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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Glycolate Analysis in Tank 22: Developing and Testing Analytical Methods for the Savannah River Site Liquid Waste System

Researchers developed and tested a range of techniques to support a low mg/L Limit of Quantitation (LOQ) of glycolate in radioactive Tank 22 waste solution by Ion Chromatography (IC) and by proton NMR. For the IC method, Dionex OnGuard II cartridges were tested as a means of removing alkali earth and transition metals that can interfere during ion chromatography applications especially when analyzing for low-concentration, chelating analytes. Additionally, concentrations of nitrate in the raw Tank 22 sample (5,000 to 10,000 mg/L) were managed by using reasonable levels of sample dilution. The resulting IC performance quality was enhanced by improving the baseline, increasing sensitivity [Limit of Quantitation (LOQ) of 12 mg/L and Limit of Detection (LOD) of 4.0 mg/L], and resolving analytes into well-defined Gaussian peaks when using the Dionex OnGuard II H⁺ cartridges to remove matrix interferences. High concentrations of nitrate limited the performance of the IC method. To achieve an acceptable baseline, samples with high nitrate content require more dilution, resulting in higher detection limits. Tests on samples with higher concentrations of nitrate (Tank 30 and 32 supernate with approximately 150000 mg/L nitrate) suggested that IC detection limits for glycolate in these samples would be > 500 mg/L. Thus, an LOQ of 12 mg/L is not feasible by this IC method on evaporator feed samples. An alternative method of glycolate analysis, using proton nuclear magnetic resonance (H NMR), was developed by the research team. In initial tests, the H NMR technique provided reasonable quantitation of glycolate in Tank 22 conditions by direct observation of the liquid. The H NMR method may provide improved detection limits for solutions with higher nitrate concentrations. We recommend further development of this analysis for high nitrate LWS samples such as evaporator feed and evaporator drop tank content. A method for pretreatment of samples using crystalline silicotitanate (CST) was developed and tested. The objective of the pretreatment was to facilitate analysis of samples with higher levels of radioactivity. The pretreatment did not influence the glycolate concentration in solution, and the pretreatment is projected to reduce Cs 137 activity in a sample by a factor of 16,200. The double strike CST pretreatment was demonstrated and would allow milliliters of higher activity samples to be transferred from the Shielded Cells and handled in a containment unit for glycolate analysis. The various studies validated IC and H NMR methods for glycolate analysis, defined the range of applicability, and demonstrated key supporting analytical protocols. Based on the results, high quality glycolate analysis of Tank 22 is feasible down to approximately 12 mg/L, with the potential for broader applicability of the methods to other conditions in the Savannah River Site Liquid Waste System (LWS).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Combining quantum noise reduction resources: A practical approach

Optomechanical sensors are capable of transducing external perturbations to resolvable optical signals. A particular regime of interest is that of high-bandwidth force detection, where an impulse is delivered to the system over a short period of time. Exceedingly sensitive impulse detection has been proposed to observe very weak signals like those due to long-range interactions with dark matter that require much higher sensitivities than current sensors can provide. Quantum resources to go beyond the traditional standard quantum limit of these sensors include squeezing of the light used to transduce the signal, backaction evasion by measuring the optimal quadrature, and quantum nondemolition (QND) measurements that reduce backaction directly. These methods have been developed in the context of gravitational wave detection for target frequencies in the audio band range. Here, we provide the theoretical limits to quantum noise reduction for higher and broader frequency targets, such as those from dark matter signals, while combining quantum-enhanced readout techniques based on squeezed light and QND measurements with optomechanical sensors. Here, we demonstrate that backaction evasion through QND techniques dramatically reduces the technical challenges presented when using squeezed light for broadband force detection, paving the way for combining multiple quantum noise reduction techniques for enhanced sensitivity in the context of impulse metrology.

Optomechanics↗
DOE OSTI2024

Phase-resolving spin-wave microscopy using infrared strobe light

The need for sensitively and reliably probing magnetization dynamics has been increasing in various contexts such as studying novel hybrid magnonic systems, in which the spin dynamics strongly and coherently couple to other excitations, including microwave photons, light photons, or phonons. Recent advances in quantum magnonics also highlight the need for employing the magnon phase as quantum state variable, which is to be detected and mapped out with high precision in on-chip micro- and nanoscale magnonic devices. Here, in this study, we demonstrate a facile optical technique that can directly perform concurrent spectroscopic and imaging functionalities with spatial and phase resolutions, using infrared strobe light operating at 1550-nm wavelength. To showcase the methodology, we spectroscopically studied the phaseresolved spin dynamics in a bilayer of Permalloy and yttrium iron garnet Y 3 Fe 5 O 12 (YIG), and spatially imaged the backward-volume spin-wave modes of YIG in the dipolar spin-wave regime. Using the strobe light probe, the detected precessional phase contrast can be directly used to construct the map of the spin wave's wave front, in the continuous-wave regime of spin-wave propagation and in the stationary state, without needing any optical reference path. By selecting the applied field, frequency, and detection phase, the spin-wave images can be made sensitive to the precession amplitude and phase. Our results demonstrate that infrared optical strobe light can serve as a versatile platform for magneto-optical probing of magnetization dynamics, with potential implications in investigating hybrid magnonic systems.

Xiong, Yuzan [University of North Carolina, Chapel↗
DOE OSTI2024

Assessing Resilience in Lane Detection Methods: Infrastructure-Based Sensors and Traditional Approaches for Autonomous Vehicles

Traditional autonomous vehicle perception subsystems that use onboard sensors have the drawbacks of high computational load and data duplication. Infrastructure-based sensors, which can provide high quality information without the computational burden and data duplication, are an alternative to traditional autonomous vehicle perception subsystems. However, these technologies are still in the early stages of development and have not been extensively evaluated for lane detection system performance. Therefore, there is a lack of quantitative data on their performance relative to traditional perception methods, especially during hazardous scenarios, such as lane line occlusion, sensor failure, and environmental obstructions. We address this need by evaluating the influence of hazards on the resilience of three different lane detection methods in simulation: (1) traditional camera detection using a U-Net algorithm, (2) radar detections using infrastructure-based radar retro-reflectors (RRs), and (3) direct communication of lane line information using chip-enabled raised pavement markers (CERPMs). The performance of each of these methods is assessed using resilience engineering metrics by simulating the individual methods for each sensor technology’s response to related hazards in the CARLA simulator. Using simulation techniques to replicate these methods and hazards acquires extensive datasets without lengthy time investments. Specifically, the resilience triangle was used to quantitatively measure the resilience of the lane detection system to obtain unique insights into each of the three lane detection methods; notably the infrastructure-based CERPMs and RRs had high resistance to hazards and were not as easily affected as the vision-based U-Net. However, while U-Net was able to recover the fastest from the disruption as compared to the other two methods, it also had the most performance loss. Overall, this study demonstrates that while infrastructure-based lane keeping technologies are still in early development, they have great potential as alternatives to traditional ones.

Patil, Pritesh↗
DOE OSTI2025

High-frequency gravitational wave detection by the BREAD experiment

The use of experiments searching for light axion dark matter as high-frequency gravitational wave detectors has garnered increasing attention in recent years. We explore the capabilities of the Broadband Reflector Experiment for Axion Detection (BREAD) in probing the GW parameter space and study the directional dependence of its coverage. This detector can investigate frequencies ranging from 0.05 to 200 THz. We find that by employing single photon detectors, BREAD is sensitive to GWs with characteristic strains as low as 10 −21 at 0.1 THz and 10 −25 at 200 THz with a year exposure time, making it competitive with other proposals operating at similar frequencies.

axions↗
DOE OSTI2021

Quantitative Detection of Products and Radical Intermediates in Low-Temperature Oxidation of Cyclopentane

We present a combined experimental and theoretical investigation of the autoignition chemistry of a prototypical cyclic hydrocarbon, cyclopentane. Experiments using a high-pressure photolysis reactor coupled to time-resolved synchrotron VUV photoionization mass spectrometry directly probe the short-lived radical intermediates and products in cyclopentane oxidation reactions. We detect key peroxy radical intermediates ROO and OOQOOH, as well as several hydroperoxides, formed by second O 2 addition. Automated quantum chemical calculations map out the R + O 2 + O 2 reaction channels and demonstrate that the detected intermediates belong to the dominant radical chain-branching pathway: ROO (+ O 2 ) → γ-QOOH + O 2 → γ-OOQOOH → products. ROO, OOQOOH, and hydroperoxide products of second-O 2 addition undergo extensive dissociative ionization, making their experimental assignment challenging. We use photoionization dynamics calculations to aid in their characterization and report the absolute photoionization spectra of isomerically pure ROO and γ-OOQOOH. Here, a global statistical fit of the observed kinetics enables reliable quantification of the time-resolved concentrations of these elusive, yet critical species, paving the way for detailed comparisons with theoretical predictions from master-equation-based models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Performance of Hamamatsu VUV4 SiPMs for detecting liquid argon scintillation

Detection of light signals is crucial to a wide range of particle detectors. In particular, efficient detection of vacuum ultraviolet (VUV) light will provide new opportunities for some novel detectors currently being developed, but is technically challenging. In this paper, we characterized the performance of Hamamatsu VUV4 silicon photomultipliers (SiPMs) for detecting VUV argon scintillation light without wavelength shifting. Using a customized cryogenic amplifier design, we operated two models of VUV4 SiPMs inside liquid argon and thoroughly examined their direct sensitivities to liquid argon scintillation. In addition to describing their cryogenic performance, we measured a photon detection efficiency of 14.7 +1.1 -2.4 % and 17.2 +1.6 -3.0 % at 128 nm for these two VUV4 models for operation at 4 V of overvoltage, with the main uncertainty arising from the SiPM reflectivity for VUV light.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Characterization of Hamamatsu VUV4 SiPM Performance for Liquid Argon Scintillation

Detection of light signals is crucial to a wide range of particle detectors. In particular, efficient detection of vacuum ultraviolet (VUV) light will provide new opportunities for some novel detectors currently being developed, but is technically challenging. In this article, we characterized the performance of Hamamatsu VUV4 silicon photomultipliers (SiPMs) for detecting VUV argon scintillation light without wavelength shifting. Here, using a customized cryogenic amplifier design, we operated two models of VUV4 SiPMs inside liquid argon and thoroughly examined their direct sensitivities to liquid argon scintillation. In addition to describing their cryogenic performance, we measured a photon detection efficiency of 14.7+1.1–2.4% and 17.2+1.6–3.0% at 128 nm for these two VUV4 models for operation at 4 V of overvoltage, with the main uncertainty arising from the SiPM reflectivity for VUV light.

Pershing, Teal↗
DOE OSTI2025

Integrating Machine-learning-assisted Computer Vision with RICH System

Developments in artificial intelligence have vastly expanded the capabilities of robots. Currently, the Spallation Neutron Source (SNS) beamlines at Oak Ridge National Lab (ORNL) have robotic sample loaders to increase the efficiency of running experiments. However, they require retraining if anything about the situation changes, e.g., where the samples are, and cannot notice if errors occur. So, the viability of using computer vision and machine learning to enhance these sample loaders’ functionality was investigated. In this project, the RICH system with a Dobot CR3 6-axis robot present at the VULCAN beamline assisted by an Intel Realsense D435i camera, a unique camera that enables convenient translation of 2D pixel coordinates to 3D world points, was programmed to load ceramic crucibles into a thermogravimetric analyzer (TGA) furnace. An algorithm was constructed in Python with three major phases planned: (1) obtaining a sample, (2) moving it to the target location, and then (3) bringing the sample back to its original location once the experiment finished. In the first phase, the algorithm would dynamically detect sample locations using ArUco markers to recognize the samples’ general location and a custom-trained yolov5 object detection model to locate the crucibles’ centers. Afterward, the robot would be directed to pick up samples based on the crucibles’ calculated positions. In the second phase, the robot would move the sample to a secondary point, reorient its grip, and place the sample at the target location. In the final phase, the robot would determine whether the sample was intact and would bring it back to its original place if it was or raise an alarm. Using this algorithm, the robot was able to pick up different types of crucibles at varying positions. These results indicate that integrating machine-learning-assisted computer vision with robotic sample loaders can result in effective autonomous detection of samples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Directional response of several geometries for reactor-neutrino detectors

Here we have modeled six abstracted detector designs, with the goal of determining their ability to resolve the direction to an antineutrino source, including two for which we have operational data for validating our computer modeling and analytical processes. We have found that the most promising options, regardless of scale and range, have angular resolutions on the order of a few degrees, which is better than any yet achieved in practice by a factor of at least two. We examine and compare several approaches to detector geometry for their ability not only to detect the inverse beta decay (IBD) reaction, but also to determine the source direction of incident antineutrinos. The information from these detectors provides insight into reactor power and burning profile, which is especially useful in constraining the clandestine production of weapons material. In a live deployment, a nonproliferation detector must be able to isolate the subject reactor, possibly from a field of much-larger power reactors; directional sensitivity can help greatly with this task. We also discuss implications for using such detectors in longer-distance observation of reactors, from a few kilometers to hundreds of kilometers.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Robust anomaly detection for particle physics using multi-background representation learning

Abstract Anomaly, or out-of-distribution, detection is a promising tool for aiding discoveries of new particles or processes in particle physics. In this work, we identify and address two overlooked opportunities to improve anomaly detection (AD) for high-energy physics. First, rather than train a generative model on the single most dominant background process, we build detection algorithms using representation learning from multiple background types, thus taking advantage of more information to improve estimation of what is relevant for detection. Second, we generalize decorrelation to the multi-background setting, thus directly enforcing a more complete definition of robustness for AD. We demonstrate the benefit of the proposed robust multi-background AD algorithms on a high-dimensional dataset of particle decays at the Large Hadron Collider.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Emerging anomaly detection techniques for electronic health records: A survey

Background Anomaly detection in electronic health records (EHRs) is a cornerstone of biomedical informatics, with direct implications for patient safety, clinical decision-making, and the prevention of healthcare fraud. Once guided primarily by simple rule-based methods, the field has advanced rapidly, driven by increased computing power, richer and more detailed health data, and the rise of machine learning and deep learning techniques. The objective of this paper is to provide a comprehensive overview of modern approaches to detecting anomalies in EHRs, outlining their strengths, limitations, and relevance to key healthcare challenges. We review traditional statistical methods alongside newer ML- and DL-based strategies and hybrid models, with particular attention to how these techniques support transparency and build clinical trust. Methods This paper presents a thorough and critical survey through systematic review (PRISMA-based) of the latest anomaly detection strategies in time-sequence data domains within electronic health record systems. Results We explore a broad spectrum of methodologies, including statistical models, supervised and unsupervised learning approaches, hybrid frameworks, and state-of-the-art ML-based techniques that collectively advance the precision and scalability of detecting anomalies in complex clinical datasets. In addition to mapping current capabilities, we address the enduring challenges that hinder widespread implementation and provide a forward-looking perspective on the future of anomaly detection in the data-rich landscape of modern healthcare. Summary The advancement in AI-based approaches is reported along with the basic principles of the individual approaches and their applicability. The increased availability of high-quality data, advancements in DL approaches, and enhanced computation power are leading to more frequent adaptation of DL-based approaches. Emerging DL-based approaches that have been adapted in other domains or recently applied in the EHR domain are also discussed in detail. Although DL-based approaches can improve model predictions by incorporating comorbidities, their application is limited in low-frequency data domains (e.g., when the total available data remains in the single digits). Therefore, the user must carefully consider the application based on data availability.

Anomaly detection↗
DOE OSTI2025

IoT Firmware Emulation and Its Security Application in Fuzzing: A Critical Revisit

As IoT devices with microcontroller (MCU)-based firmware become more common in our lives, memory corruption vulnerabilities in their firmware are increasingly targeted by adversaries. Fuzzing is a powerful method for detecting these vulnerabilities, but it poses unique challenges when applied to IoT devices. Direct fuzzing on these devices is inefficient, and recent efforts have shifted towards creating emulation environments for dynamic firmware testing. However, unlike traditional software, firmware interactions with peripherals that are significantly more diverse presents new challenges for achieving scalable full-system emulation and effective fuzzing. This paper reviews 27 state-of-the-art works in MCU-based firmware emulation and its applications in fuzzing. Instead of classifying existing techniques based on their capabilities and features, we first identify the fundamental challenges faced by firmware emulation and fuzzing. We then revisit recent studies, organizing them according to the specific challenges they address, and discussing how each specific challenge is addressed. We compare the emulation fidelity and bug detection capabilities of various techniques to clearly demonstrate their strengths and weaknesses, aiding users in selecting or combining tools to meet their needs. Finally, we highlight the remaining technical gaps and point out important future research directions in firmware emulation and fuzzing.

Zhou, Wei (ORCID:0000000178340839)↗
DOE OSTI2024

Optically induced quantum transitions in direct probed mesoscopic NbSe 2 for prototypical bolometers

Superconducting transition-edge sensors (TES) have emerged as fascinating devices to detect broadband electromagnetic radiation with low thermal noise. The advent of metallic transition metal dichalcogenides, such as NbSe 2 , has also created an impetus to understand their low-temperature properties, including superconductivity. Interestingly, NbSe 2 -based sensor within the TES framework remains unexplored. In this work, direct-probed superconducting NbSe 2 absorbers led to a proof-of-concept demonstration for the transduction of incoming light to heat, where a thermodynamic superconducting phase transition in NbSe 2 was evident to switch it to the normal-state, when biased below its superconducting transition temperature. A wavelength-dependent response of its optical absorption properties was observed, based on the incident optical excitation source used. Furthermore, extensive optical characterization studies were conducted using Raman spectroscopy, where the in-plane and out-of-plane thermal conductivity was empirically determined. Our results open new possibilities for the use of NbSe 2 in superconducting radiation detectors, including in a TES framework

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Challenges in spatial metabolomics and proteomics for functional tissue unit and single-cell resolution

While transcriptomics is the most broadly applied technology for global spatial and single cell measurements in healthy and diseased tissues. Transcripts are often used as a proxy for protein and even metabolite measurements, but it has become commonly accepted that extrapolating this kind of information is a poor proxy and not a substitute for direct measurement. Within the last decade advanced developments of mass spectrometry-based assays have made these direct measurements not only possible, but routine. Where mass spectrometry has become an enabling technology, and various methods can now detect hundreds of metabolites and thousands of proteins from samples. Not only can this be performed within bulk measurements, but much effort has been directed into translating these measurements to single cells and tissues at cellular resolution. The information obtained from mass spectrometry is now able to trace metabolic events and decipher feedback loops across anatomical regions, connecting genetic and metabolic networks that define phenotypes. Herein, we will broadly overview developments in the field over the past decade, leading into several case studies which highlight the direct measurement of metabolites, proteins, and proteoforms from thinly sliced tissues. Much of this work is feasible due to multidisciplinary team science, and we offer brief perspective on paths forward and the challenges that persist with adoption and application of spatial omics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Diol isomer revealed as a source of methyl ketene from propionic acid unimolecular decomposition

Carboxylic acids are important combustion intermediates, especially regarding the combustion of oxygenates such as ethyl esters. The purpose of this study is to discern the unimolecular decomposition pathways of one such carboxylic acid, propionic acid, using microreactor flow experiments with line-tunable photoionization mass spectrometry and infrared spectroscopy, along with high-level electronic structure calculations (CCSD(T)/cc-pV∞Z//M06-2X/cc-pVTZ level of theory) and master equation theory. Here, microreactor experiments were performed at 300–1500 K, pressures decreasing from roughly 300 Torr to vacuum pressure, and around 100 μs residence times. Primary products are methyl ketene, ketene, ethylene, and methyl radical. Theory suggests the two lowest energy bond fissions are active at these conditions and responsible for the production of ketene, methyl radical, and some ethylene. Importantly, theory revealed the significance of the isomerization of propionic acid to propene-1,1-diol, and the subsequent dehydrogenation reaction of the diol as an alternative explanation for the unimolecular formation of methyl ketene. This is predicted to be the dominant thermal decomposition pathway at lower temperatures (up to ~850 K). Line-tunable VUV photons allowed for isomer resolution of the products and showed no evidence of the diol of propionic acid surviving until detection, suggesting propene-1,1-diol decomposes either to methyl ketene and water rapidly, fragments upon ionization to a distonic ion inseparable from methyl ketene through our detection methods, or never stabilizes as propionic acid well-skips directly to methyl ketene. Infrared spectroscopy showed no evidence of the decarboxylation of propionic acid at these conditions. Updated rate constants and branching ratios for propionic acid decomposition are calculated and provided for future modeling studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Millicharged relics reveal massless dark photons

The detection of massless kinetically-mixed dark photons is notoriously difficult, as the effect of this mixing can be removed by a field redefinition in vacuum. In this work, we study the prospect of detecting massless dark photons in the presence of a cosmic relic directly charged under this dark electromagnetism. Such millicharged particles, in the form of dark matter or dark radiation, generate an effective dark photon mass that drives photon-to-dark photon oscillations in the early universe. We also study the prospect for such models to alleviate existing cosmological constraints on massive dark photons, enlarging the motivation for direct tests of this parameter space using precision terrestrial probes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Observation and Numerical Simulation of Cold Ions Energized by EMIC Waves

This is the first report of significant energization (up to 7,000 eV) of low-energy He + ions, which occurred simultaneously with H-band electromagnetic ion cyclotron (EMIC) wave activity, in a direction mostly perpendicular to the ambient magnetic field. The event was detected by the Arase satellite in the dayside plasmatrough region off the magnetic equator on 15 May 2019. The peak energy of the He + flux enhancements is mostly above 1,000 eV. At some interval, the He + ions are energized up to ~7,000 eV. The H-band waves are excited in a frequency band between the local crossover and helium gyrofrequencies and are close to a linear polarization state with weakly left-handed or right-handed polarization. The normal angle of the waves exhibits significant variation between 0° and 80°, indicating a non-parallel propagation. Here, we run a hybrid code with parameters estimated from the Arase observations to examine the He + energization. The simulations show that cold He + ions are energized up to more than 1,000 eV, similar to the spacecraft observations. From the analysis of the simulated wave fields and cold plasma motions, we found that the ratio of the wave frequency to He + gyrofrequency is a primary factor for transverse energization of cold He + ions. As a consequence of the numerical analysis, we suggest that the significant transverse energization of He + ions observed by Arase is attributed to H-band EMIC waves excited near the local helium gyrofrequency.

79 ASTRONOMY AND ASTROPHYSICS↗