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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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47 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Processing and properties of PSZT 95/5 ceramics with varying Ti and Nb substitution

Niobium doped lead-tin-zirconate-titanate ceramics near the PZT 95/5 orthorhombic AFE – rhombohedral FE morphotropic phase boundary Pb 1-0.5y (Zr 0.865-x Ti x Sn 0.135 ) 1-y Nb y O 3 were prepared according to a 2 2+1 factorial design with x = 0.05, 0.07 and y = 0.0155, 0.0195. The ceramics were prepared by a traditional solid-state synthesis route and sintered to near full density at 1250°C for 6 hours. All compositions were ~98% dense with no detectable secondary phases by XRD. The ceramics exhibited equiaxed grains with intergranular porosity and grain size was ~5 μm, decreasing with niobium substitution. Compositions exhibited remnant polarization values of ~32 μC/cm 2 , increasing with Ti substitution. Depolarization by the hydrostatic pressure induced FE-AFE phase transition was drastically affected by variation of the Ti and Nb substitution, increasing at a rate of 113 MPa / 1% Ti and 21 MPa / 1% Nb. Total depolarization output was insensitive to the change in Ti and Nb substitution, ~32.8 μC/cm 2 for the PSZT ceramics. The R3c-R3m and R3m-Pm3m phase transition temperatures on heating ranged from 90 to 105°C and 183 to 191°C, respectively. Ti substitution stabilized the R3c and R3m phases to higher temperatures, while Nb substitution stabilized the Pm3m phase to lower temperatures. Thermal hysteresis of the phase transitions was also observed in the ceramics, with transition temperature on cooling being as much as 10°C lower.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Improving the Confidence in Retrievals of Vertical Distributions of Cloud Condensation Nuclei Number Concentration from ARM Supported by Aircraft In Situ Observations

Accurate quantification of the vertical distribution of cloud condensation nuclei (CCN) number concentrations is critical for improving our understanding of aerosol–cloud interactions. Ground-based Raman lidars operated by the Atmospheric Radiation Measurement (ARM) program, together with surface CCN measurements, are used to retrieve vertically resolved CCN number concentrations (Retrieved Number concentration of CCN, RNCCN). These retrievals rely on several assumptions, including that aerosol composition is vertically homogeneous. To assess this assumption, we developed and tested a framework to infer the dominant aerosol classes/types at different altitudes. This was done by applying a k-Nearest-Neighbors (kNN) algorithm to lidar ratio and linear depolarization ratio measurements from Raman lidar. We evaluated the framework using aircraft aerosol and CCN measurements from the ARM Holistic Interactions of Shallow Clouds, Aerosols, and Land Ecosystems (HI-SCALE) field campaign. The results show that RNCCN performance degrades as vertical aerosol complexity increases, i.e., RNCCN agrees with the aircraft CCN in vertically homogeneous conditions, but closure decreases in layered aerosol structures. To generalize beyond individual examples, we introduce a metric (heterogeneity index) that quantifies the vertical complexity by assessing the variation of inferred aerosol classes/types. Case-level statistics show a tendency for RNCCN and aircraft differences to increase with this metric. By detecting retrievals that are likely compromised by aerosol vertical heterogeneity, the proposed framework improves the interpretability and effective use of RNCCN used for long-term evaluation of models and aerosol–cloud interactions.

Tian, Jingjing↗
DOE OSTI2022

Polar Aerosol Vertical Structures and Characteristics Observed with a High Spectral Resolution Lidar at the ARM NSA Observatory

Aerosol vertical distributions impact both the direct and indirect radiative effects of aerosols. High Spectra Resolution Lidar (HSRL) separates between atmospheric molecular signals and aerosol particle signals and therefore can provide reliable measurements of aerosol properties. Six years of HSRL measurements between 2014 and 2019 from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) atmospheric observatory at Utqiaqvik are used to statistically analyze Arctic aerosol vertical distributions. The annual cycle of aerosol vertical distributions in terms of aerosol particulate backscatter coefficient ($β_p$), lidar scattering ratio (SR), and aerosol particulate depolarization ratio ($δ_p$) profiles at the wavelength of 532 nm shows that Arctic Haze events are prevalent in later winter and spring at the NSA site. Mineral dust is frequently presented in strong aerosol layers in the spring, fall, and winter seasons. Over the summer season, the NSA site has large aerosol loadings that are dominated by small spherical aerosol particles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Efficiency analysis of helium-cooled MAS DNP: case studies of surface-modified nanoparticles and homogeneous small-molecule solutions

Despite the growing number of successful applications of dynamic nuclear polarization (DNP)-enhanced magic-angle spinning (MAS) NMR in structural biology and materials science, the nuclear polarizations achieved by current MAS DNP instrumentation are still considerably lower than the theoretical maximum. Here, the method could be significantly strengthened if experiments were performed at temperatures much lower than those currently widely used (~100 K). Recently, the prospects of helium (He)-cooled MAS DNP have been increased with the instrumental developments in MAS technology that uses cold helium gas for sample cooling. Despite the additional gains in sensitivity that have been observed with He-cooled MAS DNP, the performance of the technique has not been evaluated in the case of surfaces and interfaces that benefit the most from DNP. Herein, we studied the efficiency of DNP at temperatures between ~30 K and ~100 K for organically functionalized silica material and a homogeneous solution of small organic molecules at a magnetic field B 0 = 16.4 T. We recorded the changes in signal enhancement, paramagnet-induced quenching and depolarization effects, DNP build-up rate, and Boltzmann polarization. For these samples, the increases in MAS-induced depolarization and DNP build-up times at around 30 K were not as severe as anticipated. In the case of the surface species, we determined that MAS DNP at 30 K provided ~10 times higher sensitivity than MAS DNP at 90 K, which corresponds to the acceleration of experiments by multiplicative factors of up to 100.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Surface Dynamics of Charge Transport in LaAlO 3 /SrTiO 3 with Time-Resolved Kelvin Probe Force Microscopy

Time-resolved Kelvin probe force microscopy (tr-KPFM) was used to map surface potential dynamics in LAO/STO under its critical thickness, where it acts as an insulator, as polarizing and depolarizing electric fields were applied to planar electrodes in ambient conditions. Two time constants, for polarization and relaxation (i.e., depolarization) each, were derived and were shown to be independent of the direction of electrical field, revealing the reproducibility and recovery of the surfaces. Ambient aging or recent electrical history did not change the surface kinetics as determined by tr-KPFM. During polarization, the faster time constant (~3–6 s) is likely associated with the transport of H+ ions through the full length of the channel. The slower time constant (~40–50 s), on the other hand, is observed across only half the channel width near the higher-potential–more positive–electrode, which is likely associated with an electrochemical reaction such as the dissociation of water. This slower time constant drops to ~10–20 s toward the middle of the channel which could represent the transport of OH– ions. Furthermore, during relaxation, the fast time constant is consistent with polarization and is correlated to the same mechanism while the slower time constant is higher than it was during polarization and may represent the reabsorption of moisture from the atmosphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

CryoEM structures of the human CLC-2 voltage-gated chloride channel reveal a ball-and-chain gating mechanism

CLC-2 is a voltage-gated chloride channel that contributes to electrical excitability and ion homeostasis in many different tissues. Among the nine mammalian CLC homologs, CLC-2 is uniquely activated by hyperpolarization, rather than depolarization, of the plasma membrane. The molecular basis for the divergence in polarity of voltage gating among closely related homologs has been a long-standing mystery, in part because few CLC channel structures are available. Here, we report cryoEM structures of human CLC-2 at 2.46 – 2.76 Å, in the presence and absence of the selective inhibitor AK-42. AK-42 binds within the extracellular entryway of the Cl – -permeation pathway, occupying a pocket previously proposed through computational docking studies. In the apo structure, we observed two distinct conformations involving rotation of one of the cytoplasmic C-terminal domains (CTDs). In the absence of CTD rotation, an intracellular N-terminal 15-residue hairpin peptide nestles against the TM domain to physically occlude the Cl – -permeation pathway. This peptide is highly conserved among species variants of CLC-2 but is not present in other CLC homologs. Previous studies suggested that the N-terminal domain of CLC-2 influences channel properties via a “ball-and-chain” gating mechanism, but conflicting data cast doubt on such a mechanism, and thus the structure of the N-terminal domain and its interaction with the channel has been uncertain. Through electrophysiological studies of an N-terminal deletion mutant lacking the 15-residue hairpin peptide, we support a model in which the N-terminal hairpin of CLC-2 stabilizes a closed state of the channel by blocking the cytoplasmic Cl – -permeation pathway.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Thermally Activated Circularly Polarized Photoluminescence in a 2D Hybrid Perovskite with Giant Spin Splitting

Circularly polarized light generation and detection are critical for future spin-based technologies that inter-convert circularly polarized photons and electron spins. However, detailed mechanisms in such spin-photon interfaces are often either poorly understood or operate at cryogenic temperatures since typically small energies separating spin-split electronic bands facilitate thermally driven spin depolarization. Recently, several 2D hybrid perovskites with polar achiral cations were theoretically demonstrated to exhibit conduction and valence band spin-splitting energies greatly exceeding room-temperature thermal energy, suggesting their utility as spin-photon interfaces with practical operating temperatures. Here, a strong "spin memory" effect is reported in such a polar achiral layered perovskite that enables large room-temperature circularly polarized emission anisotropy following excitation with circularly polarized light. The polarization anisotropy depends strongly on temperature (thermally activated), excitation energy, and crystal orientation with respect to the excitation source. Temperature-dependent photoconductance measurements reveal similar thermally activated carrier generation. These observations suggest a mechanism whereby giant in-plane splitting of single-particle levels protects spin-polarization of photogenerated electrons and holes before recombination. Although polarized light emission is explored in greater detail in chiral perovskites, these results reveal that even without chirality, large spin memory in polar achiral perovskites can enable spin-photon interfaces that operate at elevated temperatures.

14 SOLAR ENERGY↗
DOE OSTI2025

Dynamics of Thermally Driven Domain Transformation in Ferroelectric Thin Films

An important feature in ultrathin ferroelectric films is the spontaneous formation of nanoscale polarization domain patterns. Epitaxial strain can greatly increase the ferroelectric transition temperature such that films can be in the ferroelectric state during growth. On the other hand, depolarization fields compete with ferroelectricity in ultrathin films, and, consequently, the optimal domain configuration during growth is a moving target. Under these conditions it is readily possible for a grown film to be in a nonequilibrium domain configuration. As the energy landscape in the system is quite complex, the relaxation dynamics by which a system can evolve towards the true equilibrium configuration are also quite interesting. Here, to capture the details of this process we used Bragg-geometry x-ray photon correlation spectroscopy (XPCS), in which x-ray scattering speckle patterns contain the information from the domain arrangements inside the film. With modest heating (∼15⁢0 °C) domain relaxation from 𝑇 (tetragonal) to 𝑀 𝐶 (monoclinic) was observed in BaTiO 3 films grown on ultrathin ferroelectric PbTiO 3 layers. Two-time correlation analysis reveals fascinating details associated with sticking points and reversals in the process.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Identifying insects, clouds, and precipitation using vertically pointing polarimetric radar Doppler velocity spectra

Abstract. This study presents a method to identify and distinguish insects, clouds, and precipitation in 35 GHz (Ka-band) vertically pointing polarimetric radar Doppler velocity power spectra and then produce masks indicating the occurrence of hydrometeors (i.e., clouds or precipitation) and insects at each range gate. The polarimetric radar used in this study transmits a linear polarized wave and receives signals in collinear (CoPol) and cross-linear (XPol) polarized channels. The measured CoPol and XPol Doppler velocity spectra are used to calculate linear depolarization ratio (LDR) spectra. The insect–hydrometeor discrimination method uses CoPol and XPol spectral information in two separate algorithms with their spectral results merged and then filtered into single value products at each range gate. The first algorithm discriminates between insects and clouds in the CoPol Doppler velocity power spectra based on the spectra texture, or spectra roughness, which varies due to the scattering characteristics of insects vs. cloud particles. The second algorithm distinguishes insects from raindrops and ice particles by exploiting the larger Doppler velocity spectra LDR produced by asymmetric insects. Since XPol power return is always less than CoPol power return for the same target (i.e., insect or hydrometeor), fewer insects and hydrometeors are detected in the LDR algorithm than the CoPol algorithm, which drives the need for a CoPol based algorithm. After performing both CoPol and LDR detection algorithms, regions of insect and hydrometeor scattering from both algorithms are combined in the Doppler velocity spectra domain and then filtered to produce a binary hydrometeor mask indicating the occurrence of cloud, raindrops, or ice particles at each range gate. Forty-seven summertime days were processed with the insect–hydrometeor discrimination method using US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Ka-band zenith pointing radar observations in northern Oklahoma, USA. For these 47 d, over 70 % of the hydrometeor mask column bottoms were within ±100 m of simultaneous ceilometer cloud base heights. All datasets and images are available to the public on the DOE ARM repository.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Classifying thermodynamic cloud phase using machine learning models

Vertically resolved thermodynamic cloud-phase classifications are essential for studies of atmospheric cloud and precipitation processes. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Thermodynamic Cloud Phase (THERMOCLDPHASE) value-added product (VAP) uses a multi-sensor approach to classify the thermodynamic cloud phase by combining lidar backscatter and depolarization, radar reflectivity, Doppler velocity, spectral width, microwave-radiometer-derived liquid water path, and radiosonde temperature measurements. The measured pixels are classified as ice, snow, mixed phase, liquid (cloud water), drizzle, rain, and liq_driz (liquid+drizzle). We use this product as the ground truth to train three machine learning (ML) models to predict the thermodynamic cloud phase from multi-sensor remote sensing measurements taken at the ARM North Slope of Alaska (NSA) observatory: a random forest (RF), a multi-layer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with 1 year of data show that the CNN outperforms the other two models, achieving the highest test accuracy, F1 score, and mean intersection over union (IOU). Analysis of ML confidence scores shows that ice, rain, and snow have higher confidence scores, followed by liquid, while mixed, drizzle, and liq_driz have lower scores. Feature importance analysis reveals that the mean Doppler velocity and vertically resolved temperature are the most influential data streams for ML thermodynamic cloud-phase predictions. Lidar measurements exhibit lower feature importance due to rapid signal attenuation caused by the frequent presence of persistent low-level clouds at the NSA site. The ML models' generalization capacity is further evaluated by applying them at another Arctic ARM site in Norway using data taken during the ARM Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) field campaign. The models demonstrated similar performance to that observed at the NSA site. Finally, we evaluate the ML models' response to simulated instrument outages and signal degradation and show that a CNN U-Net model trained with input channel dropouts performs better when input fields are missing.

ARM Aerial Facility↗
DOE OSTI2025

CROCUS Dual Polarization Ceilometer Data at Northeastern Illinois University Rooftop

This dataset is from the Department of Energy Office of Science funded project, CROCUS Urban Integrated Field Laboratory (https://crocus-urban.org/). The dual-polarization ceilometer (Vaisala CL61) is an autonomous lidar system operating at 910 nm wavelength, providing valuable measurements for understanding atmospheric boundary layer evolution, air quality, and cloud-aerosol interactions. The CL61 measures the backscattered signal intensity alternating between parallel- and cross-polarization signals. The unique depolarization measurement capability improves discrimination between different particle types, such as liquid droplets, ice crystals, and aerosols. The depolarization is highly dependent on the scatterer shape and orientation (spherical vs non-spherical particles), with the linear depolarization ratio providing a measure of dominant backscatter signal component from atmospheric particles at various heights, essentially allowing discrimination between liquid and solid particles. With its efficient optical system, CL61’s improved signal-to-noise ratio compared to traditional ceilometers allows studying detailed vertical profiles of aerosols and clouds up to 15 km height.Datasets are stored in a netCDF data format, and we we encourage users to make use of the associated toolkits available from Unidata (https://www.unidata.ucar.edu/software/netcdf/), Project Pythia (https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html), and our “Instrument Cookbooks” (https://crocus-urban.github.io/instrument-cookbooks) for more information on how to process the metadata-rich datasets.

54 ENVIRONMENTAL SCIENCES↗