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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 145 records · Page 8

Thermophotovoltaic efficiency of 40%

Thermophotovoltaics (TPVs) convert predominantly infrared wavelength light to electricity via the photovoltaic effect, and can enable approaches to energy storage and conversion that use higher temperature heat sources than the turbines that are ubiquitous in electricity production today. Since the first demonstration of 29% efficient TPVs (Fig. 1a) using an integrated back surface reflector and a tungsten emitter at 2,000°C (ref. 10), TPV fabrication and performance have improved. However, despite predictions that TPV efficiencies can exceed 50%, the demonstrated efficiencies are still only as high as 32%, albeit at much lower temperatures below 1,300 C (refs. 13,14,15). Here we report the fabrication and measurement of TPV cells with efficiencies of more than 40% and experimentally demonstrate the efficiency of high-bandgap tandem TPV cells. The TPV cells are two-junction devices comprising III–V materials with bandgaps between 1.0 and 1.4 eV that are optimized for emitter temperatures of 1,900–2,400°C. The cells exploit the concept of band-edge spectral filtering to obtain high efficiency, using highly reflective back surface reflectors to reject unusable sub-bandgap radiation back to the emitter. A 1.4/1.2 eV device reached a maximum efficiency of (41.1 ± 1)% operating at a power density of 2.39 W cm –2 and an emitter temperature of 2,400°C. A 1.2/1.0 eV device reached a maximum efficiency of (39.3 ± 1)% operating at a power density of 1.8 W cm–2 and an emitter temperature of 2,127°C. These cells can be integrated into a TPV system for thermal energy grid storage to enable dispatchable renewable energy. This creates a pathway for thermal energy grid storage to reach sufficiently high efficiency and sufficiently low cost to enable decarbonization of the electricity grid.

14 SOLAR ENERGY↗

Data-Driven Invertible Neural Surrogates of Atmospheric Transmission

We present Data-Driven Invertible Neural Surrogates of Atmospheric transmission, or DINSAT. DINSAT is a novel framework for inferring an atmospheric transmission profile from a spectral scene. This framework leverages a lightweight, physics-based simulator that is automatically tuned -- by virtue of autodifferentiation and differentiable programming -- to construct a surrogate atmospheric profile to model the observed data. The framework has utility in (i) performing atmospheric correction, (ii) recasting spectral data between various modalities (e.g. radiance and reflectance at the surface and at the sensor), and (iii) inferring atmospheric transmission profiles, such as absorbing bands and their relative magnitudes. We demonstrate the utility of these methods by performing a canonical atmospheric correction task for the purposes of further analysis - in this case, target detection within a scene.

Koch, James V.↗

Progress towards subsurface spectroscopy inside heterogeneous materials using four wave mixing phase conjugation

Herein, we report preliminary results on subsurface spectroscopy inside heterogeneous materials using four wave mixing phase conjugation. For our test material we use an inert plastic bonded explosive simulant that contains fluorescent guidestar particles. Using phase conjugation, we are able to obtain spectral enhancements approximately equal to the phase conjugate reflectivity. Additionally, we discuss future directions to improve this technique to obtain greater signal enhancements.

47 OTHER INSTRUMENTATION↗

The Evaluation of Machine Learning Techniques for Isotope Identification Contextualized by Training and Testing Spectral Similarity

Precise gamma-ray spectral analysis is crucial in high-stakes applications, such as nuclear security. Research efforts toward implementing machine learning (ML) approaches for accurate analysis are limited by the resemblance of the training data to the testing scenarios. The underlying spectral shape of synthetic data may not perfectly reflect measured configurations, and measurement campaigns may be limited by resource constraints. Consequently, ML algorithms for isotope identification must maintain accurate classification performance under domain shifts between the training and testing data. To this end, four different classifiers (Ridge, Random Forest, Extreme Gradient Boosting, and Multilayer Perceptron) were trained on the same dataset and evaluated on twelve other datasets with varying standoff distances, shielding, and background configurations. A tailored statistical approach was introduced to quantify the similarity between the training and testing configurations, which was then related to the predictive performance. Wilcoxon signed-rank tests revealed that the OVR-wrapped XGB significantly outperformed the other algorithms, with confidence levels of 99.0% or above for the 133Ba, 60Co, 137Cs, and 152Eu sources. The findings from this work are significant as they outline techniques to promote the development of robust ML-based approaches for isotope identification.

domain adaptation↗

Zero-power wireless system for crop water content monitoring

Zero power wireless sensors, devices, and systems are used for crop water content monitoring. The sensors consume no power while monitoring for the presence of dry crop conditions. Infrared reflectance from plants is measured and when selected spectral conditions are met, a circuit is closed, activating an alarm, an RFID tag, or a radio transmitter. The deployed sensors consume no power while monitoring, reducing or eliminating the need to change batteries.

Rinaldi, Matteo↗

Temperature-dependent diffuse reflectance measurements of ceramic powders in the near- and mid-infrared spectra

Radiative properties are critical to quantify radiative energy fluxes between surfaces and in participating media. However, there is limited experimental data on temperature-dependent radiative properties of materials. Herein, this work focuses on experimentally measuring temperature-dependent diffuse reflectance in the near- and mid-infrared spectra (1–20 μm) for ceramic particles with applications as heat-transfer and thermal-storage media in concentrated solar power (CSP) plants. Specifically, a commercially available sintered bauxite proppant, ACCUCAST ID80, and its primary chemical constituents—alumina (Al 2 O 3 ) and silica (SiO 2 )—are measured in powder form using a Fourier transform infrared spectrometer (FTIR) coupled with a specialized diffuse reflectance accessory and a heated stage. Room-temperature diffuse reflectance measurements show increased absorption in tests with greater mass fractions of the ceramic samples. There is a strong correlation in the measured reflectance spectra of ACCUCAST with alumina and silica in the spectral range 2000–500 cm –1 (5–20 μm). Whereas, for shorter wavelengths (< 5 μm), the absorptance for ACCUCAST is greater than the absorptance for alumina and silica, indicating contributions from other chemical species present in the composite material. For the first time, temperature-dependent diffuse reflectance measurements are reported for ACCUCAST up to 1000 °C. These results are compared against those of alumina and silica through the calculation of a thermal emittance. All three materials exhibit a calculated emittance of ~0.9 at room temperature. However, this value decreases to ~0.6 for ACCUCAST and drops to less than 0.4 for alumina and silica at 1000 °C. Thermal cycling in air at 1000 °C resulted in a visible color change from dark grey to light orange for ACCUCAST and a subsequent larger increase in reflectance for wavelengths less than 5 μm as compared to ACCUCAST thermally cycled at 1000 °C in vacuum. Alumina and silica spectra proved to be largely unaffected by thermal cycling under atmospheric conditions. Overall, this study establishes a powerful technique for the characterization of radiative properties of particulate materials as a function of temperature and presents a detailed case study of ACCUCAST, a candidate for next-generation particle-based CSP.

14 SOLAR ENERGY↗

Light Management in Bifacial Photovoltaics with Spectrally Selective Mirrors

Spectrally-selective mirrors that simultaneously provide above-bandgap anti-reflection and sub-bandgap light rejection are tested for their ability to provide passive cooling to partially sub-bandgap transparent bifacial photovoltaics. The optical and thermal benefits of both idealized and real, low-complexity spectrally-selective mirrors on single-axis tracking, bifacial PERC arrays under realistic conditions are tested via rigorous finite element simulations. Four- and six-layer mirror designs increased carrier generation beyond what traditional antireflection coatings can provide without the associated cell heating. Here, idealized mirrors were found to provide up to 2.4 °C of cooling when included on both air/glass interfaces of the bifacial module.

14 SOLAR ENERGY↗

Leveraging machine learning to enhance aerosol classification using Single-Particle Mass Spectrometry

Advancing automated classification of atmospheric aerosols from Single-Particle Mass Spectrometry (SPMS) data remains challenging due to overlapping ion signatures, compositional diversity, and limited labeled data. This study evaluates supervised and semi-supervised learning frameworks to enhance aerosol identification by jointly leveraging labeled and unlabeled spectra. Four models were compared: a supervised Support Vector Machine (SVM), a self-training SVM, a stacked autoencoder classifier, and a stacked autoencoder trained using a temporal-ensembling Mean Teacher approach. All models achieved high and stable accuracies (90.0 %–91.1 %), surpassing previous results on the same dataset (87 %) and matching the performance of state-of-the-art deep learning methods. Despite small global metric differences (≤ 1 %), semi-supervised variants yielded up to 5 %–10 % improvements for compositionally rare particle types – such as soot (0.77 % of spectra, F1-score: 0.93–0.97) and hazelnut pollen (0.98 % of spectra, F1-score: 0.97–1.00) – equating to roughly ∼ 187 additional correctly classified spectra. These gains are scientifically significant, as such rare particles exert disproportionate influence on radiative absorption and ice nucleation processes; their improved detection reduces modeled uncertainties in aerosol absorption optical depth and mixed-phase cloud ice nucleation rates. The models' residual misclassifications (≈ 9 %) largely arise from true spectral overlap among chemically adjacent species (e.g., Na- vs. K-feldspar, coated vs. uncoated feldspars), reflecting physical compositional continuity rather than algorithmic error. Collectively, these findings demonstrate that leveraging unlabeled data to learn robust spectral representations and refine classification enhances both fidelity and interpretability, bridging data-driven analysis with aerosol–climate process understanding.

54 ENVIRONMENTAL SCIENCES↗

Snow ALbedo eVOlution (SALVO) Campaign Spectral Albedo and Related Measurements from April - June, 2024 in Utqiagivk, AK

A field-portable spectroradiometer, referred to herein as an ‘ASD’, was used to make spatially-distributed spectral albedo (350 – 2500 nm) measurements on tundra and sea ice surfaces. The ASD detector is carried in a backpack and controlled via a computer mounted on the front of the operator (see Figure 1). The ASD measures the spectral irradiance from a fiber optic cable that is routed from the backpack to a custom, gooseneck cosine collector mounted on the end of a 1-m long boom (Grenfell and Perovich, 2008). The boom was held at hip height (approximately 1 m) and had an integrated bubble level for levelling. To make an albedo measurement, first the operator collect an incident (down-welling) irradiance, followed by a reflected (up-welling) measurement. The time between incident and reflected measurements was typically between 11 and 26 seconds (interquartile range). For each measurement, 10 spectra are averaged together. Albedo is calculated as the ratio of the reflected to incident measurement, which obviates the need for absolute radiometric calibration. Albedo measurements were taken parallel to the 200-m albedo lines at 5-m increments (41 measurements) ~1 m south of the line. While the ASD operator was making measurements, an assistant kept notes on the scan number associated with each measurement, the surface type (see below), and collected photos of each measurement (see companion oblique photos data archive). Measurements were made within 3 hours of solar noon.

ASD Spectroradiometer↗

Nanostructure‐Derived Antireflectivity in Leafhopper Brochosomes

Understanding how insect‐derived biomaterials interact with light has led to new advances and interdisciplinary insights in entomology and physics. Leafhoppers are insects that coat themselves with highly ordered biological nanostructures known as brochosomes. Brochosomes are thought to provide a range of protective properties to leafhoppers, such as hydrophobicity and antireflectivity, which has inspired the development of synthetic brochosomes that mimic their structures. Despite recent progress, the high antireflective properties of brochosome structures are not fully understood. Herein, a combination of experiments and computational modeling is used to understand the structure‐, material‐, and polarization‐dependent optical properties of brochosomes modeled on the geometries found in three leafhopper species. The results qualitatively represent that light interference interaction with nanostructures naturally occurring in brochosomes is responsible for the spectral tuning and the asymmetric line shape of the reflectance spectra. Whereas prior work has focused on the computational modeling of idealized pitted particles, this work shows that light–matter interactions with brochosome structures can be tuned by varying the geometry of their cage‐like nanoscale features and by changing the arrangement of multiparticle assemblies. Broadly, this work establishes principles for the guided design of new optically active materials inspired by these unique insect nanostructures.

Banerjee, Progna↗

First estimation of high-resolution solar photovoltaic resource maps over China with Fengyun-4A satellite and machine learning

Fengyun-4A (FY-4A), which is the latest-generation Chinese geostationary meteorological satellite, measures solar reflection and thermal emission with high temporal, spatial, and spectral resolutions. It is expected to be highly beneficial for solar resource assessment and forecasting in China. This study is the first to estimate, using FY-4A and a random forest model, the global horizontal irradiance (GHI) at a 4-km–15-min spatio-temporal resolution over China, as a means to arrive at a solar photovoltaic (PV) resource map. In terms of GHI estimates, the root mean square error and mean bias error between hourly measured and retrieved values are 147.02 (35.2%), –5.64 W/m 2 (–1.4%), respectively, whereas the values of daily estimates are 29.20 (18.0%), –2.97 W/m 2 (–1.3%). The retrieval accuracy is found much better for instances with solar zenith angles smaller than 60°. Relatively larger errors are found at locations in the Sichuan Basin and northeastern China, which can be attributed to bright surfaces and/or strong cloud transients. With the retrieved irradiance, PV resource is derived through a physical model chain. The annual mean PV resource map suggests that, over most of the west areas, the annual mean effective irradiance exceeds 1700 kWh/m 2 , with the highest value found in Tibet (around 2000 kWh/m 2 per annum). Eastern China has an annual effective irradiance of only 1300–1500 kWh/m 2 . In conclusion, the region with poorest solar resource is the Sichuan Basin (less than 1100 kWh/m 2 per annum).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Quasi-Fermi liquid behavior in a one-dimensional system of interacting spinless fermions

We present numerical evidence for a paradigm in one-dimensional interacting fermion systems, whose phenomenology has traits of both Luttinger liquids and Fermi liquids. This state, dubbed a quasi-Fermi liquid, possesses a discontinuity in its fermion occupation number at the Fermi momentum. The excitation spectrum presents particlelike quasiparticles and absence of holelike quasiparticles, giving rise instead to edge singularities. Such a state is realized in a one-dimensional spinless fermion lattice Hamiltonian by fine-tuning the interactions to a regime where they become irrelevant in the renormalization group sense. We show, using uniform infinite matrix products states and finite-entanglement scaling analysis, that the system ground state is characterized by a Luttinger parameter K = 1 and a discontinuous jump in the fermion occupation number. We support the characterization with calculations of the spectral function that show a particle-hole asymmetry reflected in the existence of well-defined Landau quasiparticles above the Fermi level and edge singularities without the associated quasiparticles below. Furthermore, these results indicate that the quasi-Fermi liquid paradigm can be realized beyond the low-energy perturbative realm.

1-dimensional systems↗

Early Results from GLASS-JWST. VII. Evidence for Lensed, Gravitationally Bound Protoglobular Clusters at z = 4 in the Hubble Frontier Field A2744

We investigate the blue and optical rest-frame sizes (λ ≃ 2300–4000 Å) of three compact star-forming regions in a galaxy at z = 4 strongly lensed (×30, ×45, and ×100) by the Hubble Frontier Field galaxy cluster A2744 using GLASS-ERS James Webb Space Telescope (JWST)/NIRISS imaging at 1.15 μm, 1.50 μm, and 2.0 μm with a point-spread function ≲0$_{.}^{"}$1. In particular, the Balmer break is probed in detail for all multiply imaged sources of the system. With ages of a few tens of Myr, stellar masses in the range (0.7–4.0) ×10 6 M⊙ and optical/ultraviolet effective radii spanning the interval 3 < R eff < 20 pc, such objects are currently the highest-redshift (spectroscopically confirmed) gravitationally bound young massive star clusters (YMCs), with stellar mass surface densities resembling those of local globular clusters. Optical (4000 Å, JWST-based) and ultraviolet (1600 Å, Hubble Space Telescope–based) sizes are fully compatible. The contribution to the ultraviolet underlying continuum emission (1600 Å) is ~30%, which decreases by a factor of 2 in the optical for two of the YMCs (~4000 Å rest-frame), reflecting the young ages (<30 Myr) inferred from the spectral energy distribution fitting and supported by the presence of high-ionization lines secured with the Very Large Telescope/MUSE. Such bursty forming regions enhance the specific star formation rate of the galaxy, which is ≃10 Gyr –1 . This galaxy would be among the extreme analogs observed in the local universe having a high star formation rate surface density and a high occurrence of massive stellar clusters in formation.

79 ASTRONOMY AND ASTROPHYSICS↗

Variable Daily Autocorrelation Functions of High-Frequency Seismic Data on Mars

Abstract High-frequency seismic data on Mars are dominated by wind-generated lander vibrations, which are radiated partially to the subsurface. Autocorrelation functions (ACFs) of seismic data on Mars filtered between 1 and 5 Hz show clear phases at ∼1.3, ∼2.6, and ∼3.9 s. Daily temporal changes of their arrival times (dt/t) correlate well with the daily changes of ground temperature, with ∼5% daily variation and ∼50 min apparent phase delay. The following two mechanisms could explain the observations: (1) the interference of two predominant spectral peaks at ∼3.3 and ∼4.1 Hz, assumed to be both lander resonance modes, generate the apparent arrivals in the ACFs; (2) the interference of the lander vibration and its reflection from an interface ∼200 m below the lander generate the 3.3 Hz spectral peak and ∼1.3 s arrival in the ACFs. The driving mechanism of the resolved dt/t that most likely explains the ∼50 min delay is thermoelastic strain at a near-surface layer, affecting the lander–ground coupling and subsurface structures. The two outlined mechanisms suggest, respectively, up to ∼10% changes in ground stiffness at 1–5 Hz and ∼15% velocity changes in the top ∼20 m layer. These are upper bound values considering also other possible contributions. The presented methodology and results contribute to analysis of ACFs with limited data and the understanding of subsurface materials on Mars.

Geochemistry & Geophysics↗

Landscape-scale Characterization of Arctic Tundra Vegetation Composition, Structure, and Function with a Multi-sensor Unoccupied Aerial System: Supporting Data.

Airborne remote sensing data collected using the Brookhaven National Laboratory's (BNL) heavy-lift unoccupied aerial system (UAS) octocopter platform, the Osprey, operated by the Terrestrial Ecosystem Science and Technology (TEST) group (https://www.bnl.gov/testgroup). This package includes data from three flights flown over the NGEE-Arctic Council, Kougarok and Teller sites in July, 2018. The Osprey is a multi-sensor UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) and thermal infrared (TIR) surface 'skin' temperature imagery, as well as surface reflectance at 1 nm intervals in the visible to near-infrared spectral range 350 - 1000 nm measured at regular intervals along each flight path. Derived image products include ortho-mosaiced RGB and TIR images, an RGB-based digital surface model (DSM) using the structure from motion (SfM) technique, digital terrain model (DTM), and a canopy height model (CHM). In addition, a VNIR surface reflectance file is provided for the trigger locations collected during each flight campaign. Ancillary aircraft data, flight mission parameters, and general flight conditions provided by the onboard flight and data collection computers are also included. Unprocessed and processed data products are included in this package (processing levels 0-3). Data and metadata are provided as text (*.txt, *.json, *.kml, *hdr, *.enp), tabular (*.dat, *.csv, *.waypoint, ENVI format (no extension)), point cloud (*.laz) and image (*.jpg, *.tif, *png) formats. This metadata document contains flight campaign, instrument and file metadata, along with a description of data processing levels, data products and file naming scheme.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy?s Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Analysis and Validation of Spectral Irradiance Simulations for 75 kW Bifacial Solar Test Field

This work investigates how the spectrum of irradiance incident on the rear of bifacial modules impacts their performance. Light incident on the rear of bifacial modules can be reflected from the ground, mounting structures, and other nearby objects, causing both the intensity and spectrum to be modified. As a result, PV cells and sensors with different spectral responses report different values for the rear irradiance, leading to increased uncertainty when modeling performance. Here, we calculate the spectral irradiance incident on the rear of modules through raytrace simulations and validate with measured field data collected from a 75kW single-axis-tracked bifacial test site. Spectral responses for different sensors and PV cells are applied and compared with field measurements for four days. Based on these results, a method for improving non-spectral simulations is proposed. In addition, a linear regression is applied to the modeled spectral results as a method to gain insight into the contributions of ground reflected light to total rear irradiance.

bifacial photovoltaics↗