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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Characterization of the X-ARAPUCA Systems' Response for SBND's Light Detection

X-ARAPUCA waveform data, collected at a test stand at the Noble Liquid Test Facility (NLTF) and the Short Baseline Near Detector (SBND), were analyzed via python scripts. For the ARARA system, various distributions and correlations were studied, including the area and amplitude distributions of the waveform peaks for identifying single photoelectron peaks, as well as characterizing the behavior of the baseline artifact. The ARARA system is being studied in order to be implemented into SBND, just as the APSAIA X-ARAPUCAs have been.

Novotny, Andrew [U. Illinois, Chicago]↗
DOE OSTI2026

Characterization of lateral amorphous selenium photodetectors for low-photon and VUV detection at cryogenic temperatures

The performance of amorphous selenium (a-Se) as a cryogenic photodetector material is evaluated through a series of experiments using laterally structured devices operated in a custom optical test stand. These studies investigate the response of a-Se detectors to low-photon fluxes at high electric fields near avalanche conditions, the linearity of the photoconductive response over a wide dynamic range and the direct detection of narrowband 130 nm vacuum ultraviolet (VUV) illumination. At 87 K, matched-filter analysis shows reliable single-shot detection with efficiencies ≥80% and area under the curve (AUC) ≥ 0.85 using as few as ∼ 6800 incident 401 nm photons, corresponding to ∼ 3400 photons within field-active regions after accounting for geometric constraints. Measurements are performed at cryogenic temperatures using calibrated photon fluxes derived from a silicon photomultiplier reference and a characterized optical filter stack. Additional experiments using a tellurium-doped a-Se (a-SeTe) device explore the material's behavior under identical test conditions and demonstrate that avalanche is achievable in a-SeTe at cryogenic temperatures. The results demonstrate reproducible low-noise operation, VUV sensitivity and field-dependent gain behavior in a lateral a-Se architecture, representing the first reported observation of avalanche multiplication in laterally structured a-Se and a-SeTe devices at cryogenic temperatures. These findings support the potential integration of laterally structured a-Se devices into next-generation pixelated liquid-argon time projection chambers (TPCs) requiring scalable, high-field-compatible photon detection systems.

Amorphous selenium↗
DOE OSTI2025

Characterization of the X-ARAPUCA systems' response for SBND's light detection

X-ARAPUCA waveform data, collected at a test stand at the Noble Liquid Test Facility (NLTF) and the Short Baseline Near Detector (SBND), were analyzed via python scripts. For the ARARA system, various distributions and correlations were studied, including the area and amplitude distributions of the waveform peaks for identifying single photoelectron peaks, which was able to be accomplished. The behavior of the baseline artifact was also characterized, which appeared only at high voltages/bright events, and separates further from the prompt peak as the voltage/brightness increases. The ARARA system is being studied in order to be implemented into SBND, just as the APSAIA X-ARAPUCAs have been.

Novotny, Andrew [Fermilab]↗
DOE OSTI2025

Characterization of Lateral Amorphous Selenium Photodetectors for Low-Photon and VUV Detection at Cryogenic Temperatures

The performance of amorphous selenium (a-Se) as a cryogenic photodetector material is evaluated through a series of experiments using laterally structured devices operated in a custom optical test stand. These studies investigate the response of a-Se detectors to low-photon fluxes at high electric fields near avalanche conditions, the linearity of the photoconductive response over a wide dynamic range and the direct detection of narrowband 130 nm vacuum ultraviolet (VUV) illumination. At 87 K, matched-filter analysis shows reliable single-shot detection with efficiencies greater than or equal to 80 percent and area under the curve (AUC) greater than or equal to 0.85 using as few as approximately 6800 incident 401 nm photons, corresponding to approximately 3400 photons within field-active regions after accounting for geometric constraints. Measurements are performed at cryogenic temperatures using calibrated photon fluxes derived from a silicon photomultiplier reference and a characterized optical filter stack. Additional experiments using a tellurium-doped a-Se (a-SeTe) device explore the material's behavior under identical test conditions and demonstrate that avalanche is achievable in a-SeTe at cryogenic temperatures. The results demonstrate reproducible low-noise operation, VUV sensitivity and field-dependent gain behavior in a lateral a-Se architecture, representing the first reported observation of avalanche multiplication in laterally structured a-Se and a-SeTe devices at cryogenic temperatures. These findings support the potential integration of laterally structured a-Se devices into next-generation pixelated liquid-argon time projection chambers (TPCs) requiring scalable, high-field-compatible photon detection systems.

FOS: Physical sciences↗
DOE OSTI2024

The Utility of Infrasound in Global Monitoring of Extraterrestrial Impacts: A Case Study of the 2008 July 23 Tajikistan Bolide

Abstract Among the various observational techniques used for the detection of large bolides on a global scale is a low-frequency sound known as infrasound. Infrasound, which is also one of the four sensing modalities used by the International Monitoring System, offers continuous global monitoring and can be leveraged for planetary defense. Infrasonic records can provide an additional dimension for event characterization and a distinct perspective that might not be available through any other observational method. This paper describes the infrasonic detection and characterization of the bolide that disintegrated over Tajikistan on 2008 July 23. This event was detected by two infrasound stations at distances of 1530 and 2130 km. Propagation paths to one of the stations were not predicted by the model, despite being clearly detected. The presence of the signal is attributed to the acoustic energy being trapped in a weak but leaky stratospheric AtmoSOFAR channel. The infrasound signal analysis indicates that the shock originated at the point of the main breakup at an altitude of 35 km. The primary mode of the shock production of the signal detected at the two stations was a spherical blast resulting from the main gross fragmentation episode. The energy estimate, based on the signal period, is 0.17–0.51 kt of TNT equivalent, suggesting a mass of 6.6–23.5 tons. The corresponding object radius, assuming the chondritic origin, was 0.78–1.18 m.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Hybridization capture sequencing for Vibrio spp. and associated virulence factors

ABSTRACT Proliferation ofVibriospp. in aquatic ecosystems is associated with climate change and, concomitantly, increased incidence of vibriosis. They are autochthonous to aquatic environments globally, but traditional metagenomic methods for detecting and typing pathogenicVibriospp. are challenged by their presence in relatively low abundance and ability to persist in a viable but nonculturable state. In the study reported here, hybridization capture sequencing (HCS) was employed to profile low-abundanceVibriospp. in environmental samples. The HCS panel targeted a family of molecular chaperones (CPN60) specific to 69Vibriospp. and 162Vibrio-specific virulence factors. This approach was evaluated in parallel with traditional whole-community shotgun sequencing in a metagenomic analysis of water and oyster samples collected from the Chesapeake Bay. In addition,Vibrio parahaemolyticusandVibrio vulnificusstrains isolated from the samples were subjected to whole-genome sequencing to determine the genetic characteristics of pathogenicVibriospp. circulating in an aquatic environment. HCS, employed to determine the incidence and characterization of specificVibriospp., yielded significantly greater metagenomic insight, notably a variety of otherVibriospp., including detection ofVibrio cholerae,Vibrio fluvialis, andVibrio aestuarianus, in addition toVibrio parahaemolyticusandVibrio vulnificus, and also important virulence factors not detectable using traditional molecular methods. Thus, pathogenicVibriospp. in aquatic ecosystems may be far more common than currently understood. It is concluded that environmental surveillance should include HCS, a valuable tool for the detection and characterization of pathogenic agents in aquatic ecosystems, notably vibrios. IMPORTANCE The increasing prevalence of pathogenicVibriospp. in aquatic ecosystems, driven by climate change, is closely linked to a rise in cholera and vibriosis cases, emphasizing the need for improved environmental surveillance. Vibrios are naturally occurring in aquatic environments globally, but traditional metagenomic methods for detecting and typing pathogenicVibriospp. are challenged by their presence in relatively low abundance and ability to persist in a viable but nonculturable state. In the study reported here, hybridization capture sequencing was employed to profile low-abundanceVibriospp. in metagenomic samples, namely water and oysters collected from the Chesapeake Bay. This approach was evaluated in parallel with traditional whole-community shotgun sequencing and whole-genome sequencing ofVibrio parahaemolyticusandVibrio vulnificusstrains isolated from the samples. Results suggest pathogenicVibriospp. in aquatic ecosystems may be far more common than currently understood, when multiple methods are considered for environmental surveillance.

Microbiology↗
DOE OSTI2026

Multiscale characterization of phase change materials for building thermal energy storage applications

Phase change materials (PCMs) store and release large amounts of thermal energy because of their high latent energy storage capacity. However, long-term cyclic stability, supercooling and performance-scalability are some of the major challenges for their use in building thermal energy storage (TES) applications. Here, in this study, we present a comprehensive multiscale characterization of two commercially available organic PCMs, Puretemp 18 and Puretemp 23. At the microscale, differential scanning calorimetry (DSC) was used to characterize phase change temperature, specific heat, and latent heat. At the mesoscale, a heat flow meter apparatus (HFMA), following the ASTM C1784 standard, was employed to measure the phase change temperature, specific heat, and latent heat properties. A comparative analysis of latent heat as a function of temperature was conducted by integrating the DSC and HFMA results. At the macroscale, the thermal performance and cyclic stability of the TES system was evaluated using Puretemp 23. The TES system consisted of a finned tube heat exchanger with a storage volume of 0.0189 m 3 (5 gal), which represents a compact, real-world TES solution suitable for building energy storage. The results showed consistent thermal stability of the PCM over 200 cycles, and the supercooling temperature remained within 0.2 °C, which was not detected in smaller-scale characterization methods. Additionally, the macroscale testing methodology of the PCM revealed that the TES is able to charge and discharge stored latent energy within 2 h under a temperature differential of 16.67 °C measured between the inlet water temperature and the phase transition temperature of the PCM. The proposed multiscale PCM characterization method provides a systematic basis for comparing important thermal storage properties while also investigating the scalability, reliability and integration challenges in large scale TES applications.

Latent heat↗
DOE OSTI2026

Chemical ionization mass spectrometry utilizing benzene cations for measurements of volatile organic compounds and nitric oxide

We evaluate the capability of chemical ionization mass spectrometry (CIMS) using benzene cations as reagent ions (benzene CIMS) for detecting atmospheric trace gases. We characterize the ionization pathways and product ion distributions for 27 analytes spanning diverse chemical classes. To interpret the complex ion chemistry involving two reagent ions (C 6 H$^{+}_{6}$ and (C 6 H 6 )$^{+}_{2}$) and multiple ionization pathways (charge transfer, proton transfer, adduct formation, and hydride abstraction), we introduce a thermodynamics-based framework that classifies analytes into three categories based on their ionization energy (IE), relative to those of benzene monomer (9.24 eV) and dimer (8.69 eV). Each class exhibits distinct ionization mechanisms and product ions. Analytes with IE smaller than 8.69 eV (low IE) undergo charge transfer with both reagent ions; analytes with IE between 8.69 and 9.24 eV (mid IE) undergo charge transfer with C 6 H$^{+}_{6}$ and potential adduct formation with (C 6 H 6 )$^{+}_{2}$; analytes with IE larger than 9.24 eV (high IE) could undergo adduct formation, proton transfer, or hydride abstraction. Analytes within each class also show similar sensitivity, enabling sensitivity estimation for compounds lacking calibration standards. In addition to volatile organic compounds (VOCs), benzene CIMS detects nitric oxide (NO) with a detection limit of 5 pptv for 1 min integration time, exceeding the performance of most commercial NOx analyzers. Field deployments in Chicago and St. Louis demonstrate good agreement with reference NO measurements. Isoprene measurements show good agreement with a co-located gas chromatography–photoionization detector (GC-PID) in St. Louis, but exhibit substantial positive bias in Chicago, likely due to interferences from anthropogenic VOCs in the polluted urban environment. These results highlight the potential of benzene CIMS for concurrent measurements of NO, VOCs, and their oxidation products using a single instrument, while also underscoring challenges in complex atmospheric conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

The final WaZP galaxy cluster catalog of the Dark Energy Survey and comparison with SZE data

In this work, we present and characterize the galaxy cluster catalog detected by the WaZP cluster finder, which is not based on red-sequence identification, on the full six years of observations of the Dark Energy Survey (DES-Y6). The full catalog contains over 400k detected clusters with richnesses, Ngals, above 5 and that reach redshifts up to 1.3. We also provide a version of the catalog where the observation depth and richness computation are homogenized to be used for cosmology, containing 33k rich (Ngals >25) clusters. We compare our results with the previous WaZP catalog obtained from the DES first-year data release (DES-Y1). We find that essentially all clusters within the common footprint and depth limit are recovered. The deeper observations on DES-Y6 and the more complete available spectroscopic redshift sample lead to improvements in the redshifts of the clusters, resulting in an average scatter of 1.4% and offset of 0.2%. The optical clusters are also cross-matched with Sunyaev Zel'dovich Effect (SZE) cluster samples detected by the South Pole Telescope (SPT) and the Atacama Cosmology Telescope (ACT). We find that essentially all SZE clusters with reasonable overlapping footprint have a corresponding WaZP cluster. Conversely, 90% of the optical detections with richness greater than 150 have a counterpart in the deeper regions of the SZE surveys. Based on cross-match with the SZE catalogs, we also find that 15-20% of the SZE matched systems have more than one possible WaZP counterpart at the same redshift and within the SZE R500c, indicating possible interacting or unrelaxed systems. Finally, given the optical and SZE beams, WaZP and SZE centerings are found to be consistent. A more detailed study of the SZE-WaZP mass-richness relation will be presented in a separate paper.

Benoist, C. [OCA, Nice, Lab. Lagrange; LIneA, Rio ↗
DOE OSTI2026

Fluorescence Signatures of Rare Earth Metals during Precipitation in Various Conditions

Fluorescence spectroscopy is a widely used sensor methodology that analyzes light emitted from a compound or element as it decays from an excited state. This technique is very sensitive and selective, which is ideal to characterize analytes at lower limits of detection. Key example targets of significant industry and research interest include rare earth elements (REEs) such as dysprosium (Dy) and europium (Eu). These are widely used in advanced technologies including semiconductors, electric vehicle motors, lasers, and permanent magnets. Identifying new sources and responsible reutilization of REEs is essential, and new approaches to extract and recycle REEs could be notably enhanced through the integration of on-line sensors. The sensors can support faster process design, informed scale-up, and cost-effective deployment. This study covers the initial exploration of applying fluorescence-based on-line monitoring to REEs within a precipitation process. This study demonstrates the successful scale-up of a fluorescence -based sensing approach, from stationary cuvettes and small-volume microfluidic devices to continuous flow systems operating at the bench scale (10-25mL). This work also provides initial insight into the challenges of signal’s effects and utility within a turbid environment. Using a modular design for monitoring flowing solutions in a flow tube, fluorescence can be characterized for a variety of analytical targets. In this study, detection performance parameters between the cuvette and flow tube system were compared. Additionally, the response of Dy during precipitation by sodium bicarbonate in the two measurement designs was explored. This letter represents a starting point to bridge the gap between traditional fluorescence sensor measurements in a cuvette to future developments that explore the ability to integrate fluorescence sensors into extraction and separation processes at industrially relevant scales.

fluorescence↗
DOE OSTI2024

Proton Quenching in Rare-Earth Inorganic Scintillators: GAGG:Ce and YSO:Ce

Scintillator detectors are an integral component of radiation detection systems for a variety of applications such as medical imaging, accelerator diagnostics, and space science. Typically, a scintillator detector’s response is characterized using gamma sources to understand the detection response to different types of radiation, including charged particle detection. However, there exists a nonlinearity of the amount of light produced from an incident gamma ray of specific energy and the light produced from an incident charged particle of the same energy. This important effect, known as quenching, must be accounted for to interpret energies from charged particles incident on detectors. In this article, we present results of quenching parameterization for two types of cerium-doped inorganic scintillators, Y2SiO5:Ce (YSO:Ce) and Gd3Al2Ga3O12:Ce (GAGG:Ce). We measured the light output from incident proton energies from 1 to 25 MeV using a 3-MV tandem accelerator and two reactions: Au(p,p)Au and 3He(d,p)⁴He. Using gamma-ray sources to calibrate the detectors, we compared the measured electron-equivalent energy versus the incident energy expected. Using an adaptation of the Birks semi-empirical formula, we extracted the Birks parameter (kB) to understand quenching. For one of the GAGG:Ce samples, the kB parameter of 0.0072 [g cm-2 MeV-1] is comparable to a similar study where the value of kB was 0.0065 [g cm-2 MeV-1]. For YSO:Ce, no other kB values were found in the literature. Three different types of GAGG:Ce were used to collect measurements of kB as a function of dopant concentration.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Characterization of dangling bond defects at the crystalline Si/SiO x interface in a polycrystalline Si passivating contact solar cell at room temperature with electrically detected magnetic resonance spectroscopy

Monocrystalline silicon solar cells can achieve photoconversion efficiencies exceeding 26%; however, performance-limiting defects that trap carriers continue to be a challenge. In this work, we have characterized Si solar cells with tunneling SiO x /polycrystalline-Si (poly-Si) passivating contacts (TOPCon) on As-doped Czochralski Si wafers with electrically detected magnetic resonance (EDMR) spectroscopy. We fabricated 2 × 20 mm 2 TOPCon-like mini solar cells with edge passivation alongside larger 4 cm 2 sister cells and obtained similar device characteristics. We performed EDMR spectroscopy at 300 K on two minicells with different degrees of surface passivation based on the recombination parameter, J o , values of 40 and 310 fA/cm2. We optimized the resolution and the signal-to-noise ratio of the EDMR response of the minicells by varying the forward bias voltage and the magnetic field modulation amplitude. We detect two distinct signals with EDMR spectroscopy, an axial-like signal at g = 2.009, 2.0087, and 2.0015, and an isotropic signal at g = 2.0024, which we attribute to Si dangling bonds (P b0 and P b centers) and boron–oxygen related defects, respectively, at or near the c-Si/SiO x interface. The EDMR signals were lower for the cell with a lower value of J o , while the ratio of the two defect populations was very similar. The EDMR signal increases with forward bias but drops to zero at bias voltages >0.5 V, consistent with interface defects within or near the boron-doped emitter depletion region. Our study demonstrates a method to fabricate minicells that can be characterized with EDMR spectroscopy to detect industrially relevant defects in TOPCon cells.

14 SOLAR ENERGY↗
DOE OSTI2026

Multinuclear Solid-State NMR and NMR Crystallography of Solid Forms of Creatine and Creatinine

Creatine is a performance-enhancing supplement with two widely available commercial solid forms, namely, creatine monohydrate (creatine·H 2 O) and creatine HCl, the latter of which does not have a reported crystal structure. Moreover, commercial formulations of creatine may contain creatinine, an undesired impurity phase resulting from the self-cyclization of creatine during manufacturing. Therefore, reliable methods for characterizing the different solid forms of creatine and detecting the presence of creatinine are essential. Herein, we address these challenges using 13 C, 15 N, and 35 Cl solid-state NMR (SSNMR) spectroscopy to obtain distinct spectral fingerprints for creatine·H 2 O and creatine HCl, along with creatinine and creatinine HCl. The acquisition of these SSNMR spectra offers a robust approach for both the rapid characterization of each solid form and the detection of the impurity phases. Additionally, quadrupolar NMR crystallography-guided crystal structure prediction (QNMRX-CSP) was applied for the de novo crystal structure determination of creatine HCl, which was validated by the subsequently determined single-crystal X-ray diffraction (SCXRD) structure. Finally, to investigate the relationship between NMR parameters and structural features, 13 C and 15 N chemical shifts and 35 Cl electric field gradient (EFG) tensors were computed from geometry-optimized structures of the four solid forms by using dispersion-corrected DFT-D2* methods. Finally, this integrative approach offers a powerful framework for advancing the structural understanding and quality control of creatine-based supplements and next-generation formulations, as well as a wide range of other solid pharmaceuticals and nutraceuticals.

NMR↗
DOE OSTI2026

Block Island Acoustic Data Analysis and Peak Detection Tools

This dataset contains acoustic signal analysis tools and processed datasets for pile driving noise characterization during Block Island Wind Farm construction (October 25, 2015), including peak detection algorithms, signal extraction methods, and visualization products for multi-channel hydrophone array data.

17 WIND ENERGY↗
DOE OSTI2025

Multiscale Characterization of Additive Manufacturing Components with Computed Tomography, 3D X-ray Microscopy, and Deep Learning

Additive manufacturing (AM) facilitates the creation of complex-geometry parts, driving advancements in lightweight aerospace components, high-efficiency engine cooling channels, and customized medical implants. However, ensuring the quality and reliability of AM parts remains challenging due to internal defects, surface irregularities, porosity, and residual trapped powder, which are often inaccessible to traditional inspection methods. Recent developments in X-ray computed tomography (XCT) and 3D X-ray microscopy (XRM), particularly systems equipped with resolution-at-a-distance (RaaD™) capabilities, enable high-resolution, non-destructive evaluation of AM components across multiple scales, from sub-micrometer to macroscopic levels. This paper explores modern XCT and XRM techniques for multiscale characterization of AM parts, focusing on their ability to detect and analyze defects such as porosity, cracks, inclusions, and surface roughness, while offering insights into defect formation mechanisms, material properties, and process-induced variations. The integration of deep learning (DL) frameworks, including Simurgh, DeepRecon, and DeepScout, enhances XCT/XRM workflows by reducing scan times, improving resolution recovery, and enabling accurate defect detection even with limited projection data. These DL-based methods overcome limitations of traditional reconstruction techniques, enabling faster, more reliable characterization of dense materials like Inconel 718 and novel alloys such as AlCe. Applications include process parameter optimization, high-throughput quality control, and multistage AM process evaluation, with DL-enhanced workflows accelerating analysis times from weeks to days. Correlative imaging approaches further validate XCT and XRM data against scanning electron microscopy (SEM) images of physically sectioned samples, confirming the accuracy of DL-based reconstructions and enabling comprehensive defect analysis. While challenges remain in generalizing DL models to diverse materials and imaging conditions, improvements in resolution, noise reduction, and defect detection highlight the transformative potential of these methods. This multiscale and correlative approach enables precise identification and correlation of microstructural features with the overall performance of AM components. By integrating advanced XCT, XRM, and DL techniques, this paper demonstrates a significant leap forward in AM characterization, offering valuable insights into the relationships between processing parameters, microstructure, and part performance, and driving innovations that enhance the quality and reliability of AM products for demanding industrial applications.

Additive manufacturing↗
DOE OSTI2025

A fault-tolerant neutral-atom architecture for universal quantum computation

Quantum error correction (QEC) is essential for the realization of large-scale quantum computers. However, owing to the complexity of operating on the encoded ‘logical’ qubits, understanding the physical principles for building fault-tolerant quantum devices and combining them into efficient architectures is an outstanding scientific challenge. Here we use reconfigurable arrays of up to 448 neutral atoms to implement the key elements of a universal, fault-tolerant quantum processing architecture and experimentally explore their underlying working mechanisms. We first use surface codes to study how repeated QEC suppresses errors, demonstrating 2.14(13)x below-threshold performance in a four-round characterization circuit by leveraging atom loss detection and machine learning decoding. We then investigate logical entanglement using transversal gates and lattice surgery and extend it to universal logic through transversal teleportation with three-dimensional [[15,1,3]] codes, enabling arbitrary-angle synthesis with polylogarithmic overhead. Finally, we develop mid-circuit qubit reuse16, increasing experimental cycle rates by two orders of magnitude and enabling deep-circuit protocols with dozens of logical qubits and hundreds of logical teleportations with [[7,1,3]] and high-rate [[16,6,4]] codes while maintaining constant internal entropy. Our experiments show key principles for efficient architecture design, involving the interplay between quantum logic and entropy removal, judiciously using physical entanglement in logic gates and magic state generation, and leveraging teleportations for universality and physical qubit reset. These results establish foundations for scalable, universal error-corrected processing and its practical implementation in neutral atom systems.

atomic and molecular physics↗
DOE OSTI2025

Ultraviolet Fluorescence Imaging for Photovoltaic Module Metrology: Best Practices and Survey of Features Observed in Fielded Modules

As the photovoltaics (PV) industry grows in sophistication, so must the extent to which systems are characterized. UV Fluorescence (UVF) imaging is a valuable, easy-to-perform, high-throughput, nonintrusive technique for characterizing modules in the field and in the lab. However, UVF is still a relatively new technique, and many in the PV industry are still unaware of its potential. We provide a guideline for obtaining, processing, and interpreting UVF images. We have provided a list of considerations for imaging hardware and settings, a suggested pipeline for image processing, and details on a survey of features shown in UVF images. As a result, a new database with UVF images of 7190 modules and another database curated by BrightSpot Automation are publicly available.

14 SOLAR ENERGY↗
DOE OSTI2026

Characterizing skyrmion flow phases with principal component analysis

Principal component analysis (PCA) is a powerful method that can identify patterns in large, complex data sets by constructing low-dimensional order parameters from higher-dimensional feature vectors. There are increasing efforts to use space-and-time-dependent PCA to detect transitions in nonequilibrium systems that are difficult to characterize with equilibrium methods. Here, we demonstrate that feature vectors incorporating the position and velocity information of driven skyrmions moving through random disorder permit PCA to resolve different types of disordered skyrmion motion as a function of driving force and the ratio of the Magnus force to the dissipation. Since the Magnus force creates gyroscopic motion and a finite Hall angle, skyrmions can exhibit a greater range of flow phases than what is observed in overdamped driven systems with quenched disorder. We show that in addition to identifying previously known skyrmion flow phases, PCA detects several additional phases, including different types of channel flow, moving fluids, and partially ordered states. Guided by the PCA analysis, we further characterize the disordered flow phases to elucidate the different microscopic dynamics and show that the changes in the PCA-derived order parameters can be connected to features in bulk transport measures, including the transverse and longitudinal velocity-force curves, differential conductivity, topological defect density, and changes in the skyrmion Hall angle as a function of drive. We discuss how asymmetric feature vectors can be used to improve the resolution of the PCA analysis, and how this technique can be extended to find disordered phases in other nonequilibrium systems with time-dependent dynamics.

36 MATERIALS SCIENCE↗