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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Magnetic field induced modification of a first-order ferromagnetic transition in Eu 2 ⁢In

Here, we present a comprehensive study of the temperature-and magnetic-field-dependent magnetization, specific heat, and local crystal structure across the first-order ferromagnetic–paramagnetic transition in Eu 2 ⁢In. Anomalies in the magnetocaloric response are observed near 𝐻 ≈ 25 kOe, including changes in field scaling of magnetic entropy, local entropy exponent, and universal master curve, which suggest an apparent weakening of the first-order character of the transition. However, quantitative analysis of the magnetocaloric parameters together with modified Arrott plots demonstrates that the transition remains first order up to at least 70 kOe. Specific-heat measurements reveal a field-induced splitting of the sharp zero-field anomaly into a doublet, providing a natural explanation for the change in the magnetocaloric response. Magnetic-field-dependent extended x-ray absorption fine structure (EXAFS) measurements show no detectable field-induced changes in the local coordination environment of Eu. We therefore attribute these observations to a magnetic-field-induced two-step transition process in Eu 2 ⁢In.

Kumar, Ajay [Ames Laboratory (AMES), Ames, IA (Uni↗
DOE OSTI2025

Automated Scoring of Morphological Changes in Images of Pentaerythritol Tetranitrate

Recent advances in characterization techniques that generate large datasets of material microstructure images require robust, automated image-processing. We applied an unsupervised anomaly detection method called feature anomaly detection system (FADS) to automatically detect and quantify microstructure changes in images of the explosive pentaerythritol tetranitrate (PETN) aged at various temperatures. We demonstrated the FADS approach on two-dimensional images extracted from computed tomography scans, but the same technique can be readily applied to other imaging modalities. FADS calculates anomaly scores on the basis of differences in filter activations of nominal and test data in pretrained convolutional neural networks. The FADS scores successfully differentiated between pristine PETN and PETN aged at a temperature where material coarsening occurred. Morphological metric analysis of segmented images verified observed trends in FADS scores as a function of aging temperature and aging time, specifically by calculating volume fractions, specific boundary lengths, two-point correlation functions, and local thicknesses. Here, the FADS technique has two important advantages compared to traditional morphological analysis: First, it uses grayscale images as input, rather than images that are segmented to separate the appropriate phases; and second, FADS scores capture any type of changes among image sets, rather than requiring prior knowledge or selection of a relevant set of metrics.

Accelerated aging↗
DOE OSTI2024

Elastic Changepoint Detection for Globally-indexed Functional Time Series Data with Climate Applications

Changepoint detection is a vital tool in the application of climate data analysis. Numerous types of climate observation data are most properly represented by functional time series, implying a need for accurate changepoint detection methods applicable to functional time series data. Such data taken at a global scale often contain both spatial heterogeneity and dependence as well as phase (time) misalignment. In this report, we present methods which can detect spatially-dependent changepoints while allowing different estimates of change time and change strength depending on location. Additionally, we provide extensions to this spatially-predicted model which controls for phase variability among observations. Our methods provide the ability to detect a single change, or control for epidemic changes (where a “return-to-normal” change is more likely to be detected than the initial change). We showcase results analyzing the June 1991 eruption of Mt. Pinatubo, where our methods demonstrate the ability to accurately detect both single and epidemic changepoints even in the presence of strong seasonal variability. We find that our spatially-predicted model improves the detection of relevant changepoints versus methods which do not take spatial information into account, and we find that controlling for phase variability helps to control the false discovery rate during the detection process.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Arctic Ocean Hydroacoustics

As the Arctic warms and loses its perennial ice cover, it is becoming more attractive for a variety of human uses. Hydroacoustic monitoring of this activity will grow in importance over the coming years and decades. Changes to the physical environment affect acoustic propagation and noise, with ramifications for our ability to detect and locate events and activities of interest. In this report, we use two long-term data sets from the Beaufort Sea, western Arctic Ocean, to determine how acoustic propagation conditions and seismic source detections are impacted by the changing environment: 1) oceanographic observations from ice-tethered profilers, and 2) passive acoustic recordings from a hydrophone. We find that changes to Beaufort Sea thermohaline stratification is stabilizing a subsurface duct, leading to more focused acoustic energy arrivals. Detections of catalogued submarine earthquakes show geographic differences in signal strength between seismic and acoustic waves. Signal strength increases with earthquake magnitude, but relationships to other source and path factors are less clear. Ambient noise also has clear seasonal patterns in the Arctic, with relatively low noise in the spring, higher noise near 1 Hz in summer, and higher noise near 10 Hz in winter. Climate change is expected to modify these seasonal noise patterns, impacting event detection. Future work will further investigate the mechanisms of ice effects on sound and couple acoustic modeling to an Earth System Model.

54 ENVIRONMENTAL SCIENCES↗
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

Experimental investigation of the influence of drainage condition on change in saturation of sheared sand

Here, this paper investigates the validity of the interpretation of results from testing saturated axisymmetric triaxial compression (ATC) sand specimens utilising three-dimensional (3D) synchrotron micro-computed tomography (SMT) to probe localised events that are completely missed or misinterpreted when analysing ATC measurements based on global standard measurements. Drained and undrained experiments were conducted at low and high back-pressures (BPs) coupled with multiple in situ 3D SMT to acquire high-resolution scans of the specimens at different axial strains. Specimens tested under low BP exhibited a large pore air volume change, which was not detected by the pump system that represents standard volume measurement. The increase in air volume caused a significant reduction in the degree of saturation leading to a possible transition from saturated to partially saturated constitutive behaviour. Undrained experiments exhibited a significant volume change contrary to the assumption of negligible volumetric strain for saturated undrained experiments. Air bubbles within the shear band for drained and undrained low-BP specimens showed opposite capillary pressure responses, increased for drained and decreased for undrained cases, due to the variation in the mechanism by which each of the two experiments predominantly counters the volume expansion within the shear band.

capillary pressure↗
DOE OSTI2026

Surface and Buried Thermal, and RGB Unexploded Ordnance Data Collection

This document provides a description of a data collection campaign of unexploded ordnance (UXOI) set. The dataset captures a controlled UAV imaging campaign designed to support detection of UXO across varied environmental conditions. Data were collected during three campaigns in Norris and Northeast Knoxville, Tennessee, using RGB, and thermal sensors mounted on Parrot UKR. In total, the dataset contains 9925 images, 26 full-motion video, and approximately 81.99 GB of data, collected across late spring/summer conditions, every hour during sunlight, and multiple surface contexts, including tall grass, short grass, gravel, as well as buried in sand, and other gravel mixtures. The collection was designed to capture thermal and visual variability relevant to UXO detection in agricultural land, bare earth, and subsurface. Review of the imagery showed that ordnance was most detectable during periods of changing solar input, especially approximately 10-60 minutes after sunrise, approximately 20-60 minutes after sunset, and 2-3 min after cloud cover interrupted prolonged solar heating. These conditions increased thermal contrast because many ordnance items retained or released heat differently than the surrounding vegetation and ground surface. This dataset provides a useful resource for developing and evaluating airborne UXO detection methods under realistic field conditions. All ordnance used in the study was inert, and thermal behavior may differ from that of live ordnance. In addition, variation in ordnance type, composition, and placement introduced differences in thermal response that should be considered when interpreting results.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2025

A tale of two towers: comparing NEON and AmeriFlux data streams at Bartlett Experimental Forest

Long-term ecological data are essential for detecting impacts of climate change and other global change factors, and for making informed predictions about future change. However, long-term measurements are rarely replicated at the site level, which raises questions about their representativeness. We used a multiscale approach to evaluate the agreement of parallel observations from AmeriFlux and NEON (National Ecological Observatory Network) towers at Bartlett Experimental Forest, New Hampshire, USA. The two towers are separated by a horizontal distance of 93 m. Here, we focused our analysis on standard meteorological variables; fluxes of CO 2 , sensible heat, and latent heat measured by eddy covariance; and phenology derived from PhenoCam imagery. Results suggest excellent agreement between AmeriFlux and NEON in meteorology and phenology, and good agreement in fluxes at the half-hourly scale. However, large disagreements in CO 2 and latent heat fluxes occurred at the annual scale, with implications especially for the forest carbon balance. The AmeriFlux tower measurements indicate a site that is close to carbon-neutral (-8 ± 65 g C m -2 y -1 , mean ± 1 SD), whereas the NEON tower measurements indicate a forest that is a carbon sink (-137 ± 10 g C m -2 y -1 ). Causes of this disagreement may include measurement height (26 m vs. 35 m), which resulted in different flux footprints being measured by the two towers, and differences in the flux measurement systems. Our results suggest the need for caution when attempting to merge long-term flux data from two different measurement platforms, and when using measurements from any one measurement platform to inform decision-making on issues related to carbon accounting or natural climate solutions.

Carbon cycle↗
DOE OSTI2025

Preliminary studies on diversion and misuse for TRISO-fueled heat-pipe-cooled microreactors

Microreactors are being developed by multiple reactor designers to mass-produce nuclear facilities for worldwide deployment. Including microreactors in a country’s energy portfolio introduces new concerns for international safeguards regarding the number of reactor locations. Microreactors have smaller quantities of nuclear material compared to current light-water reactors, which makes diverting enough material for clandestine purposes difficult for a single reactor. Diversion or misuse of multiple microreactors to obtain a significant quantity introduces a new acquisition pathway. This work examines diversion and misuse scenarios for a realistic heat-pipe-cooled microreactor to understand how these scenarios would effect reactor operations to determine if monitoring key parameters could reduce the burden of inspection on monitoring agencies. Here, we determined misuse caused too drastic of an effect on core operations to be a valid acquisition pathway for the realistic heat-pipe-cooled microreactor. Diversion was explored across varying levels of severity, where potential diversion scenarios could yield one significant quantity of material from between six and eleven microreactors. Through examining the critical control drum angle, excess reactivity, control drum worth, and power distribution changes from nominal were detected over the operational lifetime, which could indicate a divergence from normal operations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Correlation of Surface Acoustic Wave (SAW) force myography sensor output with elbow joint torque

Accurate assessment of skeletal muscle forces and net joint torque is essential for preventing fatigue-related injuries, optimizing physical training, and monitoring disease progression in neuromuscular conditions. However, existing joint torque evaluation techniques are hindered by limited portability and high operational costs, confining their use to controlled laboratory or clinical settings. Despite substantial advances in wearable joint torque estimation systems, ongoing challenges such as power constraints, bulky wired setups, and susceptibility to environmental or motion artifacts underscore the urgent need for truly batteryless, wireless solutions deployable in real-world settings. This paper proposes a novel surface acoustic wave (SAW)-based force myography (FMG) system for noninvasive measurement of joint torque, validated against a gold-standard electromechanical dynamometer. The approach uses a single SAW sensor embedded in an armband to detect volumetric biceps brachii changes, with a second-order polynomial mapping sensor output and elbow angle to torque. Seven participants were tested in both isometric (15°–90°) and isokinetic (10°/s and 20°/s) supinated elbow flexion tasks. Under isometric conditions, subject-specific calibration achieved a normalized root-mean-square error (NRMSE) of 13.6% ± 6.0% and R 2 = 0.834 ± 0.180, while a group-level model yielded 14.4% ± 6.8% and 0.808 ± 0.208, respectively. For isokinetic trials, the group model produced an NRMSE of 24.1% ± 6.6% at 10°/s and 24.9% ± 08.9% at 20°/s, highlighting the feasibility of using a single-sensor SAW-FMG setup across different speeds. Because SAW devices support wireless, battery-free operation, the proposed system offers a pathway to portable, real-time monitoring for sports medicine, rehabilitation, and clinical diagnostics.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Theoretical Study of High Harmonic Generation in Monolayer NbSe 2

High harmonic generation (HHG) is a powerful probe of electron dynamics on attosecond to femtosecond time scales and has been successfully used to detect electronic and structural changes in solid-state quantum materials, including transition-metal dichalcogenides (TMDs). Among TMDs, bulk NbSe 2 exhibits charge density wave (CDW) order below 33 K and becomes superconducting below 7.3 K. Monolayer NbSe 2 also has superconducting and CDW behavior and is therefore interesting as a material whose different structural and electronic properties could be probed via HHG. Here, we predict the HHG response of the pristine 2H and CDW phases of monolayer NbSe 2 using real-time time-dependent density functional theory under the application of a simulated laser pulse excitation. We find that due to the lack of inversion symmetry in both monolayer phases, it is possible to excite even harmonics and that the even harmonics appear as the transverse components of the current response under excitations polarized along the zigzag direction of the monolayer, while odd harmonics arise from the longitudinal current response in all excitation directions. This suggests that the even and odd harmonic responses can be controlled via the polarization of the probing field, opening an avenue for potentially useful applications in optoelectronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Pilot-Scale Validation of Distributed Optical Fiber Sensors for Underground Pipeline Monitoring

Monitoring parameters such as hoop strain, pressure, and acoustic vibrations is key to detecting potential leaks, intrusions, or structural issues. Distributed optical fiber sensor (DOFS) systems provide a compelling solution for continuous, real-time monitoring over long distances. This paper details the development and pilot-scale implementation of DOFS systems for underground pipeline monitoring, evolving from a proof-of-concept stage. Multiple custom-designed DOFS interrogator units—such as optical frequency-domain reflectometry (OFDR), Brillouin optical time-domain analysis (BOTDA), and multimodal interferometer-based fiber acoustic sensor systems were tested to measure the key parameters, such as hoop strain, pipe pressure, surrounding soil temperature, and acoustic vibrations. The underground product pipeline’s outer diameter is 30 inches, the wall thickness is 1.28 inches, and 3 feet deep from the surface. The fiber deployment strategies and sensing data acquisition methods for these systems are discussed. The results demonstrate the effectiveness of DOFS in detecting hoop strain, temperature changes, and acoustic vibrations, showcasing their potential for real-time monitoring and enhancing pipeline safety. These findings from pilot-scale testing offer valuable insights into advancing pipeline monitoring technologies and improving the reliability of underground pipeline systems.

fiber optic sensors↗
DOE OSTI2025

Pilot-Scale Validation of Distributed Optical Fiber Sensors for Underground Pipeline Monitoring

Distributed fiber optic sensing is a cutting-edge technology that has found extensive applications in the monitoring of Ensuring the safety, integrity, and operational efficiency of underground product pipelines is vital for maintaining the nation’s critical infrastructure. Monitoring parameters such as hoop strain, pressure, and acoustic vibrations is key to detecting potential leaks, intrusions, or structural issues. Distributed optical fiber sensor (DOFS) systems provide a compelling solution for continuous, real-time monitoring over long distances. This paper details the development and pilot-scale implementation of DOFS systems for underground pipeline monitoring, evolving from a proof-of-concept stage. Multiple custom-designed DOFS interrogator units—such as optical frequency-domain reflectometry (OFDR), Brillouin optical time-domain analysis (BOTDA), and multimodal interferometer-based fiber acoustic sensors—were employed to measure key parameters like hoop strain, pressure, and acoustic vibrations. The underground product pipeline's outer diameter is 30 inches, the wall thickness is 1.28 inches, and the 3-foot depth. The fiber deployment strategies, and sensing data acquisition methods for these systems are discussed. The results demonstrate the effectiveness of DOFS in detecting hoop strain, temperature changes, and acoustic vibrations, showcasing their potential for real-time monitoring and enhancing pipeline safety.

distributed fiber sensing↗
DOE OSTI2025

Regional and Temporal Variability of Atmospheric River Seasonality: Influences of Detection Algorithms and Moisture Transport Dynamics

Abstract Understanding the regional and temporal variability of atmospheric river (AR) seasonality is crucial for preparedness and mitigation of extreme events. While ARs were thought to peak in winter, recent research shows they exhibit region‐specific seasonality and are heavily influenced by the chosen detection algorithm. This study examines the link between the year‐to‐year consistency of peak‐AR activity to the presence of a dominant seasonal pattern, considering both location and algorithm choice. Regions are categorized by their temporal characteristics: consistent patterns (e.g., East Asia), patterns with occasional outliers (e.g., British Columbia coast), and regions lacking a clear dominant peak season (e.g., South Atlantic, parts of Australia). Hence, not all regions display a consistent seasonal cycle of AR activity. This study quantifies the extent to which a region experiences a dominant peak season of AR activity (or lacks one) and offers insights to enhance decision‐making in water management, natural hazard preparedness, and forecasting. Furthermore, given our finding that detection algorithms influence the peak season of AR activity, we also examine two diagnostic variables representative of moisture transport to corroborate our results. Integrated vapor transport, which captures meridional and zonal moisture transport, and Moist Wave Activity, representing moisture intrusions from lower to higher latitudes, are examined. Our analysis indicates that inconsistencies in the seasonal cycle of AR activity are not solely due to discrepancies in detection algorithms but also arise from changes in moisture transport. Plain Language Summary Atmospheric rivers (ARs) are critical weather phenomena that can cause extreme events like heavy rainfall and flooding. Understanding when and where ARs are most likely to occur throughout the year is essential for preparing and responding to these events. Traditionally, ARs were thought to peak in winter, but recent studies show this varies by region. Our study helps address the challenge decision‐makers face in anticipating and preparing for AR events by providing insights into the consistency of peak seasonal patterns across different areas. Some regions, like East Asia, and the British Columbia coast, show a consistent peak season, while others, like the South Atlantic and parts of Australia, have significant year‐to‐year variations, making it hard to identify a dominant season. To better understand these changes over time, the study also examines how moisture moves in the atmosphere, using Integrated Vapor Transport (which looks at moisture movement in various directions) and Moist Wave Activity (which tracks moisture shifts from lower to higher latitudes). The findings suggest that inconsistencies in AR patterns are due not only to detection methods but also due to changes in moisture transport. Key Points The peak season of atmospheric river activity can change depending on the year in some areas Interannual variations in the peak season can make identifying a dominant season challenging for some regions Frequent shifts in peak season across years reflect inconsistencies tied to detection algorithms and to underlying dynamics

Kamnani, Diya↗
DOE OSTI2024

Double-domed temperature-pressure phase diagram of CePd 3 S 4

CePd 3 S 4 exhibits interplay between ferromagnetism (FM), quadrupolar order, and the Kondo effect at low temperatures with a FM transition temperature that is much higher than the value expected from the de Gennes scaling of the heavier RPd 3 S 4 compounds. In this work, we investigated the electrical transport and magnetic properties of CePd 3 S 4 under pressure up through 12 GPa so as to better understand the interplay between electronic and magnetic phases in this material. Our findings show that the low pressure FM state is suddenly replaced by a new magnetically ordered phase that is most likely antiferromagnetic that spans from ~ 7 GPa to ~ 11 GPa. Whereas this could be described as an example of avoided quantum criticality, given that clear changes in resistance and Hall data are detected near 6.3 GPa for all temperatures below 300 K, it is also possible that the change in ground state is a response to a pressure induced change in structure. Furthermore, the lack of any discernible change in the pressure dependence of the room temperature unit cell parameter/volume across this whole pressure range suggests that this change in structure is either more subtle than could be detected by our measurements (i.e. development of weak, new wave vector) or the transition is electronic (such as a Lifshitz transition).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

EPCAPE-PT-LANL Measurements: Single Particle Soot Photometer

Coastal cities offer a unique environment for studying aerosol-cloud interactions and the effects of urban emissions on cloud properties. As part of the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE), the Partitioning Thrust by Los Alamos National Laboratory (EPCAPE-PT-LANL) was conducted. Our campaign focused on measuring the optical and chemical properties of aerosols and their interactions within marine stratocumulus clouds in La Jolla, California. EPCAPE-PT-LANL enhances the primary goals of EPCAPE through innovative observations of vapor-phase transitions between aerosols and cloud droplets, the impact of black carbon on aerosol-cloud dynamics, and the effects of cloud processing on aerosol optical properties. Instrument: Single Particle Soot Photometer (Droplet Measurements Technology) Data Notes: Contact us if you want additional data products from this instrument. Reported data is the black carbon (rBC) number and mass concentration with diagnostic flags. The SP2 measures incandescence from particles that is induced with a 1064 Nd-YAG laser. Particles that absorb the laser energy and then emit radiation is assumed to contain black carbon. The amount of intensity of radiation is related to the mass of absorbing material in the particle. Here, we calibrate the incandescence intensity to size selected Regal Black (Cabot) nebulized from solution. Data provided for the EPCAPE campaign used the combined broadband high-gain + low-gain channels (BHBL). Each channel has a lower threshold of detection equivalent to 2-s of the respective channel noise. Thresholding has been applied to select between the high-gain and low-gain channels. The detection limit is 80-540 nm (Deq) or 0.36- 55 fg. It is assumed that rBC is the only aerosol type that is in significant concentration in the sampled atmosphere that absorbs the laser energy. Particle data are integrated over 10 second windows to calculate a rBC number and mass concentration. QC/QA: • Diagnostic flags that impacted measured concentration: - Sample, Sheath, and Purge Flow Rates: Despite observing fluctuations in all flows, the rBC detection and mass quantification are generally observed to be stable, although large changes in sample flow rate did impact detection efficiency. A flag was implemented for sample flow deviations >12 cm3/min from the set point averaged over 30 seconds - Laser Power: Detection efficiency decreases with laser power and deviations in laser power also affect mass quantification. Flag for laser power is set for deviations in laser current from the set value >5 mA. - Primary Detector Threshold: Primary thresholding is the signal value which determines whether a “particle” is recorded. Thresholding errors occur when the threshold value is too HIGH and real particles are ignored. • Several periods without data: - 16-18 Nov: Ultra Zero Air generator failure, flows deviated significantly from set points. rBC # conc recovered but questionable. - 20-21 Nov: Offline for calibrations for several hours each day. - 25-27 Nov: Data is missing. - 30 Nov: Power outage 3 Dec: SP2 hard-drive full. - 3 Dec: Power Outage Header: - BHBL_NumbConc[#/cc]: Refers to the number concentration of refractory black carbon (rBC) measured from combined broadband high-gain and low-gain channels, expressed in particles per cubic centimeter. - BHBL_BCMass_Conc[ug/m3]: Refers to the mass concentration of refractory black carbon (rBC) measured from combined broadband high-gain and low-gain channels, expressed in micrograms per cubic meter. - NoData_Flag[bool]: A boolean flag that indicates whether no data was recorded during a measurement. - NoBC_Flag[bool]: A boolean flag indicating whether no black carbon particles were recorded during the measurement. - Laser_Flag[bool]: A boolean flag indicating deviations in laser current during the measurement. - SampleFlow_Flag[bool]: A boolean flag indicating deviations from the set sample flow rate during the measurement. - PrimThresh_Flag[bool]: A boolean flag indicating deviations from the set primary threshold during the measurement, potentially ignoring real particles. - Manual_Flag[bool]: A boolean flag indicating manual intervention or adjustments during the measurement. - CVI_Flag[bool]: A boolean flag indicating whether the Counterflow Virtual Impactor (CVI) was active or inactive during the measurement.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Miniaturized Magnetoelastic Sensor System

This article describes the design, assembly, and implementation of a hand-held, magnetic-field-based sensor system that can be adapted for a variety of sensing applications. The miniaturized system is based on Chemical Identification by Magneto-Elastic Sensing (ChIMES) technology, which uses three concentric solenoid coils to wirelessly interrogate a sensor body comprised of a response material coupled to a magnetoelastic wire. The response material expands when it encounters a target, imposing mechanical stress on the wire and altering its magnetic permeability. The sensor bodies are passive, requiring no external power source, and they are small, measuring about 15 mm in length and 3.0 mm in diameter. Up to four sensor bodies can be configured as an evenly-spaced linear array. The sensor system operates by applying a low-frequency, current-stabilized, filtered triangle wave to a uniform-density excitation coil to switch the magnetic domains within the wire. Further, the responses from the sensors are picked up by a detection coil as stress-induced changes in the Faraday voltage, and the strong magnetic field induced by the excitation coil in the detection coil is nullified by a cancellation coil reverse-wound in series with the detection coil. The responses of the sensors in an array are separated in time by a linear gradient dc biasing coil. The sensors can be interrogated through metallic and nonmetallic barriers. The signals from the detection coil and the excitation coil are digitized by a pair of bipolar analog-to-digital converters (ADCs). A Raspberry Pi single-board computer (SBC) and associated software perform data acquisition and control all aspects of the sensor system hardware. The program allows the user to select the number of sensors in the array, the type of signal that is being collected, and the number of samples to take. The program also allows for signal processing of the sensor data, such as baseline correction. The program can differentiate sensor peaks from each other and calculate the magnitude of each sensor response with less than 1% error. The data are then displayed along with a graph of the signal.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Dark Photon Dark Matter and Low-frequency Gravitational-wave Detection with Gaia-like Astrometry

Astrometric surveys offer us a method for searching for elusive cosmic signatures, such as ultralight dark photon dark matter and gravitational waves (GWs), by observing the temporal change of stars’ apparent locations. The detection capabilities of such surveys rapidly decrease at low frequencies, because the signals become hardly distinguishable from the background motion of stars. In this work, we find that the background motion can be well described by a linear model over time, based on which we propose a linear background subtraction scheme. Compared to the conventional quadratic subtraction, the advantage of linear subtraction emerges within the frequency range below 6 × 10 −9 Hz. Taking dark photons with purely gravitational interactions, dark photons with additional U(1) B or U(1) B−L gauge interactions, and low-frequency GWs as examples, we illustrate that the linear subtraction scheme can result in an enhancement of more than 1 order of magnitude in the exclusion limits of Gaia-like experiments in the low-frequency range.

Astrometry↗