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DOE OSTI2025

Characterization of High Speed Optical and Magnetic Interactions in Superconducting Nanowire Single Photon Detectors

Single-photon detectors are essential tools for quantum photonics. The ideal single photon detector would exhibit a quantum efficiency (QE) of 100% (i.e. no false negatives), zero dark photon counts per second (i.e. no false positives), zero dead time (i.e. the detector is capable of detecting one photon immediately after another), and zero jitter (i.e. the electrical signal produced by the detector perfectly reproduces the timing of the input photon signal). Commercially available avalanche photodiodes (APDs) have generally performed reasonably well for visible wavelengths but they perform poorly at longer wavelengths. For wavelengths spanning the near- ultraviolet (UV) to the mid- infrared (IR), superconducting nanowire single photon detectors (SNSPDs) can exhibit quantum efficiencies exceeding 90% with dark count rates and timing jitter roughly an order of magnitude less than is typically seen in APDs. While SNSPDSs are now commercially available from several small businesses, fundamental questions about the nature of photon interactions with superconducting nanostructures remain.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

Deflagration to Detonation Transition Update: XDDT Code Modularization

A legacy FORTRAN 77 implementation of the Baer–Nunziato two-phase mixture theory for deflagration-to-detonation transition (DDT) in reactive granular materials—hereafter the XDDT (eXplosive DDT) code—has been modularized to Fortran 90 with modular structure, external input files, and adaptive mesh capability. During validation, two code defects were identified and corrected: an inconsistency in the nodal solid pressure evaluation and a nonphysical burn-front tracking criterion. The ignition criterion was also corrected to use the granular surface temperature from the interface heat transfer model, matching the original Baer implementation. An initial attempt to validate against Figure 3 of the original Baer and Nunziato (1986) paper revealed that the code’s detonation velocity on a 201-node mesh (5.5 km/s) was approximately 21% below the expected Chapman–Jouguet value for 70% TMD HMX (∼7 km/s). Validation was redirected to the piston-driven DDT experiments of McAfee et al. (1989), Shot B-9036, for which well-characterized ionization-pin data are available. With the compaction-burn coefficient calibrated to 𝐶 𝛼 = 75, the XDDT code reproduces the DDT transition time to within 0.4% and produces a steady-state detonation velocity within 4% of the McAfee experimental value of 6.36 km/s. The burn model was generalized to support pressure-dependent exponents, enabling application to nitrocellulose-based ball propellants (TS3659) with a cube-root pressure dependence. Validation against the Sandusky/Baer PDC82 piston-impact experiment yielded a reactive wave velocity of 2.3–2.8 km/s, in good agreement with the experimental value of ∼2.2 km/s, and wave coalescence within 5% of the experimental timing. The mathematical model, input parameter requirements, and a roadmap for extending XDDT to PETN with an autocatalytic burn model are presented.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2026

Dense autoencoders, clustering techniques, and semi-supervised learning for HPGe $γ$-spectra

Classifying high-resolution gamma spectra by their isotopic content is an essential task in nuclear forensics and other applications. Traditional analysis methods are often time-intensive, but machine learning (ML) may help analysts quickly process many spectra. Such methods tend to rely on abundant, well-labeled data for training. Historical gamma data exists in various fields but is not uniformly useful for supervised ML due to inconsistent labeling. Here, to address some of these challenges, we present a method to classify and organize unlabeled data from high-purity germanium detectors using an autoencoding neural network (autoencoder). We trained dense autoencoders to compress gamma data into latent representations that enable efficient data characterization. By clustering the encoded spectra or lower-dimensional mappings of them, we identified and removed portions of over-abundant data categories, resulting in a more balanced dataset and improved autoencoder performance. This encoding and clustering pipeline also enabled the organization of spectra into self-consistent categories. Finally, we found that encoded representations showed potential as inputs for semi-supervised learning of nuclide identification (NID) labels, achieving an average F1 score of 0.85 ± 0.03 when mapping encodings to a set of 65 isotope labels.

Autoencoders↗

DOE OSTI2025

Quantifying dispersity in size and shape of nanoparticles from small-angle scattering data using machine learning based CREASE

Here, we use machine learning (ML) enhanced computational reverse engineering analysis of scattering experiments (CREASE) to interpret small-angle X-ray scattering (SAXS) data obtained from a system of nanoparticles without a priori knowledge of their exact shapes (e.g. spheres or ellipsoids), sizes (0.5–50 nm) and distributions. The SAXS measurements yielded three categories of scattering profiles exhibiting 'strong', 'weak' and 'no' features. Diminishing features (e.g. broadening or disappearing peaks) in scattering profiles have always been attributed to the presence of significant dispersity in the system. Such featureless SAXS data are not suitable for traditional analysis using analytical models. If one were to fit a relevant analytical model (e.g. the lmfit analytical model for polydisperse spheres) to these 'weak' and 'no' SAXS profiles from our nanoparticle systems, one would obtain non-unique interpretations of the data. Relying on electron microscopy to identify the distributions of nanoparticle shapes and sizes is also unfeasible, especially in high-throughput synthesis and characterization loops. In such situations, to identify the distributions of particle sizes and shapes that could be present in the sample, one must rely on methods like ML-CREASE to interpret the data quickly and output all relevant interpretations about the structure present in the system. The ML-CREASE optimization loop takes the experimental scattering profile as input and outputs multiple candidate solutions whose computed scattering profiles match the SAXS profile input. The ML-CREASE method outputs distributions of relevant structural features, such as the volume fraction of the nanoparticles in the system and the mean and standard deviation of the particle size and aspect ratio, assuming a type of distribution (e.g. normal, log-normal) for size and aspect ratio. We find that, for the SAXS profiles analyzed here, accounting for the shape dispersity along with size dispersity of the nanoparticles using ML-CREASE improved the match between the computed scattering profiles and input experimental profiles.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Machine-learning based approach to examine ecological processes influencing the diversity of riverine dissolved organic matter composition

Dissolved organic matter (DOM) assemblages in freshwater rivers are formed from mixtures of simple to complex compounds that are highly variable across time and space. These mixtures largely form due to the environmental heterogeneity of river networks and the contribution of diverse allochthonous and autochthonous DOM sources. Most studies are, however, confined to local and regional scales, which precludes an understanding of how these mixtures arise at large, e.g., continental, spatial scales. The processes contributing to these mixtures are also difficult to study because of the complex interactions between various environmental factors and DOM. Here we propose the use of machine learning (ML) approaches to identify ecological processes contributing toward mixtures of DOM at a continental-scale. We related a dataset that characterized the molecular composition of DOM from river water and sediment with Fourier-transform ion cyclotron resonance mass spectrometry to explanatory physicochemical variables such as nutrient concentrations and stable water isotopes ( 2 H and 18 O). Using unsupervised ML, distinctive clusters for sediment and water samples were identified, with unique molecular compositions influenced by environmental factors like terrestrial input and microbial activity. Sediment clusters showed a higher proportion of protein-like and unclassified compounds than water clusters, while water clusters exhibited a more diversified chemical composition. We then applied a supervised ML approach, involving a two-stage use of SHapley Additive exPlanations (SHAP) values. In the first stage, SHAP values were obtained and used to identify key physicochemical variables. These parameters were employed to train models using both the default and subsequently tuned hyperparameters of the Histogram-based Gradient Boosting (HGB) algorithm. The supervised ML approach, using HGB and SHAP values, highlighted complex relationships between environmental factors and DOM diversity, in particular the existence of dams upstream, precipitation events, and other watershed characteristics were important in predicting higher chemical diversity in DOM. Our data-driven approach can now be used more generally to reveal the interplay between physical, chemical, and biological factors in determining the diversity of DOM in other ecosystems.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1984

The 20 x 20 high speed microwave switches

Tests were conducted at NASA Lewis Research Center to characterize the proof-of-concept matrix switches built under NASA contract by Ford Aerospace and Aeronautics Corporation at Palo Alto, California, and the General Electric Company at Valley Forge, Pennsylvania. The contract requirements and goals are tabulated along with the results of the NASA tests. Characteristics examined are bandwidth, insertion loss, ripple, switching speed, isolation, standing wave ratio (input and output), deviation from linear phase, noise figure, reconfiguration rates, spurious responses, gain compression, and third order intermodulation distortion. A brief description of the testing method and a statistical analysis of the test results for each of the switches are provided.

Saunders, A.↗

NASA NTRS1991

A numerical study of the direct contact condensation on a horizontal surface

The results of a numerical study of the direct contact condensation on a slowly moving horizontal liquid surface are presented. The geometrical configuration and the input conditions used to obtain numerical solutions are representative to those of experiments of Celata et al. The effects of Prandtl number (Pr), inflow Reynolds number, and Richardson number on the condensation rate are investigated. Numerical predictions of condensation rate for laminar flow are in good agreement with experimental data. The effect of buoyancy on the condensation rate is characterized by Richardson number. A correlation based on the numerical solutions is developed to predict the average condensation Nusselt number in terms of Richardson number, Peclet number, and inflow Reynolds number.

Hasan, M. M.↗

NASA NTRS1991

A numerical study of the direct contact condensation on a horizontal surface

Hasan, M. M.↗

NASA NTRS1995

Spectral Changes in Metal Halide and High-pressure Sodium Lamps Equipped with Electronic Dimming

Electronic dimming of high-intensity discharge lamps offers control of photosynthetic photon flux (PPF) but is often characterized as causing significant spectral changes. Growth chambers with 400-W metal halide (MH) and high-pressure sodium (HPS) lamps were equipped with a dimmer system using silicon-controlled rectifiers (SCR) as high-speed switches. Phase control operation turned the line power off for some period of the alternating current cycle. At full power, the electrical input to HPS and MH lamps was 480 W (root mean squared) and could be decreased to 267 W and 428 W, respectively, before the arc was extinguished. Concomitant with this decrease in input power, PPF decreased by 60% in HPS and 50% in MH. The HPS lamp has characteristic spectral peaks at 589 and 595 nm. As power to the HPS lamps was decreased, the 589-nm peak remained constant while the 595-nm peak decreased, equaling the 589-nm peak at 345-W input, and the 589-nm peak was almost absent at 270-W input. The MH lamp has a broader spectral output but also has a peak at 589 nm and another smaller peak at 545 nm. As input power to the MH lamps decreased, the peak at 589 diminished to equal the 545-nm peak. As input power approached 428 W, the 589-nm peak shifted to 570 nm. While the spectrum changed as input power was decreased in the MH and HPS lamps, the phytochrome equilibrium ratio (P(sub fr):P(sub tot)) remains unchanged for both lamp types.

Bubenheim, David L.↗

NASA NTRS1995

Spectral Changes in Metal Halide and High-Pressure Sodium Lamps Equipped with Electronic Dimming

Electronic dimming of high-intensity discharge lamps offers control of Photosynthetic Photon Flux (PPF) but is often characterized as causing significant spectral changes. Growth chambers with 400-W Metal Halide (MH) and High-Pressure Sodium (HPS) lamps were equipped with a dimmer system using Silicon-Controlled Rectifiers (SCR) as high-speed switches. Phase control operation turned the line power off for some period of the alternating current cycle. At full power, the electrical input to HPS and MH lamps was 480 W (root mean squared) and could be decreased to 267 W and 428 W, respectively, before the arc was extinguished. Concomitant with this decrease in input power, PPF decreased by 60% in HPS and 50% in MH. The HPS lamp has characteristic spectral peaks at 589 and 595 nm. As power to the HPS lamps was decreased, the 589-nm peak remained constant while the 595-nm peak decreased, equaling the 589-nm peak at 345-W input, and 589-nm peak was almost absent at 270-W input. The MH lamp has a broader spectral output but also has a peak at 589 nm and another smaller peak at 545 nm. As input power approached 428 W, the 589-nm peak shifted to 570 nm. While the spectrum changed as input power was decreased in the MH and HPS lamps, the phytochrome equilibrium ratio (P(sub ft):P(sub tot)) remains unchanged for both lamp types.

Bubenheim, David L.↗

NASA NTRS2006

Damage Tolerance Analysis of a Pressurized Liquid Oxygen Tank

A damage tolerance assessment was conducted of an 8,000 gallon pressurized Liquid Oxygen (LOX) tank. The LOX tank is constructed of a stainless steel pressure vessel enclosed by a thermal-insulating vacuum jacket. The vessel is pressurized to 2,250 psi with gaseous nitrogen resulting in both thermal and pressure stresses on the tank wall. Finite element analyses were performed on the tank to characterize the stresses from operation. Engineering material data was found from both the construction of the tank and the technical literature. An initial damage state was assumed based on records of a nondestructive inspection performed on the tank. The damage tolerance analyses were conducted using the NASGRO computer code. This paper contains the assumptions, and justifications, made for the input parameters to the damage tolerance analyses and the results of the damage tolerance analyses with a discussion on the operational safety of the LOX tank.

Forth, Scott C.↗

NASA NTRS2011

An Active Broad Area Cooling Model of a Cryogenic Propellant Tank with a Single Stage Reverse Turbo-Brayton Cycle Cryocooler

As focus shifts towards long-duration space exploration missions, an increased interest in active thermal control of cryogenic propellants to achieve zero boil-off of cryogens has emerged. An active thermal control concept of considerable merit is the integration of a broad area cooling system for a cryogenic propellant tank with a combined cryocooler and circulator system that can be used to reduce or even eliminate liquid cryogen boil-off. One prospective cryocooler and circulator combination is the reverse turbo-Brayton cycle cryocooler. This system is unique in that it has the ability to both cool and circulate the coolant gas efficiently in the same loop as the broad area cooling lines, allowing for a single cooling gas loop, with the primary heat rejection occurring by way of a radiator and/or aftercooler. Currently few modeling tools exist that can size and characterize an integrated reverse turbo-Brayton cycle cryocooler in combination with a broad area cooling design. This paper addresses efforts to create such a tool to assist in gaining a broader understanding of these systems, and investigate their performance in potential space missions. The model uses conventional engineering and thermodynamic relationships to predict the preliminary design parameters, including input power requirements, pressure drops, flow rate, cycle performance, cooling lift, broad area cooler line sizing, and component operating temperatures and pressures given the cooling load operating temperature, heat rejection temperature, compressor inlet pressure, compressor rotational speed, and cryogenic tank geometry. In addition, the model allows for the preliminary design analysis of the broad area cooling tubing, to determine the effect of tube sizing on the reverse turbo-Brayton cycle system performance. At the time this paper was written, the model was verified to match existing theoretical documentation within a reasonable margin. While further experimental data is needed for full validation, this tool has already made significant steps towards giving a clearer understanding of the performance of a reverse turbo-Brayton cycle cryocooler integrated with broad area cooling technology for zero boil-off active thermal control.

Guzik, Monica C.↗

NASA NTRS2020

A Computational Study to Investigate the Effect of Defect Geometries on the Fatigue Crack Driving Forces in Powder-Bed AM Materials

Powder-bed additive manufacturing (AM) processes are associated with the formation of multiple types of process-specific pores, including but not limited to lack-of-fusion (LoF) and keyhole pores. The performance of an AM component is dependent on the type of pores, their density and their proximity to the free surface, and other heterogeneities in the microstructure. In order to characterize the influence of porosity on the mechanical behavior of AM materials, it is imperative to quantitatively analyze the heterogeneous strain accumulation in the vicinity of porosity. Process-specific microstructure models are generated using SPPARKS, an open-source process simulation code. Spherical keyhole or irregular LoF pores are embedded into the microstructure models, which are meshed and input into a finite element code, ScIFEN, to solve for the heterogeneous strain localization in the vicinity of the pores. Given the non-smooth geometries of LoF pores, they readily promote strain accumulation in their vicinity thereby increasing the propensity of initiating fatigue cracks.

Saikumar R Yeratapally↗

DOE OSTI2026

Advancing Detector R&D for High-Pressure Gaseous Argon TPCs in Precision Neutrino Physics

High-pressure gaseous argon time projection chambers (HPgTPCs) represent an emerging detector paradigm for neutrino physics, combining increased target density with the intrinsic tracking and low thresholds of gaseous detectors. This approach enables detailed reconstruction of exclusive final states, improved particle identification, and sensitivity to low-energy and rare processes — capabilities that are increasingly central to precision oscillation measurements and searches for beyond-the-Standard-Model signatures. This abstract presents an overview of ongoing detector R&D toward high-pressure gaseous argon TPC operation, with emphasis on micro-pattern gas detector (MPGD) charge amplification in argon-based mixtures. We report experimental characterization of triple-GEM structures at pressures relevant for neutrino applications, including studies of multiplication factor scaling, stability, and operational voltage envelopes across gas admixtures. Measurements performed at the TOAD and GORG test stands at Fermilab help define viable amplification and electronics noise regimes in conditions where higher density imposes stricter constraints on signal formation. These results provide essential input to the optimization of high-pressure gaseous argon detectors for future neutrino experiments, including near-detector concepts such as ND-GAr in DUNE Phase II near detector upgrade. More broadly, this program shows how dedicated detector R&D can expand the precision frontier in neutrino physics by enabling complementary reconstruction capabilities beyond conventional detectors.

McConnell, Brenna [Indiana U.] (ORCID:000900041138↗

NASA NTRS1984

Numerical Simulation of North Atlantic Sea Ice Variability, 1951 - 1980

A two-level dynamic-thermodynamic sea ice model is used to simulate the growth, drift and decay of sea ice in the Northern Hemisphere during a 30-year period, 1951 to 1980. The model is run with a daily timestep on a 222 km grid and is forced by interanually varying fields of geostrophic wind and temperature-derived thermodynamic fluxes. The objective is a quantitative description of large-scale sea ice variability in terms of the dynamic and thermodynamic processes responsible for the fluctuations, especially in the North Atlantic where sea ice represents a substantial input of fresh water. The fields of ice velocity and thickness contain strong seasonal as well as interannual variability. The mean drift pattern results in thicknesses of 4 to 5 m offshore of northern Canada and Greenland, while winter thicknesses of approximately 2 m are typical of Alaskan. Eurasian and East Greenland coastal waters. The 30-year mean fields are characterized by ecessive ice in the North Atlantic during winter and by a summer retreat that is more rapid than observed.

Walsh, J. E.↗

NASA NTRS1990

Submillimeter sources for radiometry using high power Indium Phosphide Gunn diode oscillators

A study aimed at developing high frequency millimeter wave and submillimeter wave local oscillator sources in the 60-600 GHz range was conducted. Sources involved both fundamental and harmonic-extraction type Indium Phosphide Gunn diode oscillators as well as varactor multipliers. In particular, a high power balanced-doubler using varactor diodes was developed for 166 GHz. It is capable of handling 100 mW input power, and typically produced 25 mW output power. A high frequency tripler operating at 500 GHz output frequency was also developed and cascaded with the balanced-doubler. A dual-diode InP Gunn diode combiner was used to pump this cascaded multiplier to produce on the order of 0.5 mW at 500 GHz. In addition, considerable development and characterization work on InP Gunn diode oscillators was carried out. Design data and operating characteristics were documented for a very wide range of oscillators. The reliability of InP devices was examined, and packaging techniques to enhance the performance were analyzed. A theoretical study of a new class of high power multipliers was conducted for future applications. The sources developed here find many commercial applications for radio astronomy and remote sensing.

Deo, Naresh C.↗

NASA NTRS1994

Power Electronics Development for the SPT-100 Thruster

Russian electric propulsion technologies have recently become available on the world market. Of significant interest is the Stationary Plasma Thruster (SPT) which has a significant flight heritage in the former Soviet space program. The SPT has performance levels of up to 1600 seconds of specific impulse at a thrust efficiency of 0.50. Studies have shown that this level of performance is well suited for stationkeeping applications, and the SPT-100, with a 1.35 kW input power level, is presently being evaluated for use on Western commercial satellites. Under a program sponsored by the Innovative Science and Technology Division of the Ballistic Missile Defense Organization, a team of U.S. electric propulsion specialists observed the operation of the SPT-100 in Russia. Under this same program, power electronics were developed to operate the SPT-100 to characterize thruster performance and operation in the U.S. The power electronics consisted of a discharge, cathode heater, and pulse igniter power supplies to operate the thruster with manual flow control. A Russian designed matching network was incorporated in the discharge supply to ensure proper operation with the thruster. The cathode heater power supply and igniter were derived from ongoing development projects. No attempts were made to augment thruster electromagnet current in this effort. The power electronics successfully started and operated the SPT-100 thruster in performance tests at NASA Lewis, with minimal oscillations in the discharge current. The efficiency of the main discharge supply was measured at 0.92, and straightforward modifications were identified which could increase the efficiency to 0.94.

Hamley, John A.↗

NASA NTRS1993

Analysis of a hardware and software fault tolerant processor for critical applications

Computer systems for critical applications must be designed to tolerate software faults as well as hardware faults. A unified approach to tolerating hardware and software faults is characterized by classifying faults in terms of duration (transient or permanent) rather than source (hardware or software). Errors arising from transient faults can be handled through masking or voting, but errors arising from permanent faults require system reconfiguration to bypass the failed component. Most errors which are caused by software faults can be considered transient, in that they are input-dependent. Software faults are triggered by a particular set of inputs. Quantitative dependability analysis of systems which exhibit a unified approach to fault tolerance can be performed by a hierarchical combination of fault tree and Markov models. A methodology for analyzing hardware and software fault tolerant systems is applied to the analysis of a hypothetical system, loosely based on the Fault Tolerant Parallel Processor. The models consider both transient and permanent faults, hardware and software faults, independent and related software faults, automatic recovery, and reconfiguration.

Dugan, Joanne B.↗