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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Jefferson Laboratory C100 Superconducting Radio-Frequency Cavity Fault Data, 2020

The dataset was created to train machine learning models for the task of identifying the (1) cavity and (2) fault type from C100-type cryomodules at the Thomas Jefferson National Accelerator Facility (Jefferson Lab), thereby replacing the time-consuming efforts of a subject matter expert. Superconducting radio-frequency (SRF) cavity trips represent a significant source of accelerator downtime. Real-time – rather than post-mortem – identification of the offending cavity and classification of the fault type would give control room operators valuable feedback for corrective action planning. The anticipated benefit is increased beam-on-target time for users and provides performance metrics that can be used to improve future cavity designs. A series of 17 RF signals are recorded for each of the 8 cavities in a C100 cryomodule every time a cavity trips. These time-series signals are written to file using a specially designed data acquisition system. The dataset represents fault events recorded during Continuous Electron Beam Accelerator Facility (CEBAF) beam operations between January 18, 2019 and March 9, 2020. The following filtering steps were applied to collected data; (1) only 4 of the 17 signals per cavity are retained (GMES, GASK, CRFP, DETA2) (2) only events with data from each of the eight cavities in the cryomodule are kept, (3) only events that were sampled at 5 kHz were kept, (4) events from cryomodule 0L04 were neglected, (5) events occurring between February 4, 3PM and February 5, 12PM were neglected. As a result of preprocessing, the dataset is comprised of 2,375 unique events. The full dataset is comprised of three files: features.csv, cavity_labels.csv, fault_labels.csv. Each instance in faults.csv includes a timestamp (“date_time”), a label for the cryomodule which experienced the trip (“zone_label”), and 192 features (“feature_1”, “feature_2”... “feature_192”). The features correspond to 6 autoregressive features for each of 4 signals per cavity for each of the 8 cavities (6 × 4 signals/cavity × 8 cavities/cryomodule = 192). To deal with the large variation of signal amplitudes, time-series standardization via the z-score (standard score) function was applied prior to computing the features. For each instance, there is an associated label for the (1) cavity which faulted first (cavity_labels.csv) and (2) the type of fault that caused the trip (fault_labels.csv). The cavity identification can take values of [0, 1, 2, 3, 4, 5, 6, 7, 8] and the fault type can take values of [‘Microphonics’, ‘Quench_100ms’, ‘Controls_Fault’, ‘E_Quench’, ‘Quench_3ms’, ‘Single_Cav_Turn_Off’ , ‘Heat_Riser_Choke’, ‘Multi_Cav_Turn_Off’].

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Optimal filtering and generation of entangled photons for quantum applications in the presence of noise

Filtering is commonly used in quantum optics to reject noise photons, and also to enable interference between independent photons. However, filtering the joint spectrum of photon pairs can reduce the inherent coincidence probability or loss-independent heralding efficiency. Here we investigate filtering for multiphoton applications based on entanglement and interference (e.g., quantum teleportation). We multiplex C-band entangled photons and C-band classical communications into the same long-distance fibers, which enables scalable low-loss quantum networking but requires filtering of spontaneous Raman scattering noise from classical light. Using tunable-bandwidth filters, low-jitter detectors, and polarization filters, we distribute wavelength-degenerate time-bin entangled photons in the C band (1536.5 nm) over 25 km/25 km standard fibers (50 km) each carrying 10 Gbit/s C-band classical data signals. Narrow filtering enables milliwatt-level C-band power, which exceeds the power achieved by comparable studies by roughly an order of magnitude and could feasibly support terabit per second classical rates. We evaluate how performance depends on pump and filter bandwidths, multipair emission, filter shapes, loss, phase matching, and how quantum information is measured. We find a trade-off between reducing noise impact and increasing single-mode purity, and discuss mitigation methods toward optimal multiphoton applications. Importantly, these results apply to noise in free space and in quantum devices (sources, frequency converters, switches, detectors, etc.) and provide insight into filter-induced degradation of single-photon purity and rates even in noise-free environments.

Thomas, Jordan M. [Fermilab; Northwestern U.]↗
DOE OSTI2026

The Poisson tensor completion parametric estimator

We introduce the Poisson tensor completion (PTC) estimator that exploits inter-sample relationships to compute a low-rank Poisson tensor decomposition of the frequency histogram for samples of a multivariate distribution. Our crucial observation is that the histogram bins are an instance of a space partitioning of counts and thus can be identified with a spatial non-homogeneous Poisson process. The Poisson tensor decomposition leads to a completion of the mean measure over all bins—including those containing few to no samples—and leads to our proposed estimator. A Poisson tensor decomposition models the underlying distribution of the count data and guarantees non-negative estimated values obviating the need for additional constraints to ensure non-negativity. Furthermore, we demonstrate that our PTC estimator is a substantial improvement over standard histogram-based estimators for sub-Gaussian probability distributions because of the concentration of norm phenomenon.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Next-Generation Intensity-Duration-Frequency Curves for Diverse Land across the Continental United States

The current methods for designing hydrological infrastructure rely on precipitation-based intensity-duration-frequency curves. However, they cannot accurately predict flooding caused by snowmelt or rain-on-snow events, potentially leading to underdesigned infrastructure and property damage. To address these issues, next-generation intensity-duration-frequency (NG-IDF) curves have been developed for the open condition, characterizing water available for runoff from rainfall, snowmelt, and rain-on-snow. However, they lack consideration of land use land cover (LULC) factors, which can significantly affect runoff processes. We address this limitation by expanding open area NG-IDF dataset to include eight vegetated LULCs over the continental United States, including forest (deciduous, evergreen, mixed), shrub, grass, pasture, crop, and wetland. This NG-IDF 2.0 dataset offers a comprehensive analysis of hydrological extreme events and their associated drivers under different LULCs at a continental scale. It will serve as a useful resource for improving standard design practices and aiding in the assessment of infrastructure design risks. Additionally, it provides useful insights into how changes in LULC impact flooding magnitude, mechanisms, timing, and snow water supply.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Electrobaryonic axion: hair of neutron stars

Axion-like particles are predicted in many physics scenarios beyond the Standard Model (SM). Their interactions with SM particles may arise from the triangle anomaly of the associated global symmetry, along with other SM global and gauge symmetries, including anomalies with the global baryon number and electromagnetic gauge symmetries. We initiate the phenomenological study of the corresponding “electrobaryonic axion”—a particle that couples with both the baryon chemical potential and the electromagnetic field. Neutron stars, particularly magnetars, possessing high baryon density and strong magnetic fields, can naturally develop a thin axion hair around their surface. In this study, we calculate this phenomenon, considering the effects of neutron star rotation and general relativity. For axion particles lighter than the neutron star rotation frequency, the anomalous interaction can also induce the emission of axion particles from the neutron star. In the light axion regime, this emission can significantly contribute to the neutron star cooling rate.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Shape-constrained Input Estimation for Efficient Multi-shaker Vibration Testing

Multi-shaker vibration testing is gaining interest from structural dynamics test engineers as it can provide a much more accurate match to complicated field vibration responses than traditional single-axis shaker tests. However, the force capabilities of the small modal shakers typically used in multi-shaker vibration tests has limited the achievable response levels. To date, most multi-shaker vibration tests have been performed using a variety of standard, commercially-available control systems. While these control systems are adequate for a wide range of multiple-input/multiple-output tests, their control algorithms have not been tailored for the specific problem of multi-shaker vibration tests: efficiently coordinating the various shakers to work together to achieve a desired response. Here, a new input estimation algorithm is developed and demonstrated using simulations and actual test data. This algorithm, dubbed shape-constrained input estimation, is shown to effectively coordinate multiple shakers using a set of constraint vectors based on the deflection shapes of the test structure. This is accomplished by using the singular vector shapes of the system frequency response matrix, which allows the constraint vectors to automatically change as a function of frequency. Simulation and test results indicate a significant reduction in the input forces required to achieve a desired response. Finally, the results indicate that shape-constrained input estimation is an effective method to achieve higher response levels from limited shaker forces which will enable higher level multi-shaker vibration tests to be performed.

42 ENGINEERING↗
DOE OSTI2025

Si-Cr-Al-Mn Alloy for High Specific Resistivity

Laboratory material produced in budget period one met the target resistivity, mechanical and magnetic requirements for the Go/No-Go decision to move to industrial trials. The chosen chemistry settled on a high Cr strategy, with moderate Mn and Al additions, providing a good comprise on core loss and induction with minimal impact on mechanical properties, important to successful downstream processing. Industrial trials began in budget period two with the chosen chemistry, referred to as Alloy X. Difficulties occurred during initial hot rolling trials. Reheating the material using the standard NOES practice caused slab cracking from high thermal gradients in areas exposed to the roof burners, this was solved using a modified reheat practice. High Cr caused poor dynamic recrystallization during hot rolling, which was solved using a modified hot rolling practice. The high Cr content of the steel also caused poor decarburization during final annealing, which necessitated lowering the melt carbon aim for the final heat, together with a modified decarburization practice. Steel was finished to final thicknesses of 0.20 – 0.50 mm and evaluated for magnetic and mechanical properties. Although the target core loss for the 0.25 and 0.35 mm material was not achieved, significant reductions in high frequency core loss were measured, compared to equivalent commercially available material. Alloy X at 0.35 mm showed a 26 % and 23 % improvement at 400 HZ and 1000 Hz respectively, over Cliffs’ M-19 (0.35 mm) commercially available NOES. At 0.25 mm, Alloy X showed a 23 % and a 26 % improvement at 400 HZ and 1000 Hz respectively, over Cliffs’ HF-10 (0.25 mm) commercially available NOES. The 0.25 mm product was chosen for motor efficiency evaluation. ORNL collaborated with Cleveland-Cliffs (CC) to build, assemble, and test two 5HP motors: a baseline motor with M19 steel and a motor made with high efficiency steel (Alloy X) developed for the project. Overall, results were as expected with comparable performance at low speeds, and with more than 8% efficiency improvement for high speeds. Increased motor steel efficiency at high frequencies not only results in direct efficiency improvements but can yield reductions in motor size and cost by facilitating higher operation speeds, or by increasing the number of poles in the machine. This allows the production of more power-dense motors which are sometimes avoided with conventional material due to increased core losses. The material developed on this project provides more viable options for achieving improved motor efficiency or reduced motor size and cost.

36 MATERIALS SCIENCE↗
DOE OSTI2025

DC-Link Capacitor Design for a Neutral-Point-Less Three-Level Dual-Phase Inverter for Traction Application

Conventional multilevel inverters, such as neutral￾point-clamped and T-type inverters, have gained popularity in electric vehicle applications due to their advantages, including high voltage range, high power capability, low switching losses, low total harmonic distortion, and low electromagnetic interference. However, these traditional multilevel inverters require a neutral point connection to generate a zero-voltage vector. The neutral point current oscillates at three times the fundamental frequency, leading to voltage imbalance and overvoltage stress on the power modules. Additionally, the use of two stacked DC-link capacitors increases the volume required for the same overall capacitance and complicates packaging due to ripple current and heat dissipation from separate components. This is a significant concern for traction drive units, where space is limited. In this paper, a neutral-point-less multilevel dual three￾phase inverter topology is investigated for traction inverter applications. Simulation results demonstrate that the proposed topology effectively retains the benefits of multilevel operation while utilizing a single DC-link capacitor. The inverter model was simulated in conjunction with an industry-standard battery model to evaluate the potential for capacitor size reduction compared to a conventional three-level inverter.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Chiral microwave nonreciprocity demonstrated via Rayleigh and Sezawa modes supported in an Al 0.58 ⁢Sc 0.42 ⁢N/4⁢H–Si⁢C platform

Chirality plays a crucial role in the helicity mismatch between surface acoustic waves and magnetic spin waves, leading to nonreciprocal transmission of acoustic power for coupled magnetoacoustic modes. Acoustic modes with both longitudinal and shear strain exhibit elliptical particle displacements, making them chiral, and different acoustic modes can exhibit different helicities of this elliptical particle displacement. Here, we study chiral acoustic modes with different helicities supported on the same piezoelectric platform and their interaction with magnetic spin waves. Our study demonstrates that the nonreciprocal transmission of acoustic power is driven by the helicity mismatch effect and, specifically, that the handedness of the nonreciprocity is based on whether the surface acoustic wave has retrograde (Rayleigh mode) or prograde (Sezawa mode) elliptical particle displacement with respect to the propagation direction. We found the transmission nonreciprocity to be significant, with 7.3 dB/mm for the retrograde particle displacement (Rayleigh mode at 2.358 GHz) and 3.3 dB/mm for prograde particle displacement (Sezawa mode at 3.112 GHz). Furthermore, this work highlights that piezoelectric platforms can be engineered to support acoustic modes with opposite helicities to enable frequency-selective nonreciprocal radiofrequency and microwave components, such as isolators and circulators, through coupled acoustic spin wave interactions.

42 ENGINEERING↗
DOE OSTI2023

Extrapolation of the Rainflow-Counted Load Ranges for Fatigue Assessment of the Wind Turbine's Blades

Wind turbine design standards recommend the use of statistical modeling coupled with extrapolation of the short-term load data to long-term periods for fatigue reliability assessment. However, statistical error and computational expense can limit the accuracy of such approaches. In the case of wind turbine blades, the errors are more significant because of the high material fatigue exponent that makes the damage estimations more sensitive to variations. In addition, due to different excitation sources, the flapwise load range histogram is not unimodal, and thus its statistical modeling is complex. In the present work, we provide three methods for statistical modeling of the flapwise bending moment ranges including a novel approach based on frequency-based separation of the modes. The first two methods are simplified approaches for modeling the most crucial load ranges using unimodal distributions and the third method involves multimodal distribution fitting. The research is based on 3600 10-minute aeroelastic simulations of DTU 10MW case study wind turbine from which a benchmark damage equivalent load (DEL) is calculated. The DEL calculated by each of the three proposed methods is compared to this reference. The results show that the conventional approach based on using 6 seeds as well as using mixture models fitted on the limited data lead to under-conservative results with errors up to 23%. On the other hand, the simplified unimodal approaches provided in this work can provide conservative estimations of the fatigue damage with mean values 5% and 12% higher than the benchmark. However, the variability of the DEL estimates is higher when using unimodal extrapolation of the load ranges, and the data can be conservative by 17.5%. The proposed unimodal fits suggested for modeling and extrapolation of the blade's load ranges provide less errors relatively and most importantly conservative DEL estimations while maintaining computational efficiency.

blade fatigue↗
DOE OSTI2021

Engineering Dynamical Sweet Spots to Protect Qubits from 1/$f$ Noise

Protecting superconducting qubits from low-frequency noise is essential for advancing superconducting quantum computation. Based on the application of a periodic drive field, we develop a protocol for engineering dynamical sweet spots which reduce the susceptibility of a qubit to low-frequency noise. Using the framework of Floquet theory, we prove rigorously that there are manifolds of dynamical sweet spots marked by extrema in the quasi-energy differences of the driven qubit. In particular, for the example of fluxonium biased slightly away from half a flux quantum, we predict an enhancement of pure-dephasing by three orders of magnitude. Employing the Floquet eigenstates as the computational basis, we show that high-fidelity single- and two-qubit gates can be implemented while maintaining dynamical sweet-spot operation. We further confirm that qubit readout can be performed by adiabatically mapping the Floquet states back to the static qubit states, and subsequently applying standard measurement techniques. Our work provides an intuitive tool to encode quantum information in robust, time-dependent states, and may be extended to alternative architectures for quantum information processing.

Huang, Ziwen↗
DOE OSTI2021

Reliability metrics and their management implications for open pond algae cultivation

The prevalence of contaminating organisms in outdoor algae cultivation, with the often-associated dramatic crop failures, necessitates the need for metrics describing production system reliability. Standard metrics for algae cultivation reliability are critically needed to be able to map improvements in operational parameters, but do not currently exist. In this work, we present a set of standard metrics including mean time to failure (MTTF) and mean time between failures (MTBF) as the basis for the calculation of pond failure rate (FR) and reliability coefficient (RC). Metrics associated with the numbers of contaminating organisms such as abundance ratio (AR), prevalence of infection (PI), and mean intensity of infection (MII) are also relevant. These metrics, based on measured experimental values of outdoor pond performance during the Algae Testbed Public-Private Partnership (ATP3) Unified Field Studies (UFS), provide a basis for quantifying pond failure and provide insight into potential pond management and contaminant mitigation strategies. From these reliability metrics applied to this dataset, we are able to link operational parameters, such as harvest frequency and inoculum source, to pond reliability for different algae strains and seasons, and from an assessment of AR, provide contamination thresholds beyond which a culture may be unrecoverable. Ultimately, the implementation of widely-practiced and simple-to-calculate algae pond reliability metrics calculated from rapid and easy to collect data or observations will reduce risk and uncertainty in large-scale algae deployment and aid in the development of integrated pest management (IPM) strategies.

09 BIOMASS FUELS↗
DOE OSTI2020

Numerical simulation of an atmospheric pressure plasma jet with coaxial shielding gas

A two-dimensional ( r, z ) numerical simulation of the discharge characteristics of an atmospheric pressure plasma jet (APPJ), with coaxial shielding gas, was performed. The helium working gas flowed in a central capillary tube, engulfing a needle electrode powered by 13.7 MHz radio frequency sinusoidal voltage. The N 2 shielding gas flowed in the annular space of a coaxial tube. These gases emerged, in laminar flow, in a 78%N 2 -21%O 2 -1%Ar dry air ambient. The characteristics of the APPJ with shielding gas were compared to those of the APPJ without shielding gas. The nitrogen shielding gas hindered the diffusion of oxygen and argon from the ambient air into the helium jet. With the shielding gas present, more nitrogen penetrated into the helium core, causing a shorter plasma ‘plume’. The flow rates of the working and shielding gas, critically affected the gas temperature, and in turn the discharge characteristics. For a He flow of 2 standard liters per minute (slm), switching on the nitrogen shielding gas flow (at 4.5 slm) reduced the on-axis O 2 and Ar mole fractions from 3.9 × 10 - 4 to 6.8 × 10 - 5 and from 1.9 × 10 - 5 to 3.3 × 10 - 6 , respectively, at an axial distance of 3 mm downstream of the nozzle. The radial profiles of the mole fractions of the ambient gases were monotonically and strongly decreasing towards the system axis, for short axial distances from the nozzle (~1 mm), but became progressively flatter at longer distances from the nozzle (3 mm and 5 mm). Simulation predictions captured the salient features of experimental data of ambient species mole fractions in the plasma jet, and the 706 nm optical emission intensity profiles of the He 3 3 S excited state.

Physics↗
DOE OSTI2025

Improving Dose Modeling With Dynamic Modeling Tools [Slides]

Utilities aiming for higher fuel enrichment for power uprates or extended operation times before refueling must conduct a new dose analysis. Current conservative dose estimation standards may cause utilities to exceed regulatory limits for proposed increased fuel enrichment. A more accurate modeling of doses from reactor accidents can lower these conservative assumptions. Prescott et al. (2022) demonstrated that the Event Modeling Risk Assessment using Linked Diagrams (EMRALD) software tool, developed at Idaho National Laboratory (INL), can be coupled with the Modular Accident Analysis Program (MAAP5) for dynamic accident analysis in reactor plants. EMRALD forms models of potential accident scenarios, while MAAP5 simulates the accident progression and dose consequences. By integrating these software tools with utility-specific data, a more precise estimation of dose consequences from plant accidents can be achieved. Preliminary findings indicate that EMRALD provides accurate mean core damage frequencies for generalized accident scenarios. Future work includes expanding the model to account for plant-specific data and mitigation factors.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Single-shot electro-optic sampling with arbitrary terahertz polarization

With the recent development of diversity electro-optic sampling (DEOS), significant progress has been made in the range of applicability of single-shot EOS measurements, allowing broadband THz waveforms to be captured in a single shot over large temporal windows. In addition to the decrease in acquisition time compared to standard multishot data acquisition, this technique allows measurements on systems far from equilibrium with large shot-to-shot noise or with irreversible or poorly repeatable dynamics. Although DEOS has been demonstrated and verified for linearly polarized THz waveforms, we investigate the effects resulting from the presence of a secondary polarization component. This imposes new challenges for accurate waveform reconstruction, and opens the opportunity to measure out complex polarization states such as arbitrary elliptically polarized THz field. We demonstrate a single-shot diversity-electro-optic-sampling-based approach to capture both x- and y-THz fields simultaneously with a single (110)-cut EO crystal for THz polarimetry and ellipsometry over a wide range of frequencies.

Lenz, Maximilian [University of California, Los An↗
DOE OSTI2021

Direct Mercury Detection in Landfill Leachate Using a Novel AuNP-Biopolymer Carbon Screen-Printed Electrode Sensor

A novel Au nanoparticle (AuNP)-biopolymer coated carbon screen-printed electrode (SPE) sensor was developed through the co-electrodeposition of Au and chitosan for mercury (Hg) ion detection. This new sensor showed successful Hg2+ detection in landfill leachate using square wave anodic stripping voltammetry (SWASV) with an optimized condition: a deposition potential of −0.6 V, deposition time of 200 s, amplitude of 25 mV, frequency of 60 Hz, and square wave step voltage of 4 mV. A noticeable peak was observed at +0.58 V associated with the stripping current of the Hg ion. The sensor exhibited a good sensitivity of ~0.09 μA/μg (~0.02 μA/nM) and a linear response over the concentration range of 10 to 100 ppb (50–500 nM). The limit of detection (LOD) was 1.69 ppb, which is significantly lower than the safety limit defined by the United States Environmental Protection Agency (USEPA). The sensor had an excellent selective response to Hg2+ in landfill leachate against other interfering cations (e.g., Zn2+, Pb2+, Cd2+, and Cu2+). Fifteen successive measurements with a stable peak current and a lower relative standard deviation (RSD = 5.1%) were recorded continuously using the AuNP-biopolymer-coated carbon SPE sensor, which showed excellent stability, sensitivity and reproducibility and consistent performance in detecting the Hg2+ ion. It also exhibited a good reliability and performance in measuring heavy metals in landfill leachate.

Hwang, Jae-Hoon (ORCID:0000000220100864)↗
DOE OSTI2025

Durability of PGM catalyst MEAs of polymer electrolyte membrane fuel cells for heavy-duty vehicles

Polymer electrolyte membrane fuel cells (PEMFCs) are promising power sources for heavy-duty vehicles (HDVs) owing to cleanliness and efficiency. However, the degradation of membrane electrode assemblies (MEAs) under HDV conditions remains a huge challenge. Here, this work investigated MEA durability under HDV conditions using a US Department of Energy standard accelerated stress test for 180,000 cycles (equivalent to 1 million miles of HDV operation). Effects of catalyst Pt content on MEA durability were examined using homemade 30% Pt/C (H-Pt/C) and commercial 46% Pt/C (C-Pt/C) catalysts. Both MEAs experienced H 2 /air and H 2 /O 2 performance loss over cycles. Analysis with scanning transmission electron microscopy, X-ray diffraction, inductively coupled plasma mass spectrometry, and mercury intrusion porosimetry revealed severe degradation of Pt nanoparticles (NPs), support structures, and the catalyst layer. Two degradation stages for NPs were proposed: Ostwald ripening dominated the initial 60,000 cycles, followed by combined Ostwald ripening and particle migration. Measurements with ion chromatography, high-frequency resistance, and oxygen-diffusion resistance revealed degradation of membrane and ionomer, respectively.

25 ENERGY STORAGE↗
DOE OSTI2025

Spin squeezing of macroscopic nuclear spin ensembles

Spin squeezing has been explored in atomic systems as a tool for quantum sensing, improving experimental sensitivity beyond the spin standard quantum limit for certain measurements. To optimize absolute metrological sensitivity, it is beneficial to consider macroscopic spin ensembles, such as nuclear spins in solids and liquids. Coupling a macroscopic spin ensemble to a parametrically-modulated resonant circuit can create collective spin squeezing by generating spin correlations mediated by the circuit. We analyze the squeezing dynamics in the presence of decoherence and finite spin polarization, showing that achieving 7 dB spin squeezing is feasible in several nuclear spin systems. The metrological benefit of squeezing a macroscopic spin ensemble lies in the suppression of technical noise sources in the spin detection system relative to the spin projection noise. This expands the experimental sensitivity bandwidth when searching for signals of unknown frequency and can improve the resonant signal-to-noise ratio. Squeezing macroscopic spin ensembles may prove to be a useful technique for fundamental physics experiments aimed at detecting spin interactions with oscillating background fields, such as ultralight dark matter. Published by the American Physical Society 2025

Boyers, Eric↗