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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

High-rate heavy-ion tracking using MWPCs and PPACs with an Anti-Discharge Unit

This work reports on the development of two robust, heavy-ion beam tracking concepts operating at low pressure (< 15 Torr) for high rate applications (> 200 kHz). The first concept consists of a Multi-Wire Proportional Counter (MWPC) with a central anode consisting of 12 μm Au-plated Tungsten wires spaced 1 mm from each other. The anode grid is sandwiched between two segmented cathodes aligned orthogonally in the two dimensions for (x,y) particle localization. The second detector is a Parallel-Plate Avalanche Counter (PPAC) that uses the same readout geometry as the MWPC, but replaces the wire anode with a 150 nm silver layer deposited on both sides of a thin (< 1 mg/cm 2 ) polypropylene foil. Additionally, the bias circuitry for the PPAC anode central foil is equipped with an Anti-Discharge Unit (ADU) to prevent transitions from proportional operation to streamer formation, thereby avoiding damaging discharges. The localization capability of both detectors was tested with a low-rate alpha-particle source (241-Am). A position resolution of < 1 mm (FWHM) was achieved under stable, high-gas-gain (> 1000) operating conditions. Their performance in terms of detection efficiency as a function of the isotope charge (Z) was determined by irradiating the detectors with a cocktail beam (Z ≤ 15) with energy of ∼ 100 MeV/u. Full detection efficiency is maintained for all available fragments under optimal operational conditions (i.e., voltage bias). Full detection efficiency was achieved at rates above 200 kHz by irradiating the detectors with a 1 cm diameter 238 U beam at an energy of 143 MeV/u.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Data Summarization and Inference at Scale

This is the final report for the DOE ASCR grant SC-0022260, Data Summarization and Inference at Scale, PI: Alex Pothen, Purdue University. The goal of the project was to solve data-intensive and compute-intensive problems in the physical sciences, engineering, information science, data science, etc. by designing and implementing new algorithms that could work with a subset of the data. The four subgoals were: (a) The solution of problems where the data is too large to be stored in the memory of a computer. In this streaming model of computation, the data arrives as a stream of elements to the computer, each element is processed as it arrives, and a decision is made to discard the data or to store it; only a small subset of the data proportional to the size of the output solution is stored, and when all the data has been streamed, a solution to the problem is computed from the stored subset. (b) The use of machine learning methods to compute solutions to data-intensive problems. The use of GPUs is critical to obtain high performance on machine learning tasks, but their memory sizes are smaller relative to that of CPUs. For large-scale problems, the data is sampled many times, and small samples are used with repetition, for robustness, to compute solutions to inference tasks. This sampling reduces the memory required to solve the problem, but attention is needed to avoid slow convergence to the solutions, and reduced accuracy of inference. We propose submodular optimization, Large Language Models, and physics-informed neural networks to enable GPU computations here. (c) Modeling and visualization of high-dimensional data using interpretable features. Clinical proteomic data sets from immunology for the detection of cancer and other diseases are temporal and high-dimensional, and algorithms for visualizing these data sets using clinically interpretable features are lacking. We propose methods that compute distances based on the optimal transportation problem and graph edit distances to address this problem. We also propose the use of optimal transport-based distances, spatial statistics, and network structure to classify image data sets, We apply these algorithms to electron micrographs of the peripheral nervous system in the digestive tract. (d) The design of data-intensive algorithms on emerging architectures, specifically, noisy, intermediate-scale quantum (NISQ) devices. Quantum computers offer the possibility of exploring large solution spaces due to the principle of superposition, but current quantum computers are limited by few qubits, short coherence times due to noise, poor interconections among the qubits, etc. We propose the use of the divide and conquer paradigm to solve large-scale problems, wherein collections of small subproblems are solved on the quantum devices, and the solutions to the subproblems are integrated into a solution for the original problem on a classical computer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Characterization Techniques Investigated for Characterization of Anomalous Materials in Plutonium Oxide – 25666

The DOE has adopted a Dilute and Dispose approach for processing surplus plutonium which consists of blending plutonium oxide with adulterants and packaging it in a form which is acceptable for disposal at the Waste Isolation Pilot Plant. The feed material for the downblend process is intended to be pure plutonium oxide powder, however other objects are occasionally encountered within the oxide, particularly with legacy material. Potential technologies which could assist in the resolution of incidents where such anomalies are encountered have been investigated. Resolution of these incidents requires characterization of the anomalous object so that plutonium oxide processing can resume and so that a disposition pathway can be determined for the anomalous material. Technologies including gamma ray spectroscopy, alpha-gamma coincidence, LiDAR volumetric measurements, and surface conductivity measurements were investigated for this purpose, with a focus on systems which can be easily introduced into the processing environment when an anomaly is encountered, then removed from the environment after resolution to avoid impeding normal processing activities. This places an emphasis on small and portable measurement systems and systems that can operate in a high-background, oxide-processing environment. Gamma ray systems investigated include the GR1™a CZT detector and the MicroGe™a germanium detector, with a focus on detecting characteristic gamma rays from Pu-239 and other actinides. A gamma ray and alpha particle coincidence method was investigated with the goal of identifying actinides in the presence of a gamma ray background produced by adjacent plutonium oxide material. Leica™b BLK360 G1 and Keyence™c LJ-X8300 LiDAR systems were investigated for use in conjunction with mass measurements to gain accurate material density values, and a Foerster Sigmatest™d 2.070 was tested to determine surface conductivity. The combination of these properties would allow improved identification and characterization of a wide variety of potential anomalous material.

Munson, Justin M.↗
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 OSTI2026

Highly Responsive Near-Infrared Photodetector Based on Contactless PdSe 2 Integration with a Few-Layered MoSe 2 Field-Effect Transistor

Two-dimensional (2D) semiconductors with narrow bandgaps are promising candidates for near- and far-infrared (IR) photodetection, particularly in the telecommunication spectral window. However, current low-bandgap IR photodetectors face significant challenges due to their high dark current, increased carrier recombination, and thermally generated noise. Here, in this work, a hybrid phototransistor is demonstrated by integrating direct, contact-free palladium diselenide (PdSe 2 ) as a highly responsive IR detection layer with a non-IR-absorbing molybdenum diselenide (MoSe 2 ) field-effect transistor (FET), using a near-IR source at a wavelength of λ = 1650 nm. Exfoliated PdSe 2 flakes integrated into a back-gated FET architecture exhibit ambipolar transport behavior, with extracted hole and electron mobilities of 24.8 cm 2 V –1 s –1 and 58.4 cm 2 V –1 s –1 , respectively. The devices show a clear photocurrent generation under the illumination of a λ = 1650 nm laser source, achieving a notable responsivity of ∼300 mA W -1 at an applied gate voltage of 15 V, which highlights the suitability of PdSe 2 as a narrow-bandgap material for photodetection. Photoresponsivity saturates and does not have any effect above an applied gate voltage of 15 V. To further tune the photoresponsivity performance continuously with the applied gate voltage, we construct a van der Waals heterostructure phototransistor, where few layers of PdSe 2 are directly transferred onto the 2D channel region of a MoSe 2 FET, while avoiding any contact with the metal electrodes. In this heterostructure, PdSe 2 works as the primary active IR-absorbing layer, while MoSe 2 provides high-performance FET characteristics. This spatial separation of absorption and transport facilitates efficient interlayer charge transfer and charge separation, resulting in high responsivities of up to 972 mA W –1 at near-IR wavelengths and a low power density of 1.5 mW/mm 2 . The responsivity of our photodetector is comparable to that of some state-of-the-art commercially available NIR photodetectors, highlighting the potential of PdSe 2 -based heterostructures as scalable, CMOS-compatible platforms for high-performance near-IR detection.

Infrared (IR) photodetectors↗
DOE OSTI2024

Energy Level Gradients from Surface to Bulk in Hybrid Metal-Halide Perovskite Thin Films

Variations in local strain, defect densities, and composition of hybrid metal-halide perovskites have been reported to create heterogeneous energy landscapes in thin films, which impact charge-carrier diffusion and recombination dynamics. Here, we employ one- and two-photon transient absorption spectroscopy to selectively probe the dynamics of charge carriers from surface and bulk regions of methylammonium lead bromide thin films. Differences in the transient absorption spectra indicate that an energy gradient of approximately 100 meV is formed between the higher band-gap surface and lower band-gap bulk regions. Thus, during their lifetime, photoexcited carriers move away from the surface to recombine in the bulk, where our experiments detect long-lived charge populations despite the significant band splitting that has conventionally been assumed to inhibit efficient radiative recombination. Supported by first-principles calculations, we demonstrate that bright emission can still arise from the bulk with states that occupy a wide range of momenta in the vicinity of the band extrema, which show strong dipole transitions. Our results report that photoexcitations in the hybrid perovskites avoid defect-rich surface regions, and that particularly strong emission is generated from accumulated excitation populations in the bulk. Published by the American Physical Society 2024

Bourelle, Sean A.↗
DOE OSTI2024

Options for Upgrading Low-Voltage Spot Network Protection to Increase DER Interconnection Capacity

Existing standards and policies for interconnecting distributed energy resources (DERs) into low voltage spot networks severely limits the amount of DER installed on those networks to avoid negative impacts on protection systems. This report investigates options for upgrading the protection systems of spot networks to allow for additional DER installations beyond the normal limits (i.e., no reverse power flows allowed onto the MV system). Eight potential upgrade options are discussed that span various methods for new network protector algorithms, hardware upgrades, and the addition of communication. Each method has tradeoffs in terms of accuracy of detecting faults, requirements to upgrade equipment in the spot networks, need for communication, and sensitivity to false trips—all of which are explored in this report.

42 ENGINEERING↗
DOE OSTI2025

DarkNESS: A skipper-CCD NanoSatellite for Dark Matter Searches

The Dark matter Nanosatellite Equipped with Skipper Sensors (DarkNESS) deploys a recently developed skipper-CCD architecture with sub-electron readout noise in low Earth orbit (LEO) to investigate potential signatures of dark matter (DM). The mission addresses two interaction channels: electron recoils from strongly interacting sub-GeV DM and X-rays produced through decaying DM. Orbital observations avoid attenuation that limits ground-based measurements, extending sensitivity reach for both channels. The mission proceeds toward launch following laboratory validation of the instrument. A launch opportunity has been secured through Firefly Aerospace's DREAM 2.0 program, awarded to the University of Illinois Urbana-Champaign (UIUC). This will constitute the first use of skipper-CCDs in space and evaluate their suitability for low-noise X-ray and single-photon detection in future space observatories.

Alpine, Phoenix [Illinois U., Urbana (main)] (ORCI↗
DOE OSTI2025

DarkNESS: A skipper-CCD nanosatellite for dark matter searches

The Dark matter Nanosatellite Equipped with Skipper Sensors (DarkNESS) deploys a recently developed skipper-CCD architecture with sub-electron readout noise in low Earth orbit (LEO) to investigate potential signatures of dark matter (DM). The mission addresses two interaction channels: electron recoils from strongly interacting sub-GeV DM and X-rays produced through decaying DM. Orbital observations avoid attenuation that limits ground-based measurements, extending sensitivity reach for both channels. The mission proceeds toward launch following laboratory validation of the instrument. A launch opportunity has been secured through Firefly Aerospace’s DREAM 2.0 program, awarded to the University of Illinois Urbana-Champaign (UIUC). As a result, this will constitute the first use of skipper-CCDs in space and evaluate their suitability for low-noise X-ray and single-photon detection in future space observatories.

Alpine, Phoenix [University of Illinois, Urbana-Ch↗
DOE OSTI2025

In‐situ Analysis of Paste Properties in Resonant Acoustic Mixers for Quality Monitoring

Formulation control is key to achieving consistent target properties of energetic materials, as feedstock variations and slight deviations in the ratios of different ingredients can have major effects on final product properties, particularly in dense pastes with high particle loading >65 vol.%. In large‐scale operations, it is imperative to either correct or remove batches of material that perform outside baseline property specifications as early as possible to avoid unnecessary processing of suboptimal material. Quality monitoring is the practice of measuring material properties during processing using process analytical technologies as opposed to only testing the properties of the final product; it is a key principle in the quality‐by‐design frameworks used for designing formulations and manufacturing processes. Herein, a process analytical technology method for correlating material properties of dense pastes directly after mixing in a Resonant Acoustic Mixer to motor data is developed and used to detect differences in the particle content of dense paste formulations. This method was also capable of detecting variations in powder feedstock properties, such as particle packing efficiency, and is sensitive enough to detect changes of 2 wt.% in the total solids content of the formulation. The techniques presented herein show excellent promise for use as a process analytical technology capable of quantifying formulation effects on material movement modes during resonant acoustic mixing.

Materials science↗
DOE OSTI2024

Enhancement of the Curie temperature in single-crystalline ferromagnetic LaCrGe 3 by electron irradiation-induced disorder

LaCrGe 3 has attracted attention as a potential candidate for studies of quantum phase transitions in a ferromagnetic material. The application of pressure avoids a quantum critical point by developing a new magnetic phase. It was suggested that the disorder may provide an alternative route to a quantum critical point. We used low-temperature 2.5 MeV electron irradiation to induce relatively small amounts of pointlike disorder in single crystals of LaCrGe 3 . Irradiation leads to an increase of the resistivity at all temperatures with some deviation from the Matthiessen rule. Hall effect measurements show that electron irradiation does not cause any detectable change in the carrier density. Unexpectedly, the Curie temperature, T FM , increases with the increase of disorder from approximately 90 K in pristine samples up to nearly 100 K in the heavily irradiated sample, with a tendency towards saturation at higher doses. This effect is observed both in resistivity and magnetization measurements. Although the mechanism of this effect is not entirely clear, we conclude that it cannot be caused by effective “doping” or “pressure” due to electron irradiation. Finally, we suggest that disorder-induced broadening of a sharp peak in the density of states, D⁡(E), situated at E p = E F – 0.25 eV below the Fermi energy, E F , causes an increase in D⁡(E F ), leading to an enhancement of T FM in this itinerant ferromagnet.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Techno-economic assessment of emissions mitigation technologies for post-combustion CO2 capture using AMP/PZ

Minimizing the environmental impacts of amine-based post-combustion carbon capture technologies is essential for meeting environmental permitting regulations and ensuring public acceptance. Experimental test campaigns at the CO₂ capture pilot plant in Niederaussem using CESAR1 demonstrated that integrating available emission abatement technologies can significantly reduce the concentration of amines and degradation products in CO₂-depleted flue gas to below the detection limit of an infrared spectrometer. The study confirmed that proprietary dry bed technology (OEASE Aerozone™) or a second water wash can lower AMP and PZ emissions to below 1 mg/Nm³. However, to achieve very low NH₃ emissions below 2 mg/Nm³, an acid or other chemically active wash downstream of the water wash is required. A configuration with a dry bed or a double water wash results in a carbon capture cost (CCC) of 44 €/tCO₂, and a CO₂ avoided cost (CAC) of 86 €/tCO₂. A configuration with an acid wash increases the CCC to 47 €/tCO₂ and the CAC to 90 €/tCO₂ due to the amine losses in the acid waste and its treatment.

CO2 capture↗
DOE OSTI2025

Investigation into Scalable and Detection-Enhanced Satellite Conjunction Assessment

Imaging opportunities (viewable conjunctions) of Resident Space Objects (RSOs) by satellites are not continuously discovered. We propose to continuously produce and report viewable conjunctions among objects in orbit. Viewable conjunctions are events in space and time when a satellite may favorably view a Resident Space Object (RSO). Favorability is defined by a set of constraints, e.g., solar illumination, distance between observer and target, orbital location for viewable event. Computing viewable conjunctions requires calculation of orbital propagation while considering constraints based on the state vectors of position, velocity, with covariance for both satellite and RSO. We propose two parallel lanes of effort: acceleration and research. The objective of acceleration is to avoid missed opportunities and reduce latency for satellite maneuver requests through continuous prediction and reporting of viewable conjunctions. The effort will begin by deploying currently available software on dedicated systems and continue with optimizing the code for high performance computing hardware. The research lane aims to expand RSO inspection and modeling capabilities. Among our current research ideas are spectral characterization of RSO materials and planning multiple observations to recover RSO 3D form. Computing resources at Oak Ridge National Laboratory (ORNL) are available for the acceleration work. Laika, Maxar conjunction prediction dashboard software, and Bluesim, Maxar orbital propagation software, are expected to be the first software in the acceleration lane. Laike and Bluesim are to be provided by the sponsor, and output will be made accessible through its dashboard. Deliverables will follow a gated schedule to the sponsor. ORNL will provide progressively more robust viewable conjunction assessments from both modelled and actual ephemerides.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Addressing Issues with Working Memory in Video Object Segmentation

Contemporary state-of-the-art video object segmentation (VOS) models compare incoming unannotated images to a history of image-mask relations via affinity or cross-attention to predict object masks. We refer to the internal memory state of the initial image-mask pair and past image-masks as a working memory buffer. While the current state of the art models perform very well on clean video data, their reliance on a working memory of previous frames leaves room for error. Affinity-based algorithms include the inductive bias that there is temporal continuity between consecutive frames. To account for inconsistent camera views of the desired object, working memory models need an algorithmic modification that regulates the memory updates and avoid writing irrelevant frames into working memory. A simple algorithmic change is proposed that can be applied to any existing working memory-based VOS model to improve performance on inconsistent views, such as sudden camera cuts, frame interjections, and extreme context changes. The resulting model performances show significant improvement on video data with these frame interjections over the same model without the algorithmic addition. Our contribution is a simple decision function that determines whether working memory should be updated based on the detection of sudden, extreme changes and the assumption that the object is no longer in frame. By implementing algorithmic changes, such as this, we can increase the real-world applicability of current VOS models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Adaptive Fault Current-Limiting Control of MMC for Protection of Multiterminal HVDC Systems

A crucial requirement of the protection system for multi-terminal high-voltage DC (MTDC) transmission is that it is capable of selectively isolating the faulty area from the healthy part of the network using DC circuit breakers (DCCBs), while ensuring continuous operation of converter stations in the healthy part of the network. But in the half-bridge modular multilevel converters (HB-MMCs) based MTDC system, since HB-MMCs do not have fault current absorption capability, when a DC fault occurs, the rising fault currents can quickly reach the blocking threshold within a few milliseconds and disrupt the operation of the MMCs in the healthy part. To facilitate fault-ride-through capability of MTDC system, large DC reactors are often considered in series with DCCBs to reduce the rate of rise of the fault current and prevent blocking the MMCs in the healthy part of the DC networks; however, large DC reactors prohibitively increase the cost of the system, introduce stability issues and can create post-fault oscillations. This paper presents an adaptive fault current-limiting control method for MMCs to avoid their blocking and enable the continuous operation of the healthy part of MTDC systems. The method contains two parts: The first part is based on circulating current feedforward control, which emulates virtual reactors in each arm of an MMC, and is immediately activated when the fault current starts to increase to reduce the rate of rise of the fault current. The second part temporarily bypasses all the submodules when the fault current exceeds a preset threshold, complementing the fault current-limiting effect of the first part. Neither part requires fault detection signals, and they are automatically activated during faults. Simulation case studies of a four-terminal bipolar MMC-based high-voltage DC system are presented to demonstrate the effectiveness of the proposed control methods.

active fault current limiting↗
DOE OSTI2024

Adaptive Fault Current-Limiting Control of MMC for Protection of Multiterminal HVDC Systems: Preprint

For the development of multi-terminal high voltage DC (MTDC) transmission, it is critical to design the protection system that can selectively isolate the faulty area from the healthy part of the dc grid using DC circuit breakers (DCCBs) while ensuring continuous operation of converter stations in the healthy part. However, because of the lack of fault current blocking capability in half-bridge (HB) modular multilevel converters (MMCs), when a dc fault occurs, the rising fault currents can quickly reach the blocking threshold within a few milliseconds and disrupt the operation of MMCs in the healthy part. Large DC reactors are often considered in series with DCCBs to reduce the rate of rise of fault currents and prevent blocking of MMCs in the healthy part of the grid. However, large DC reactors can prohibitively increase the cost of the system, particularly when they are considered in an offshore environment, for instance in offshore wind projects. Large dc reactors can also introduce stability issues and create post-fault oscillations. This paper presents an adaptive fault current limiting control method for MMCs to avoid their blocking and enable continuous operation of MTDC systems. It contains two parts: The first part is based on circulating current feedforward control that emulates virtual reactors in each arm of an MMC, which is immediately activated when the fault current starts to increase, to reduce the rate of rise of the fault current; the second part is triggered when the fault current exceeds a preset threshold by temporarily bypassing the SMs, serving as a complement to the fault current limiting effect of the first part. Both parts do not require fault detection signal and they are activated automatically during faults. Simulation case studies of a four-terminal bipolar MMC-HVDC system are presented to demonstrate the effectiveness of the proposed control methods.

active fault current limiting↗
DOE OSTI2025

Experimental targets for dark photon dark matter

Ultralight dark photon dark matter features distinctive cosmological and astrophysical signatures and is also supported by a burgeoning direct-detection program searching for its kinetic mixing with the ordinary photon over a wide mass range. Dark photons, however, cannot necessarily constitute the dark matter in all of this parameter space. In minimal models where the dark photon mass arises from a dark Higgs mechanism, early-Universe dynamics can easily breach the regime of validity of the low-energy effective theory for a massive vector field. In the process, the dark sector can collapse into a cosmic string network, precluding dark photons as viable dark matter. We establish the general conditions under which dark photon production avoids significant backreaction on the dark Higgs and identify regions of parameter space that naturally circumvent these constraints. After surveying implications for known dark photon production mechanisms, we propose novel models that set well-motivated experimental targets across much of the accessible parameter space. We also discuss complementary cosmological and astrophysical signatures that can probe the dark sector physics responsible for dark photon production.

Dark matter↗
DOE OSTI2024

Utilizing HYSPLIT for Emergency Response Modeling at SRS

At SRS, emergency responders use a variety of tools to detect, track, and mitigate hazardous material releases into the atmosphere. Two models currently used at SRS are Puff-Plume and the Lagrangian Particle Dispersion Model (LPDM), a Gaussian and Lagrangian model, respectively. A decision has been made to replace LPDM with the more widely-supported Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model for evaluating inhalation and ingestion doses following a release. HYSPLIT is designed to compute complex dispersion and deposition simulation To achieve the implementation of HYSPLIT, we have developed a preliminary UI framework that will allow HYSPLIT to be run on ATG computers without the need for active network connections, thus avoiding the loss of capabilities in the event of a network outage during an emergency.

Earley, Ian↗