Abbe-Rayleigh criterion has been utilized to assess the spatial resolution limits of imaging instruments. Recently, there has been interest in using spatial projective measurements to enhance the resolution of imaging systems. Unfortunately, these schemes require a priori information regarding the coherence properties of “unknown” light beams and impose stringent alignment conditions. Here, we introduce a smart quantum camera for superresolving imaging that exploits the self-learning features of artificial intelligence to identify the statistical fluctuations of unknown mixtures of light sources at each pixel. This is achieved through a universal quantum model that enables the design of artificial neural networks for the identification of photon fluctuations. Our protocol overcomes limitations of existing superresolution schemes based on spatial mode projections, and consequently provides alternative methods for microscopy, remote sensing, and astronomy.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Signatures of enhanced spin-triplet superconductivity induced by interfacial properties

While spin-triplet pairing remains elusive in nature, there is a growing effort to realize proximity-induced equal-spin triplet superconductivity in junctions with magnetic regions or an applied magnetic field and common s-wave superconductors. To enhance such spin-triplet contribution, it is expected that junctions with a weak interfacial barrier and strong spin-orbit coupling are desirable. Intuitively, a weak interfacial barrier enables a robust proximity-induced superconductivity and strong spin-orbit coupling promotes spin mixing, converting spin-singlet into spin-triplet superconductivity. In contrast, we reveal a nonmonotonic spin-triplet contribution with the strength of the interfacial barrier and spin-orbit coupling. This picture is established by considering different signatures in conductance and superconducting correlations, as well as by performing self-consistent calculations. As a result, we identify a strongly enhanced spin-triplet superconductivity, realized for an intermediate strength of interfacial barrier and spin-orbit coupling. In junctions with magnetic regions, an enhanced spin-triplet superconductivity leads to a large magnetoanisotropy of conductance and superconducting correlations. Furthermore, this picture of an enhanced spin-triplet superconductivity is consistent with experiments demonstrating a huge increase in the conductance magnetoanisotropy, which we predict can be further enhanced at a finite bias.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Few-cycle self-compression of GW mid-IR pulses in an anti-resonant fiber in ambient air

We report self-compression of mid-IR optical pulses to the few-cycle regime in an anti-resonant hollow core fiber filled with ambient air. Transform-limited 120-fs duration input optical pulses with 160 μJ energy are compressed to 29.8 fs (< 3 cycles) with a compression efficiency of 75%, resulting in 2.6 GW peak power few-cycle pulses. In addition, we show that nonlinear compression is maintained when the fiber is coiled, allowing for a compact setup. Lastly, we elucidate the dynamics involved in this self-compression setup via numerical simulations and identify the critical role played by Raman shifting in molecular gases and ionization limitations.

Hettel, Will [University of Colorado & NIST, Bould↗
DOE OSTI2021

Hydropower Cyber-Physical Configurations

The U.S. Department of Energy’s Water Power Technologies Office funded Pacific Northwest National Laboratory, Argonne National Laboratory, and the National Renewable Energy Laboratory to develop a typology to characterize the variety and pervasiveness of cyber-physical configurations across the nation’s hydropower fleet. Outreach to owners and operators returned configurations for 275 hydropower plants or approximately 12% of the fleet. Components (OT and IT), systems, and connections among systems differed among plants according to function, age, position in the river cascade, and many other factors. Seven cyber-physical configuration types labeled A through I, included from 2 to dozens of plants. They were differentiated by how pervasive data and control connections were among cyber-physical components and how frequently control signals paired with data signals in a feedback loop. The flow of data and control within each type implies what cybersecurity vulnerabilities may exist, and what mitigation actions may be most effective. A self-assessment approach allows plant operators to identify the configuration type similar to their plant and link to the lessons learned and best practices information. The cyber-physical typology reinforces the idea that hydropower facilities vary widely, but it also identifies groups that highlight similarities in how their cyber-physical components interact. This helps address fleetwide cybersecurity needs by identifying a reasonable number of configuration types that share risks, vulnerabilities, and potential mitigations.

13 HYDRO ENERGY↗
DOE OSTI2025

The Future of X-ray Irradiation: Addressing Supply Chain Risks and Opportunities (UUR Edition)

This study supports the Office of Radiological Security’s (ORS) mission of eliminating cesium irradiators by analyzing the supply chain for self-shielded X-ray irradiators (SSXIs), identifying potential risks, and proposing mitigation measures. The research focuses on the primary components of SSXIs, including X-ray tubes, controllers, generators, and coolers or chillers, and evaluates their vulnerabilities using a comprehensive risk matrix framework. The methodology includes subject matter expert (SME) interviews with relevant manufacturers and major stakeholders, a deep literature review, and a meta-analysis of maintenance reports provided by SSXI end users. Results show that while the SSXI market is small, it’s growing, and the highly global nature of the supply chain may create vulnerabilities for critical SSXI components (X-ray tubes are the most vulnerable, followed by generators and controllers). This research communicates necessary information to address concerns of current and future end users, especially those interested in transitioning away from radioactive sources, and informs future policy aimed at supporting the irradiation industry.

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS2006

Patterns in Crew-Initiated Photography of Earth from ISS - Is Earth Observation a Salutogenic Experience?

This viewgraph presentation asks the question "Is the observation of earth from the ISS a positive (salutogenic) experience for crew members?"All images are distributed to the public via the "Gateway to Astronaut Photography of Earth at http://eol.jsc.nasa.gov. The objectives of the study are (1) Mine the dataset of Earth Observation photography--What can it tell us about the importance of viewing the Earth as a positive experience for the crewmembers? (2) Quantify extent to which photography was self-initiated (not requested by scientists) (3) Identify patterns photography activities versus scientific requested photography.

Robinson, Julie A.↗