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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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NASA NTRS2026

The Trajectory of Recent Solid State Fusion Results

Both NASA and Google have explored and funded Low Energy Nuclear Reaction (LENR) aka Solid-State Fusion or Lattice Confinement Fusion (LCF) research. NASA has funded efforts since 1989, and Google Research began in 2014. Google, and researchers initially-funded by Google, published significant scientific papers in Nature, Nature Communications and the Journal of Applied Physics. NASA began a significant set of LENR-triggering programs in 2012 resulting in papers in Physical Review C, the Journal of Electroanalytical Chemistry and the Journal of Condensed Matter Nuclear Science. Both NASA and Google engaged researchers across fields of nuclear physics, chemistry, electrochemistry, material science and more. NASA built upon early novel gas pumping experiments then followed the patented work of the US Navy SPAWAR (US8,419,919, “System and Method to Generate Particles”) and experiments with the Naval Surface Warfare Centers. Google supported researchers at Lawrence Berkeley National Laboratory (LBNL), the University of British Columbia (UBC), MIT and others. This resulted in patent applications and two granted patents (US10264661B2, “Target structure for enhanced electron screening” and US10566094B2 “Enhanced electron screening through plasmon oscillations”). These separate efforts, unknown to the researchers at the time, provided the impetus for the DoE ARPA-E LENR program followed by the DARPA DSO “Mechanisms for Amplification of Fusion Reaction Rates in Solids” (MARRS) program. This document briefly describes the overlapping NASA and Google Research efforts in plasma loading and electron screening emphasizing the results of the latest paper in Nature Communications. The papers and patents cited are listed.

electron screening↗
DOE OSTI2024

Reverse Engineering of Medical Devices for Innovation and Advancement in Healthcare

Medical cybersecurity research addresses the critical intersection of healthcare and digital security. As medical devices expand and become increasingly interconnected, the healthcare sector is poised to become a primary target for cyber warfare. This project aims to mitigate the risks associated with a field that often underestimates the importance of cybersecurity.

Baldwin, David↗
DOE OSTI2025

Contrasting Time-Frequency Representations for Unknown Waveform Detection

Identifying unseen electromagnetic waveforms is critical for many applications, like interference management, electronic warfare and spectrum management. Traditionally this is done using statistical methods for anomaly detection, which has evolved to deep learning models for identifying the unseen data, formally termed as open set recognition. Some prior methods use a generative model to emulate open set data, which face challenges in generating synthetic samples for open set while simultaneously selecting an optimal discriminator for accurate classification. To alleviate this issue, we propose a discriminative model that effectively combines time and frequency domain features of communication signals for accurate predictions. We further introduce a cosine similarity loss that makes the domain specific features unique to enhance the prediction rate. Additionally, our model avoids generic feature vectors by extracting class-specific features during training, resulting in improved class representation. The experiment results show that this combined feature approach with cosine loss outperforms single-domain models and improves accuracy by 10% over models without cosine loss.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Detecting Unclassified Electromagnetic Signals for Secure Wireless Communication Using Open Set Recognition

We developed multiple machine learning methods for the detection and classification of new wireless communication waveforms, which is critical for targeted attacks in wireless networks and electronic warfare. Our machine learning models are capable of dynamically detecting security threats in near real time through our advanced open set recognition (OSR) approach. This model has demonstrated significant improvements in the detection of unknown waveforms, thereby enhancing the security and reliability of mission critical communications. Our approach to detecting uncertain security threats is novel; we advanced OSR techniques by incorporating domain knowledge of wireless signals. Specifically, we combined time and frequency domain model features to enhance the model’s performance. Utilizing an OSR approach eliminates the need for training data to be distributed similarly to the deployment environment and removes the requirement for the training set to contains all possible threat classes. This is crucial because it is often infeasible to determine and characterize all potential security threats in advance. Our model were trained on simulated data, generated in partnership with the University at Albany, State of New York. The data set contained a diverse array of wireless signals, including those with additive white Gaussian noise and multipath signals, with and without line of sight. This comprehensive training set allowed us to optimize our models to detect unknown waveforms under various challenging scenarios, such as low signal-to-noise ratios. By training on various waveforms, varying signal-to-noise ratio, and different sample sizes under normal conditions, our models were fine tuned to perform effectively in challenging environments.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Improved field assessments of chemicals and explosives using high-resolution gamma-ray spectroscopy with a tagged neutron interrogation system

A fi eld-portable tagged neutron interrogation system is being developed for detection of explosives and chemical warfare agents by prompt gamma-ray neutron activation analysis. The system combines an associated particle imaging deuterium-tritium neutron generator with a high-purity germanium gamma-ray detector. Fine spatial resolution neutron and alpha detectors enable precise mapping of characteristic gamma-ray emission distributions onto high-clarity neutron radiographic images. A narrow coincidence gate associated with each tagged neutron ensures a large signal-to-background ratio, thus signifi cantly improving sensitivity to the chemical compositions of the items being assessed. Recent experimental results recorded from test objects involving mock explosives and other chemicals are presented.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2025

Improved field assessments of chemicals and explosives using high-resolution gamma-ray spectroscopy with a tagged neutron interrogation system

A fi eld-portable tagged neutron interrogation system is being developed for detection of explosives and chemical warfare agents by prompt gamma-ray neutron activation analysis. The system combines an associated particle imaging deuterium-tritium neutron generator with a high-purity germanium gamma-ray detector. Fine spatial resolution neutron and alpha detectors enable precise mapping of characteristic gamma-ray emission distributions onto high-clarity neutron radiographic images. A narrow coincidence gate associated with each tagged neutron ensures a large signal-to-background ratio, thus signifi cantly improving sensitivity to the chemical compositions of the items being assessed. Recent experimental results recorded from test objects involving mock explosives and other chemicals are presented.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2024

Exploiting Multi-Domain Features for Detection of Unclassified Electromagnetic Signals

Deep Learning based classification techniques have shown excellent performance in static environments, where the training and testing samples are drawn from the same distribution. However, real world scenarios often present samples that do not belong to the known set of classes chosen during training. This is quite common for electromagnetic signals, where it is impractical to assume that all possible waveforms are known a-priori, specially in scenarios like warfare. To address this problem, we propose a deep learning based adversarial model where the generator learns to generate waveform features that can deceive the discriminator model as true samples. We introduce domain knowledge of wireless signals by decomposing the signal into a lower dimensional unique feature set, which is used for classifying known versus unknown signals. We further introduce multiple domain representations of the signal to extract features and combine them together to accurately classify new waveforms as an unknown class. Our results show that combined features from multiple domains outperform any single domain representation, especially at low SNR regimes with fewer number of samples to classify.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Exploiting Multi-Domain Features for Detection of Unclassified Electromagnetic Signals (Presentation)

Deep Learning based classification techniques have shown excellent performance in static environments, where the training and testing samples are drawn from the same distribution. However, real world scenarios often present samples that do not belong to the known set of classes chosen during training. This is quite common for electromagnetic signals, where it is impractical to assume that all possible waveforms are known a-priori, specially in scenarios like warfare. To address this problem, we propose a deep learning based adversarial model where the generator learns to generate waveform features that can deceive the discriminator model as true samples. We introduce domain knowledge of wireless signals by decomposing the signal into a lower dimensional unique feature set, which is used for classifying known versus unknown signals. We further introduce multiple domain representations of the signal to extract features and combine them together to accurately classify new waveforms as an unknown class. Our results show that combined features from multiple domains outperform any single domain representation, especially at low SNR regimes with fewer number of samples to classify.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Large Hyperfine Coupling Arising from Pseudo- 2 S Ground States in a Series of Lutetium(II) Metallocene Complexes

The synthesis of molecules with strong coupling between electronic and nuclear spins represents an important challenge in molecular quantum information science. Here, we report the synthesis and characterization of the divalent lutetium metallocene complexes Lu(Cp Me 5 )(Cp iPr 5 ) (Cp Me 5 = pentamethylcyclopentadienyl; Cp iPr 5 = pentaisopropylcyclopentadienyl), Lu(Cp iPr 4 Et ) 2 (Cp iPr 4 Et = ethyltetraisopropylcyclopentadienyl), and Lu(Cp iPr 4 ) 2 (Cp iPr 4 = tetraisopropylcyclopentadienyl). The molecular structures of these complexes, as determined through singlecrystal X-ray diffraction, feature a common bent sandwich geometry, with average Cp–Lu–Cp angles ranging from 159.9° to 152.6°. Analysis of continuous-wave electron paramagnetic resonance (EPR) spectra for the complexes reveals nearly isotropic g tensors with only a slight deviation from that of a free electron. Moreover, an extremely large splitting of the eight-line spectra indicates the presence of strong hyperfine coupling, and simulations provide isotropic hyperfine coupling constants of A iso = 4.38, 4.30, and 4.17 GHz across the series, where the value of A iso is found to decrease as the Cp–Lu–Cp angle becomes more acute. Notably, these values are the largest yet observed for any lanthanide complex. Moreover, EPR and computational analysis show that the large values of A iso stem from large s-orbital character up to 41.2% in the corresponding singly occupied molecular orbitals. To our knowledge, this degree of s-character in a molecular orbital is the largest yet reported for an open-shell isolable complex. These results outline a general strategy toward the isolation of paramagnetic molecules with strong hyperfine coupling and highly isotropic doublet electronic ground states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1958

Army Ordnance Satellite Program

The following 82 pages contain high points of Army Ordnance satellite history, beginning with scientists Hermann Oberth and Robert Goddard after World War I. Still to be written is a detailed, technical account. However, a long and helpful step in this direction is this history's contemporary, called Explorers In Orbit, a technically oriented study prepared by Vitro Engineering Company for the Army Ballistic Missile Agency. The Development Operations Division, ABMA, as well as the ABMA Historical Section have copies of this Vitro Study on file.

Guided missiles↗
DOE OSTI2026

Towards High-Speed friction stir welding of 25 mm Thick AA2139-T8: tool innovation and process development

Joining thick plates (≥ 12 mm) of aluminum (Al) alloys is challenging due to high tool forces, uneven material flow, and non-uniform heat distribution through the material’s thickness. Recent advancements in tool design and welding parameters for friction stir welding (FSW) in thick plates butt joining have encountered a developmental plateau, highlighting the need for innovative approaches to overcome existing limitations. Here, this study focuses on the systematic development of single-pass and double-pass FSW processes for high-strength aluminum alloy AA2139-T8, to improve joint efficiency and enable high-speed welding capabilities. Experimental evidence is presented for a novel tool design with opposing pin threads, enabling high-speed (178 mm/min) single-pass friction stir butt welding of 25 mm thick AA2139-T8. A series of FSW trials was conducted both in air and with a trailing water spray, using steel backing plates (BPs) to investigate the impact of quenching and cooling rates on process response and joint performance. A joint efficiency of 83% was attained using the novel tool features and effectively controlling process forces and thermal boundary conditions.

AA2139-T8↗
DOE OSTI2025

Using radioactive material to evaluate decontamination of contaminated electronics

Electronic materials are used everywhere and can get easily contaminated by their use in the field/laboratory. The goal of this project was to use radioactive material to track the effectiveness of a cleaning procedure using an off-the-shelf cleaning gel. Radioactive potassium bromide (KBr) was used as a model contaminant in four contamination scenarios to gauge the effectiveness of a cleaning gel in the decontamination of contaminated raspberry pi’s. Finally, the investigated decontamination technique was found to be 75–97% effective in removing contamination from the tested electronic devices. 95% of the contaminated electronic devices retained their functionality post-decontamination.

38 - RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCL↗
DOE OSTI2025

Groundwater flowpath characteristics drive variability in per- and polyfluoroalkyl substances (PFAS) loading across a stream-wetland system

Groundwater dependent ecosystems in areas with industrial and military land use are at risk of direct exposure to a wide range of contaminants, including PFAS chemicals. Glaciated terrain often has mixed high and low permeability sediments coupled with groundwater flow-through lake features. These hydrogeologic attributes create highly complex ‘source to seep’ dynamics that make spatiotemporal contaminant transport patterns difficult to predict. We investigated one such system in detail using a suite of heat-tracing and chemical methods. Numerous (n=57) preferential groundwater discharge zones (vertical flux rates ranging 0.2 to 3.2 m/d) were identified across the upper Quashnet River stream-wetland system in Mashpee, MA, USA, adjacent to an Air Force Base with several known PFAS source areas. Surface-water and groundwater samples were collected and analyzed (n=145) for precursors and terminal PFAS compounds between March and September 2022. Samples were collected at identified seeps along the Quashnet River (n=59), from wells upgradient from the stream-wetland system (n= 44), from contributing flow-through kettle lakes (n=8), and at multiple locations along the Quashnet River (n=34). Samples from seeps and wells had measured PFAS concentrations ranging from non-detect to approximate 3,500 ng/L (mean= 1,650 ng/L), and a range of deuterium excess values (3.2 to 15.9 per mil) indicative of varying degrees of groundwater-lake interaction prior to emergence at the discharge zones. Groundwater-lake interaction along flowpaths that sourced the sampled seeps was farther supported by significant correlations (p < 0.01) between deuterium excess and %PFAS precursors, and between %PFAS precursors and multiple terminal PFAS compounds (e.g., PFPeS, PFBS, PFHxS). However, some sampled seeps contributing groundwater to the stream-wetland system had much higher total PFAS concentrations (>1000 ng/L) than the upgradient kettle lakes, despite showing lake (evaporative) isotopic signatures, indicating the potential for groundwater flowpath convergence at wetland discharge zones and the influence of lakebed PFAS precursor reactions. PFAS compounds and water isotopic composition at sampled multilevel groundwater wells, rivers, lakes, and seeps suggest that a complex mixture of source groundwater and flowpath characteristics are responsible for diverse observed PFAS mixtures at preferential discharge zones across the stream-wetland system. Further, total PFAS loading patterns to the Quashnet River via groundwater discharge remained remarkably similar from winter to summer to fall conditions, despite a regional dry period in late summer 2022 with the upper river channel completely drying. This work addresses gaps in the existing PFAS literature by demonstrating the importance of subsurface fate and transport on PFAS compound concentrations in controlling contaminant mass loading in preferential groundwater discharge zones and presents a transferrable field toolkit for efficient characterization of spatially preferential PFAS transport dynamics.

Contaminant transport↗
NASA NTRS1992

Aircraft ship operations

Worldwide interest in the use of shipborne aircraft as a major weapons system is very broad. Many NATO countries operate fixed wing aircraft from ships. Additionally, the use of ships as helicopter platforms is extensive in the NATO community and brings another import dimension to the aircraft/ship interface issue. Thus, it seemed that both fixed and rotary wing aviation deserved equal billing in the Aircraft/Ship Interface Symposium which is the subject of this Technical Evaluation Report. This Symposium was held in Seville, Spain, from 20th to 23rd May 1991 and was the first Symposium sponsored by the AGARD Flight Mechanics Panel devoted to this topic. The Symposium contained twenty-five presentations grouped under the following topics: Keynote Addresses; Ship Environment; Guidance, Controls, and Displays; Flight Test and Simulation Techniques; Launch, Recovery, and Handling Systems Development; and Operational Views and Future Developments. The full texts of the papers presented at this Symposium are published in AGARD-CP-509.

Aircraft carriers↗
NASA NTRS2003

Mortality of atomic bomb survivors predicted from laboratory animals

Exposure, pathology and mortality data for mice, dogs and humans were examined to determine whether accurate interspecies predictions of radiation-induced mortality could be achieved. The analyses revealed that (1) days of life lost per unit dose can be estimated for a species even without information on radiation effects in that species, and (2) accurate predictions of age-specific radiation-induced mortality in beagles and the atomic bomb survivors can be obtained from a dose-response model for comparably exposed mice. These findings illustrate the value of comparative mortality analyses and the relevance of animal data to the study of human health effects.

NASA Discipline Radiation Health↗
NASA NTRS2003

Radiation-induced second cancers: the impact of 3D-CRT and IMRT

Information concerning radiation-induced malignancies comes from the A-bomb survivors and from medically exposed individuals, including second cancers in radiation therapy patients. The A-bomb survivors show an excess incidence of carcinomas in tissues such as the gastrointestinal tract, breast, thyroid, and bladder, which is linear with dose up to about 2.5 Sv. There is great uncertainty concerning the dose-response relationship for radiation-induced carcinogenesis at higher doses. Some animal and human data suggest a decrease at higher doses, usually attributed to cell killing; other data suggest a plateau in dose. Radiotherapy patients also show an excess incidence of carcinomas, often in sites remote from the treatment fields; in addition there is an excess incidence of sarcomas in the heavily irradiated in-field tissues. The transition from conventional radiotherapy to three-dimensional conformal radiation therapy (3D-CRT) involves a reduction in the volume of normal tissues receiving a high dose, with an increase in dose to the target volume that includes the tumor and a limited amount of normal tissue. One might expect a decrease in the number of sarcomas induced and also (less certain) a small decrease in the number of carcinomas. All around, a good thing. By contrast, the move from 3D-CRT to intensity-modulated radiation therapy (IMRT) involves more fields, and the dose-volume histograms show that, as a consequence, a larger volume of normal tissue is exposed to lower doses. In addition, the number of monitor units is increased by a factor of 2 to 3, increasing the total body exposure, due to leakage radiation. Both factors will tend to increase the risk of second cancers. Altogether, IMRT is likely to almost double the incidence of second malignancies compared with conventional radiotherapy from about 1% to 1.75% for patients surviving 10 years. The numbers may be larger for longer survival (or for younger patients), but the ratio should remain the same.

Review, Tutorial↗
NASA NTRS1999

Monte Carlo mixture model of lifetime cancer incidence risk from radiation exposure on shuttle and international space station

Estimating uncertainty in lifetime cancer risk for human exposure to space radiation is a unique challenge. Conventional risk assessment with low-linear-energy-transfer (LET)-based risk from Japanese atomic bomb survivor studies may be inappropriate for relativistic protons and nuclei in space due to track structure effects. This paper develops a Monte Carlo mixture model (MCMM) for transferring additive, National Institutes of Health multiplicative, and multiplicative excess cancer incidence risks based on Japanese atomic bomb survivor data to determine excess incidence risk for various US astronaut exposure profiles. The MCMM serves as an anchor point for future risk projection methods involving biophysical models of DNA damage from space radiation. Lifetime incidence risks of radiation-induced cancer for the MCMM based on low-LET Japanese data for nonleukemia (all cancers except leukemia) were 2.77 (90% confidence limit, 0.75-11.34) for males exposed to 1 Sv at age 45 and 2.20 (90% confidence limit, 0.59-10.12) for males exposed at age 55. For females, mixture model risks for nonleukemia exposed separately to 1 Sv at ages of 45 and 55 were 2.98 (90% confidence limit, 0.90-11.70) and 2.44 (90% confidence limit, 0.70-10.30), respectively. Risks for high-LET 200 MeV protons (LET=0.45 keV/micrometer), 1 MeV alpha-particles (LET=100 keV/micrometer), and 600 MeV iron particles (LET=180 keV/micrometer) were scored on a per particle basis by determining the particle fluence required for an average of one particle per cell nucleus of area 100 micrometer(2). Lifetime risk per proton was 2.68x10(-2)% (90% confidence limit, 0.79x10(-3)%-0. 514x10(-2)%). For alpha-particles, lifetime risk was 14.2% (90% confidence limit, 2.5%-31.2%). Conversely, lifetime risk per iron particle was 23.7% (90% confidence limit, 4.5%-53.0%). Uncertainty in the DDREF for high-LET particles may be less than that for low-LET radiation because typically there is very little dose-rate dependence. Probability density functions for high-LET radiation quality and dose-rate may be preferable to conventional risk assessment approaches. Nuclear reactions and track structure effects in tissue may not be properly estimated by existing data using in vitro models for estimating RBEs. The method used here is being extended to estimate uncertainty in spacecraft shielding effectiveness in various space radiation environments.

NASA Center LaRC↗