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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

High‐speed 4‐dimensional scanning transmission electron microscopy using compressive sensing techniques

Abstract Here we show that compressive sensing allows 4‐dimensional (4‐D) STEM data to be obtained and accurately reconstructed with both high‐speed and reduced electron fluence. The methodology needed to achieve these results compared to conventional 4‐D approaches requires only that a random subset of probe locations is acquired from the typical regular scanning grid, which immediately generates both higher speed and the lower fluence experimentally. We also consider downsampling of the detector, showing that oversampling is inherent within convergent beam electron diffraction (CBED) patterns and that detector downsampling does not reduce precision but allows faster experimental data acquisition. Analysis of an experimental atomic resolution yttrium silicide dataset shows that it is possible to recover over 25 dB peak signal‐to‐noise ratio in the recovered phase using 0.3% of the total data. Lay abstract : Four‐dimensional scanning transmission electron microscopy (4‐D STEM) is a powerful technique for characterizing complex nanoscale structures. In this method, a convergent beam electron diffraction pattern (CBED) is acquired at each probe location during the scan of the sample. This means that a 2‐dimensional signal is acquired at each 2‐D probe location, equating to a 4‐D dataset. Despite the recent development of fast direct electron detectors, some capable of 100kHz frame rates, the limiting factor for 4‐D STEM is acquisition times in the majority of cases, where cameras will typically operate on the order of 2kHz. This means that a raster scan containing 256^2 probe locations can take on the order of 30s, approximately 100‐1000 times longer than a conventional STEM imaging technique using monolithic radial detectors. As a result, 4‐D STEM acquisitions can be subject to adverse effects such as drift, beam damage, and sample contamination. Recent advances in computational imaging techniques for STEM have allowed for faster acquisition speeds by way of acquiring only a random subset of probe locations from the field of view. By doing this, the acquisition time is significantly reduced, in some cases by a factor of 10‐100 times. The acquired data is then processed to fill‐in or inpaint the missing data, taking advantage of the inherently low‐complex signals which can be linearly combined to recover the information. In this work, similar methods are demonstrated for the acquisition of 4‐D STEM data, where only a random subset of CBED patterns are acquired over the raster scan. We simulate the compressive sensing acquisition method for 4‐D STEM and present our findings for a variety of analysis techniques such as ptychography and differential phase contrast. Our results show that acquisition times can be significantly reduced on the order of 100‐300 times, therefore improving existing frame rates, as well as further reducing the electron fluence beyond just using a faster camera.

Robinson, Alex W.↗
DOE OSTI2026

Experimental considerations and applications for time-resolved impedance on silicon-anode battery systems

Dynamic electrochemical impedance spectroscopy (dEIS) utilizes a superimposed multi-sinusoidal waveform and enables temporally resolved investigations on various electrochemical processes; however, the signal-to-noise ratio must be maximized while retaining linearity and stationarity within the system. In the present work, we probe the impact of the waveform’s total amplitude as well as the waveform and phase profiles. The equal amplitude multi-sinusoidal waveform with 35 mV total amplitude (<1 mV per frequency) and random phase profile exhibits the lowest impedance noise. This input signal is sufficient in avoiding the high frequency signal attenuation from the potentiostat’s low-pass filter. Additionally, we demonstrate the optimized dEIS waveform’s utility in investigating surface passivation within thin-film and composite silicon (Si) anodes. Within a two-electrode Si-lithium metal coin cell, the charge transfer resistance (RCT) associated with alloying kinetics dominates the overall impedance. RCT increases with state of charge indicating a kinetic bottleneck at higher lithiation states. To explore this further, we utilize a three-electrode Si-LiNi0.8Mn0.1Co0.1O2 pouch cell to deconvolute the Si impedance contributions. The evolution of the solid electrolyte interphase (SEI) and charge transfer resistances correlate to specific Li–Si alloy phases. We attribute this to the influence of Si particle volume expansion on SEI instabilities and a kinetic bottleneck at higher lithiation states.

Lam, Steven [ORNL]↗
DOE OSTI2025

Comprehensive defect evaluation of advanced nuclear fuels using high-resolution acoustic signals and optimized sensor separation

Graphite pebble composite structures based on TRistructural-ISOtropic (TRISO) particles are being developed as core nuclear fuels in advanced power reactors, promising safe operation at increased temperatures. Ensuring the structural integrity of these nuclear fuels requires comprehensive and accurate non-destructive evaluation (NDE) techniques to characterize defects and damage in the pebbles. However, traditional acoustic evaluation methods face limitations in defect characterization due to the highly attenuative, and geometrically and compositionally complex nature of these structures. This study proposes an improved acoustic NDE technique for accurate detection and classification of anticipated relevant defects and damage in graphite pebbles using high-resolution acoustic signals and optimized transmit-receive sensor networks. The proposed approach utilizes a triangular three-sensor network as the base unit, comprising three transmit-receive sensors. The sensor separation distance, as well as acoustic excitation center frequency, pulse-width, and bandwidth are optimized to enhance spatial resolution and improve signal-to-noise ratio, enabling effective characterization of the smallest size and widest range of defects in pebbles. Furthermore, the use of the triangular sensor configuration instead of a more conventional transmit-receive sensor pair expands the inspection region from a one-dimensional linear path to a two-dimensional area, increasing spatial coverage. To mitigate challenges associated with processing of complex acoustic signals arising from high-frequency, high-bandwidth excitation in these structures, a machine-learning-based signal processing algorithm is integrated with the sensor network. In the machine-learning-based algorithm, multi-domain features are extracted from the acoustic signals to capture intricate signal characteristics, significantly improving defect identification and classification compared to traditional approaches. The proposed acoustic NDE technique offers considerable promise for practical and reliable defect/damage diagnostics of advanced nuclear pebble fuels.

42 ENGINEERING↗
DOE OSTI2024

Co-existence of Heterogeneous Wireless Networks in 2.4 GHz and 5 GHz Spectrum

To achieve automation across different applications, next-generation nuclear power plants are beginning to leverage advanced wireless technologies. The deployment of these wireless technologies is a salient need for modernizing the existing nuclear plants. A “one-size-fits-all” solution cannot be adopted since wireless technologies are selected according to specific application needs, quality of service, and economic restrictions. To balance the trade-off between technical and economic requirements, a multi-band heterogeneous wireless network architecture is needed. However, the co-existence of these multi-band wireless technologies poses numerous challenges. Due to factors including dissimilarity in channel access mechanisms, transmit power levels, distance between nodes, and interference among co-existing solutions, performance can be seriously degraded, leading to very low signal-to-noise ratio. This report builds on our previous study, "Experimental Evaluation of Interference in 2.4 GHz Wireless Network," which analyzed the performance of wireless communication technologies such as Wi-Fi, Zigbee, and Bluetooth co-existing within the 2.4 GHz band. We now extend this study by developing a new upper-layer approach that uses rate control to create temporary opportunities for signal transmission while using the shared band. Unlike existing work in the literature, our approach does not require modifications at the link or physical layers of the network. Further, we extend our work to explore the co-existence of Wi-Fi and fifth-generation (5G) in the 5 GHz unlicensed spectrum, using both experiments and simulations. This report provides a technical foundation for understanding the operational designs of Wi-Fi and 5G in the unlicensed band and evaluates their performance when these networks co-exist. Our findings show that the performance of 5G can be improved by controlling the Wi-Fi’s packet rate at the upper layer.

42 ENGINEERING↗
DOE OSTI2026

A Pulsar-Inspired Timing Framework for Power System: Optimization and Performance Evaluation

Due to their excellent stability, neutron pulsar stars are considered promising candidate timing sources for power system applications. However, the complexity of pulsar signals necessitates advanced processing algorithms to provide accurate timing references. This paper presents the foundational framework for pulsar signal processing, serving as the basis for further optimization. To enhance the timing accuracy and computation efficiency in pulsar period searches, three algorithms are proposed as the initial optimization step: wavelet de-noising, fast folding, and cross-correlation for profile evaluation. Wavelet de-noising improves signal-to-noise ratio (SNR) by 36%–70%. Fast folding reduces computation time from hundreds of seconds to mere milliseconds. Cross-correlation works better than traditional SNR-based methods by effectively identifying the optimal period. The performance of the proposed algorithms is evaluated using observation data from telescopes. Together, these algorithms significantly improve pulsar timing performance, reducing the error of the Pulse Per Second (PPS) signal from hundreds to tens of microseconds.

Wu, Ori [ORNL] (ORCID:0000000326723410)↗
DOE OSTI2024

Three Photon Excited Image Scanning Microscopy for in-Depth Super-Resolution Studies of Biological Samples

Multiphoton laser scanning microscopy is a powerful tool for deep imaging of thick biological samples. Image scanning microscopy (ISM) has demonstrated significant improvements in the signal-to-noise ratio in confocal laser scanning microscopy, while at the same time improving upon the effectively attainable resolution. Two-photon excitation (2PE), combined with ISM, has been shown to allow for deep tissue imaging with enhanced resolution compared to 2PE microscopy. Three-photon excitation (3PE) has enabled record imaging depth and contrast for multiphoton imaging, due to the superior suppression of out-of-focus signal generation. In this paper, we demonstrate super-resolution 3PE ISM. This is achieved using a single-photon avalanche detector array, and 1040-nm pulses for 3PE of blue fluorescence. This method enables subdiffraction limited resolution imaging of biological samples stained with blue fluorescent markers, such as mouse myocardial and spinal cord tissues stained with 4 ′ , 6 -diamidino-2-phenylindole. Deconvolution improves the resolving power further and allows for imaging with better than λ / 8 resolution with respect to the 3PE wavelength λ . With the ISM pixel reassignment procedure, we demonstrate a resolution enhancement of ∼ 1.6 laterally, compared to the resolution attained using a photomultiplier tube in a non-descanned detection arrangement, and a factor of ∼ 1.8 enhancement in axial resolution. The experimentally measured three-dimensional point spread function volume is shrunk ∼ 4.4 -fold, which is close to the theoretically expected enhancement. Published by the American Physical Society 2024

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Wilson loops with neural networks

Wilson loops are essential objects in QCD and have been pivotal in scale setting and demonstrating confinement. Various generalizations are crucial for computations needed in effective field theories. In lattice gauge theory, Wilson loop calculations face challenges, including excited-state contamination at short times and the signal-to-noise ratio issue at longer times. To address these problems, we develop a new method by using neural networks to parametrize interpolators for the static quark-antiquark pair. We construct gauge-equivariant layers for the network and train it to find the ground state of the system. The trained network itself is then treated as our new observable for the inference. Our results demonstrate a significant improvement in the signal compared to traditional Wilson loops, performing as well as Coulomb-gauge Wilson-line correlators while maintaining gauge invariance. Additionally, we present an example where the optimized ground state is used to measure the static force directly, as well as another example combining this method with the multilevel algorithm. Finally, we extend the formalism to find excited-state interpolators for static quark-antiquark systems. To our knowledge, this work is the first study of neural networks with a physically motivated loss function for Wilson loops.

Bellscheidt, Verena [Massachusetts Inst. of Techno↗
DOE OSTI2026

Spatiotemporal Learning in Power Modules: Wavelet-Enhanced Forecasting of Thermomechanical Degradation

Detecting internal defects in power electronics packages is critical for their performance and reliability, especially under extreme operating conditions, as these defects can lead to catastrophic failure if not properly addressed. Confocal scanning acoustic microscopy (C-SAM) plays a key role in the nondestructive evaluation of bond layer degradation within a power electronics package by detecting defects such as delamination, voids, and cracks. However, accurately quantifying and predicting these defects from C-SAM images remains a significant challenge due to the low noise-to-signal ratio, which typically arises from both imaging process and bond patterns itself. In this paper, we explore machine learning strategies for processing C-SAM images and providing predictive models of defect growth. We use C-SAM images of sintered copper and sintered silver samples, which are obtained under accelerated thermal experiments, as the representative dataset for our study. We investigate the effect of Fourier transforms and wavelet transforms on these datasets to remove high-frequency noise and address noise across multiple scales with histogram equalization to enhance the contrast and improve the visibility of defects. As a result, defect boundaries can be clearly distinguished, enabling more accurate tracking of their growth over time. We then employ different time-series forecasting algorithms on the denoised images to formulate an image-based lifetime prediction model. Statistical models and deep-learning techniques are trained on images obtained in the early stages of thermal shock, and defect growth in the later stages is predicted. Our work serves as a preliminary attempt to improve the accuracy of lifetime prediction models of power electronics packages, which is critical under extreme operating environments.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Mathematical Morphological Filtering with a Self-Adaptive Reconstruction Technique and Application to Local Seismic Data

Recorded seismic data are generally contaminated by noise from different sources, which masks the signals of interest. In the seismology community, frequency filtering (FF) is the standard method for noise suppression. However, when the signal of interest and noise share the same frequency band, the latter cannot be filtered out without infringing on the former. We implemented a noise suppression approach based on the mathematical morphology theorem. The method involves compound operations of dilation and erosion using structuring elements of varying lengths and decomposes an input noisy waveform into several time functions with differing characteristics. Further, the filtered waveform is constructed from the time functions using a self-adaptive reconstruction technique. Application to a data set of >4700 local waveforms suggests that the implemented mathematical morphological filtering (MMF) approach is efficient for data with low signal-to-noise ratio (SNR) and significantly outperforms FF in that SNR range. For most of the dataset, FF, machine learning (ML) denoising, and continuous wavelet transform (CWT) thresholding result in higher SNR values compared with the MMF method. However, for ~42% of the waveforms, MMF outperforms FF, and the SNR gain achieved with MMF is as large as ~23 dB. Compared to ML denoising and CWT thresholding, this proportion drops to only ~10%–14%. Our results suggests that in an operational setting, MMF cannot replace the other noise suppression methods; however, signal detection can be improved if MMF is used to supplement them in some scenarios. MMF could help detect signals in problematic low-SNR data, which are currently being missed particularly when using FF alone.

58 GEOSCIENCES↗
DOE OSTI2025

Distinguishing prompt-collapse binary neutron star mergers from binary black Holes: Tidal effects and remnant properties

We study the properties of remnants formed in prompt-collapse binary neutron star mergers. We consider nonspinning neutron star binaries over a range of total masses and mass ratios across a set of 22 equations of state, totaling 107 numerical relativity simulations. We report the final mass and spin of the systems (including the accretion disk and ejecta) to be constrained in a narrow range—0.98 ≲ 𝑀 𝑓 /𝑀 ≲ 0.99 for the mass and 0.85 ≲ 𝑎 𝑓 ≲ 0.95 for the dimensionless spin—regardless of the binary configuration and matter effects. This sets them apart from binary black hole merger remnants. We assess the detectability of the postmerger signal in a future 40 km Cosmic Explorer observatory and find that the signal-to-noise ratio in the postmerger of an optimally located and oriented binary at a distance of 100 Mpc can range from <1 to 8, depending on the binary configuration and equation of state, with a majority of them greater than 4 in the set of simulations that we consider. We also consider the distinguishability between prompt-collapse binary neutron star and binary black hole mergers with the same masses and spins. We find that Cosmic Explorer will be able to distinguish such systems primarily via the measurement of tidal effects in the late inspiral. Neutron star binaries with reduced tidal deformability $\tilde{Λ}$ as small as ∼ 3.5 can be identified up to a distance of 100 Mpc, while neutron star binaries with $\tilde{Λ}$ ∼ 22 can be identified to distances greater than 250 Mpc. This is larger than the distance up to which the postmerger will be visible. Finally, we discuss the possible implications of our findings for the equation of state of neutron stars from the gravitational wave event GW230529.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Tailoring spectral properties for entangled photon generation

The linear intensity scaling of entangled two-photon absorption (ETPA) offers a fundamental mechanism to enable nonlinear optical spectroscopy and microscopy under a substantially lower excitation power than is currently feasible. However, the long data acquisition time and low signal-to-noise ratio in reported ETPA-based spectroscopic and microscopic studies prevent its widespread application. To gain the full potential of this novel quantum light approach, it is essential to optimize entangled photon generation for significantly enhanced ETPA responses. Here, we report a new quantum light source by combining entangled photon generation with free-space femtosecond pump-pulse shaping. Here, through measurements of singles and coincidence counts by varying the patterns applied to a spatial light modulator to control the spectral widths of the pump pulses, we reveal strong dependence of the singles and coincidence count rates as well as their ratios on the spectral widths of pump pulses. An optimal spectral width for the highest ratios between the coincidence photon and the signal or idler photon count rates is also determined. Identification of such optimal spectral widths for entangled photon generation in the presence of postgeneration spectral selection makes this quantum light source a promising choice for ETPA-based spectroscopy and imaging.

Photon pairs & parametric down-conversion↗
DOE OSTI2026

Validation of 266 nm UV Raman thermometry using the alpha-to-beta quartz transition

Ultraviolet Raman scattering is a promising diagnostic for temperature measurements relevant to dynamic compression experiments, where improved signal strength and reduced background are critical. In this work, we experimentally validate Raman thermometry at 266 nm using crystalline quartz heated through the α to β phase transition in a tube furnace. Quartz provides a useful benchmark because of its well-characterized transition temperature near 846 K at ambient pressure. Temperatures inferred from the Stokes to anti-Stokes intensity ratio are compared with thermocouple measurements and with the observed phase transition. Single-shot Raman temperatures track the thermocouple closely, with an empirical single-shot scatter of approximately ±15 K under the present conditions. Temporal averaging reduces shot-to-shot scatter and improves agreement between the Raman temperatures and thermocouple readings to within approximately 8 K, while the transition is identified within 5 K of the accepted value. Measurements are performed using the fourth harmonic of a nanosecond pulsed Nd:YAG laser at 266 nm. The shorter excitation wavelength provides enhanced Raman scattering efficiency and reduced visible background relative to conventional visible excitation. Comparison with 532 nm Raman measurements acquired in the same experimental geometry demonstrates substantially improved signal-to-noise ratio for the UV configuration. These results establish 266 nm Raman thermometry as a reliable and accurate temperature diagnostic under controlled heating conditions and provide a quantitative benchmark for future application in dynamic compression and shock physics experiments.

Chemistry - Chemical explosives↗
DOE OSTI2025

Approaching the Lower Temporal Limit of Laser‐Produced Plasma Sources for Table‐Top Soft X‐Ray NEXAFS Measurements

Abstract The increasing popularity of time‐resolved X‐ray absorption measurements for understanding dynamics in molecular and material systems has led to many advances in table‐top sources for pulsed X‐rays. We report on a table‐top laser‐produced plasma (LPP) source that can perform soft X‐ray (SXR), near‐edge X‐ray absorption fine structure (NEXAFS) measurements using a laser source with 23 ps pulse duration. The spectrometer's key specifications, such as brilliance, resolution, and stability, are characterized against the more commonly used longer‐pulse‐duration LPP sources. The 23 ps laser produced approximately an order of magnitude weaker SXR flux than the 8 ns laser for a higher power density due to the smaller total energy absorbed by the plasma. The increased repetition rate, as well as the use of a high line‐density X‐grating, and a self‐referencing scheme still allowed for NEXAFS measurements of Si 3 N 4 and TiO 2 thin films with 2.5 minute acquisition times, a resolving power of E/ΔE=424, and a signal‐to‐noise ratio of 100. It was observed that degradation of the gas jet nozzle led to long‐term instability of the source, which can be remediated using alternative nozzle designs. This work demonstrates the feasibility of achieving higher temporal resolution in future time‐resolved X‐ray absorption measurements using table‐top LPP sources.

Nimlos, Danika [Division of Chemistry and Chemical↗
DOE OSTI2025

Sensing Few Electrons Floating on Helium with High-Electron-Mobility Transistors

We report on low-frequency measurements of few electrons floating on superfluid helium using a bespoke cryogenic cascode amplifier circuit built with off-the-shelf GaAs high-electron-mobility transistors (HEMTs). We integrate this circuit with a charge-coupled device (CCD) to transport the electrons on helium and characterize its performance. Here, we show that this circuit has a signal-to-noise ratio (SNR) of ~ 2 $\frac{e}{√Hz}$ at 102 kHz, an order of magnitude improvement from previous implementations, and provides a compelling alternative to few electron sensing with high-frequency resonators.

Charge-Coupled Devices↗
DOE OSTI2026

The Interstellar Mapping And Acceleration Probe High Energy (IMAP-Hi) Neutral Atom Imager

The IMAP-Hi Energetic Neutral Atom (ENA) Imager on NASA’s Interstellar Mapping and Acceleration Probe (IMAP) mission (McComas et al. 2018a, 2025) is designed to measure ENAs from the global interaction between the heliosphere and the local interstellar medium (LISM). These ENAs are initially plasma ions of solar wind origin that are neutralized by charge exchange with the cold neutral atoms of LISM that freely flow through the heliosphere-LISM interaction region. IMAP-Hi consists of two identical single-pixel sensors, each covering the ENA spectral range from 0.44 keV to 15.6 keV over nine contiguous energy passbands and having an approximately conical field-of-view (FOV) of 4.1o full width at half maximum (FWHM). The Hi-45 sensor points 45o relative to the spacecraft spin axis from the antisunward direction; each spacecraft spin, it measures ENA intensity over a circular swath with half-cone angle 45o centered on the ecliptic plane. The Hi-90 sensor points 90o relative to the spin axis; each spacecraft spin, it measures ENA intensity over a great circle in the sky, sampling both the north and south ecliptic poles. As the IMAP spin vector is re-pointed daily toward the Sun, the ecliptic longitude of the swaths moves daily by ∼1o such that a full sky map is acquired by Hi-90 every six months and a complete low latitude (−45o to +45o) map is acquired by Hi-45 annually. The IMAP-Hi sensor design has direct heritage from the IBEX-Hi imager on the Interstellar Boundary Explorer (IBEX) mission, with substantial improvements in energy range, energy resolution, angular resolution, signal-to-noise ratio, and, for ecliptic latitudes within ±45o, temporal resolution and exposure time. The global ENA maps acquired by IMAP-Hi partially overlap in energy and viewing with the ENA maps acquired by the IMAP-Lo and IMAP-Ultra ENA imagers, which we combine to answer fundamental questions about the structure and dynamics of the interaction of the heliosphere and the LISM.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

ESM data downscaling: a comparison of super-resolution deep learning models

Abstract Climate projections at fine spatial resolutions are required to conduct accurate risk assessment for critical infrastructure and design adaptation planning. Generating these projections using advanced Earth system models (ESM) requires significant computational resources. To address this issue, various statistical downscaling techniques have been introduced to generate fine-resolution data from coarse-resolution simulations. In this study, we evaluate and compare five deep learning-based downscaling techniques, namely, super-resolution convolutional neural networks, fast super-resolution convolutional neural network ESM, efficient sub-pixel convolutional neural network, enhanced deep residual network (EDRN), and super-resolution generative adversarial network (SRGAN). These techniques are applied to a dataset generated by the Energy Exascale Earth System Model (E3SM), focusing on key surface variables such as surface temperature, shortwave heat flux, and longwave heat flux. Models are trained and validated using paired fine-resolution (0.25 $$^{\circ }$$ ∘ ) and coarse-resolution (1 $$^{\circ }$$ ∘ ) monthly data obtained from a 9-year simulation. Next, blind testing is performed using monthly data obtained from two different years outside of the training and validation set. To evaluate the efficiency of each technique, different statistical metrics are used, including mean squared error (MSE), peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and learned perceptual image patch similarity (LPIPS). The results show that EDRN outperforms other algorithms in terms of PSNR, SSIM, and MSE, but struggles to capture fine-scale features in the data. In contrast, SRGAN, a generative model that uses perceptual loss, excels in capturing fine details at boundaries and internal structures, resulting in lower LPIPS than other methods.

Pawar, Nikhil M. (ORCID:0000000211613289)↗
DOE OSTI2026

Modeling and Experimental Demonstration of Flux Spreading in Light Trapping Planar-Cavity Solar Enclosed Particle Receivers

This study experimentally validates and numerically models the flux-spreading effect in a light-trapping planar-cavity solar receiver) for particle-based concentrating solar power systems. The receiver's shallow cavity with vertical planar walls redistributes concentrated solar flux, reducing peak intensity and achieving uniform heat flux. On-sun tests at National Renewable Energy Laboratory's High-Flux Solar Furnace under flux up to 1500 kW/m2 measured cavity wall temperatures, which were compared with Monte Carlo ray-tracing (SolTrace) and computational numerical simulations. Three angular absorptance models were evaluated: constant absorptance, a Pyromark-based directional model, and a Fresnel-based Cr2O3 model. The Fresnel-derived model showed the best agreement with experiments, achieving high correlation (PC > 0.85), structural similarity (SSIM > 0.98), and signal-to-noise ratios (PSNR > 40 dB), with temperature prediction errors of 1-11%. Results confirm that flux spreading mitigates local overheating and validate the integrated modeling approach, supporting the solar receiver scalability for high-efficiency, high-temperature concentrating solar power applications.

14 SOLAR ENERGY↗
DOE OSTI2024

Characterization of SimulCam, a standoff Raman system for scientific support of SuperCam operations on Mars

During the development activities of SuperCam Calibration Target, target intended for one of the two first Raman instruments to be deployed on another planetary body, our group developed a laboratory instrument that could simulate to some extent the Raman capabilities of one of such instruments and could provide data with similar quality. The use of this kind of laboratory instruments has demonstrated its utility in the evaluation of potential calibration targets or anticipating the science outcome that an instrument could provide. The present work describes our laboratory setup to support SuperCam, evaluating similarities between both instruments, despite of differences in the hardware. Evaluation of data gathered by SuperCam on Mars and the availability of one replica of SuperCam’s Calibration Target allowed the comparison on the same set of targets, demonstrating how similar Signal-to-Noise Ratio (SNR) could be achieved from both instruments. The higher energy per pulse on SimulCam is compensated by a greater analytical footprint and the use of smaller collection optics. The results show how spectra obtained at representative distances of SuperCam are comparable. Operational principles are also comparable in terms of time resolution, and close in terms of spectral resolution. This similarity has allowed different science support works using SimulCam data, as well as the support to Mars detections using our setup. We provide examples of this support that will be shared with the community in different papers, as well as examples of possible operations activities that could benefit from experiments performed with SimulCam. We show how this setup can complement the two laboratory replicas in Los Alamos and Toulouse in providing support data to different experiments.

47 OTHER INSTRUMENTATION↗