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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Disentangling Alzheimer’s disease neurodegeneration from typical brain ageing using machine learning

Abstract Neuroimaging biomarkers that distinguish between changes due to typical brain ageing and Alzheimer’s disease are valuable for determining how much each contributes to cognitive decline. Supervised machine learning models can derive multivariate patterns of brain change related to the two processes, including the Spatial Patterns of Atrophy for Recognition of Alzheimer’s Disease (SPARE-AD) and of Brain Aging (SPARE-BA) scores investigated herein. However, the substantial overlap between brain regions affected in the two processes confounds measuring them independently. We present a methodology, and associated results, towards disentangling the two. T1-weighted MRI scans of 4054 participants (48–95 years) with Alzheimer’s disease, mild cognitive impairment (MCI), or cognitively normal (CN) diagnoses from the Imaging-based coordinate SysTem for AGIng and NeurodeGenerative diseases (iSTAGING) consortium were analysed. Multiple sets of SPARE scores were investigated, in order to probe imaging signatures of certain clinically or molecularly defined sub-cohorts. First, a subset of clinical Alzheimer’s disease patients (n = 718) and age- and sex-matched CN adults (n = 718) were selected based purely on clinical diagnoses to train SPARE-BA1 (regression of age using CN individuals) and SPARE-AD1 (classification of CN versus Alzheimer’s disease) models. Second, analogous groups were selected based on clinical and molecular markers to train SPARE-BA2 and SPARE-AD2 models: amyloid-positive Alzheimer’s disease continuum group (n = 718; consisting of amyloid-positive Alzheimer’s disease, amyloid-positive MCI, amyloid- and tau-positive CN individuals) and amyloid-negative CN group (n = 718). Finally, the combined group of the Alzheimer’s disease continuum and amyloid-negative CN individuals was used to train SPARE-BA3 model, with the intention to estimate brain age regardless of Alzheimer’s disease-related brain changes. The disentangled SPARE models, SPARE-AD2 and SPARE-BA3, derived brain patterns that were more specific to the two types of brain changes. The correlation between the SPARE-BA Gap (SPARE-BA minus chronological age) and SPARE-AD was significantly reduced after the decoupling (r = 0.56–0.06). The correlation of disentangled SPARE-AD was non-inferior to amyloid- and tau-related measurements and to the number of APOE ε4 alleles but was lower to Alzheimer’s disease-related psychometric test scores, suggesting the contribution of advanced brain ageing to the latter. The disentangled SPARE-BA was consistently less correlated with Alzheimer’s disease-related clinical, molecular and genetic variables. By employing conservative molecular diagnoses and introducing Alzheimer’s disease continuum cases to the SPARE-BA model training, we achieved more dissociable neuroanatomical biomarkers of typical brain ageing and Alzheimer’s disease.

Hwang, Gyujoon↗
NASA NTRS2018

Update on the NASA Glenn Propulsion Systems Lab Icing and Ice Crystal Cloud Characterization (2017)

NASA Glenn's Propulsion Systems Lab, an altitude engine test facility, generates icing clouds with a spray system. While the spray system is used mostly to create ice crystal clouds (Appendix D/P), the 2017 cloud characterization effort added the requirement to produce exactly supercooled liquid clouds in Appendix C and Appendix O. Success was demonstrated to supercool the largest drops at the warmest conditions, but not freeze out the smallest drops at the coldest conditions. This paper documents primarily the total water content characterization methodology and results from an Iso-Kinetic Probe in ice crystals and Multi-Wire sensor in supercooled liquid, along with the cloud uniformity provided by light extinction tomography. Particle size distribution results from High Speed Imaging probes and a Phase Doppler Interferometer are discussed. Also, a new numerical model for tracking the thermodynamics of the air-drop interactions in PSL from the plenum toward the cloud characterization plane are noted. Both of these latter topic are more fully documented in companion papers.

Calibration↗
DOE OSTI2023

Deep learning Hamiltonians from disordered image data in quantum materials

The capabilities of image probe experiments are rapidly expanding, providing new information about quantum materials on unprecedented length- and timescales. Many such materials feature inhomogeneous electronic properties with intricate pattern formation on the observable surface. This rich spatial structure contains information about interactions, dimensionality, and disorder—a spatial encoding of the Hamiltonian driving the pattern formation. Image recognition techniques from machine learning are an excellent tool for interpreting information encoded in the spatial relationships in such images. Here, we develop a deep learning framework for using the rich information available in these spatial correlations in order to discover the underlying Hamiltonian driving the patterns. We first vet the method on a known case, scanning near-field optical microscopy on a thin film of V⁢O 2 . We then apply our trained convolutional neural network architecture to new optical microscope images of a different V⁢O 2 film as it goes through the metal-insulator transition. We find that a two-dimensional Hamiltonian with both interactions and random field disorder is required to explain the intricate, fractal intertwining of metal and insulator domains during the transition. This detailed knowledge about the underlying Hamiltonian paves the way for using the model to control the pattern formation via, e.g., tailored hysteresis protocols. Finally, we also introduce a distribution-based confidence measure on the results of a multilabel classifier, which does not rely on adversarial training. In addition, we propose a machine-learning-based criterion for diagnosing a physical system's proximity to criticality.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRSDate not supplied

The View From Out Here: The Solar System Planets as Exoplanet Analogs

As we begin to characterize planets orbiting other stars, one of the most important tools available to us is the collection of disk-integrated solar system observations. To date, these have been limited in how they match up with expected exoplanet observations in terms of wavelength, time, viewing geometry, and separations. The Interstellar Probe mission could push the boundaries of planetary science by providing a much-needed and unique dataset for the solar system viewed as an extrasolar system in advance of the next generation of ground and space-based telescopes. Viewing the solar system at large separations over a long period serves several purposes. It acts as a practical test directly analogous to exoplanet observations under realistic conditions, including such effects as zodiacal dust (e.g., Roberge et al., 2012). Secondly, it allows for both the validation of forward models (that is, simulating a planet and generating spectra) and retrievals (where some of the planetary properties are not known) (e.g., Robinson et al., 2011; Agarwal and Wettlaufer, 2017). Third, the mission pro le would be able to collect data at both high- and low-phase angles, which are lacking for most of the solar system planets (e.g., Mallama and Hilton, 2018). Lastly, the long duration of the proposed mission would allow not only snapshots, but time resolved observations using the same instrument, highlighting the dynamic nature of the planets (e.g., seasonality, storms). The planets need not be resolved to make these observations, which eases instrumentation requirements. Here, we show simulations of what an Interstellar Probe imager would see, improving on work that was part of a white paper submitted to the Planetary Science and Astrobiology Decadal Survey. The opportunity for multiple full orbits for most of the solar system planets, including a full phase curve of Saturn, is unique and worth pursuing during the development of the Interstellar Probe mission.

Chester Harman↗
DOE OSTI2022

Classification of Cloud Particle Imagery from Aircraft Platforms Using Convolutional Neural Networks

Abstract A vast amount of ice crystal imagery exists from a variety of field campaign initiatives that can be utilized for cloud microphysical research. Here, nine convolutional neural networks are used to classify particles into nine regimes on over 10 million images from the Cloud Particle Imager probe, including liquid and frozen states and particles with evidence of riming. A transfer learning approach proves that the Visual Geometry Group (VGG-16) network best classifies imagery with respect to multiple performance metrics. Classification accuracies on a validation dataset reach 97% and surpass traditional automated classification. Furthermore, after initial model training and preprocessing, 10 000 images can be classified in approximately 35 s using 20 central processing unit cores and two graphics processing units, which reaches real-time classification capabilities. Statistical analysis of the classified images indicates that a large portion (57%) of the dataset is unusable, meaning the images are too blurry or represent indistinguishable small fragments. In addition, 19% of the dataset is classified as liquid drops. After removal of fragments, blurry images, and cloud drops, 38% of the remaining ice particles are largely intersecting the image border (≥10% cutoff) and therefore are considered unusable because of the inability to properly classify and dimensionalize. After this filtering, an unprecedented database of 1 560 364 images across all campaigns is available for parameter extraction and bulk statistics on specific particle types in a wide variety of storm systems, which can act to improve the current state of microphysical parameterizations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Peculiarities of the phase transformation dynamics in bulk FeRh based alloys from magnetic and structural measurements

We analyze coexistence of antiferromagnetic and ferromagnetic phases in bulk iron-rhodium and its alloys with palladium, Fe 50,4 Rh 49,6 , Fe 49,7 Rh 47,4 Pd 2,9 and Fe 48,3 Rh 46,8 Pd 4,9 , using neutron diffraction, magnetization and scanning Hall probe imaging. Temperature dependencies of the lattice parameters, AFM and FM phase weight fractions, and Fe magnetic moment values were obtained on cooling and heating across the AFM-FM transition. Substantial thermomagnetic hysteresis for the phases’ weight fractions and a relatively narrow one for the unit cell volume has been observed on cooling-heating. Furthermore, a clear dependence of hysteretic behavior on Pd concentration has been traced. Additional direct magnetic measurements of the spatial distribution of the phase transition are acquired using scanning Hall probe microscopy, which reveals the length scale of the phase coexistence and the spatial progression of the transition in the presence of external magnetic field. Also, the magnetic phase diagram has been constructed for a series of Pd-doped FeRh alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Sub-10 nm upconversion nanocrystals for long-term single-particle tracking

Lanthanide-doped upconversion nanoparticles are attractive single-molecule imaging probes due to their high photostability and anti-Stokes luminescence. However, achieving both small particle size and strong brightness has remained a major challenge, as reducing size often leads to dimmer emission. Herein, we fabricate a sub-10 nm cascade actively protected upconversion nanoparticles, which shows a 33-fold enhanced upconversion efficiency at the single-particle level compared to larger ~19 nm conventional nanoparticles. Theoretical modeling and time-resolved measurements show that emission loss mainly comes from energy leakage of Er 3+ ions to surface defects. By introducing a NaYbF 4 layer as photon-harvesting and protective intermediate layer, we minimize this energy loss and significantly boost brightness. A monolayer of inert NaLuF 4 can effectively suppress the surface quenching to Yb 3+ . Using these ultra-small bright probes, we successfully tracked single epidermal growth factor receptor molecules on live cells for up to one hour, revealing dynamic switching between different diffusion modes.

Qiu, Xiaochen [Fudan Univ., Shanghai (China); Shen↗
DOE OSTI2022

Radar Retrieval Evaluation and Investigation of Dendritic Growth Layer Polarimetric Signatures in a Winter Storm

Abstract This study evaluates ice particle size distribution and aspect ratio φ Multi-Radar Multi-Sensor (MRMS) dual-polarization radar retrievals through a direct comparison with two legs of observational aircraft data obtained during a winter storm case from the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign. In situ cloud probes, satellite, and MRMS observations illustrate that the often-observed K dp and Z DR enhancement regions in the dendritic growth layer can either indicate a local number concentration increase of dry ice particles or the presence of ice particles mixed with a significant number of supercooled liquid droplets. Relative to in situ measurements, MRMS retrievals on average underestimated mean volume diameters by 50% and overestimated number concentrations by over 100%. IWC retrievals using Z DR and K dp within the dendritic growth layer were minimally biased relative to in situ calculations where retrievals yielded −2% median relative error for the entire aircraft leg. Incorporating φ retrievals decreased both the magnitude and spread of polarimetric retrievals below the dendritic growth layer. While φ radar retrievals suggest that observed dendritic growth layer particles were nonspherical (0.1 ≤ φ ≤ 0.2), in situ projected aspect ratios, idealized numerical simulations, and habit classifications from cloud probe images suggest that the population mean φ was generally much higher. Coordinated aircraft radar reflectivity with in situ observations suggests that the MRMS systematically underestimated reflectivity and could not resolve local peaks in mean volume diameter sizes. These results highlight the need to consider particle assumptions and radar limitations when performing retrievals. significance statement Developing snow is often detectable using weather radars. Meteorologists combine these radar measurements with mathematical equations to study how snow forms in order to determine how much snow will fall. This study evaluates current methods for estimating the total number and mass, sizes, and shapes of snowflakes from radar using images of individual snowflakes taken during two aircraft legs. Radar estimates of snowflake properties were most consistent with aircraft data inside regions with prominent radar signatures. However, radar estimates of snowflake shapes were not consistent with observed shapes estimated from the snowflake images. Although additional research is needed, these results bolster understanding of snow-growth physics and uncertainties between radar measurements and snow production that can improve future snowfall forecasting.

Meteorology & Atmospheric Sciences↗
DOE OSTI2020

Chemical and bonding analysis of liquids using liquid cell electron microscopy

Liquid cell transmission electron microscopy (TEM) has become an essential tool for studying the structure and properties of both hard and soft condensed-matter samples, as well as liquids themselves. Liquid cell sample holders, often consisting of two thin window layers separating the liquid sample from the high vacuum of the microscope column, have been designed to control in situ conditions, including temperature, voltage/current, or flow through the window region. While high-resolution and time-resolved TEM imaging probes the structure, shape, and dynamics of liquid cell samples, information about the chemical composition and spatially resolved bonding is often difficult to obtain due to the liquid thickness, the window layers, the holder configuration, or beam-induced radiolysis. Here, we review different approaches to quantitative liquid cell electron microscopy, including recent developments to perform energy-dispersive x-ray and electron energy-loss spectroscopy experiments on samples in a liquid environment or the liquid itself. We also cover graphene liquid cells and other ultrathin window layer holders.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1993

Remote sensing estimates of cirrus particle size for tropical and midlatitude cirrus: Hexagonal crystals and ice spheres

A large discrepancy exists in current estimates of a mean cirrus particle size appropriate for calculations of the effects of these ice clouds on solar and thermal infrared radiative fluxes. For spheres with large size parameter (x = (2 pi r / lambda) is greater than 30, where r is particle radius), and moderate absorption (n(sup i) x less than 1, where n(sup i) is imaginary index of refraction for ice), the optimal effective particle radius is given by: r(sub e) = integral of r(exp 3)n(r)dr / integral of r(exp 2)n(r)dr. For the remote sensing of cirrus particle size at wavelengths of 0.83, 1.65, and 2.21 mu m, a 50 mu m ice sphere would have a size parameter of about 200, and values of n(sup i) x of 0, 0.045, and 0.06, satisfying the above conditions. However, while r(sub e) is a well-defined parameter for spheres, this cross-section area-weighted particle radius can only be extended to non-spherical particles by defining some equivalent sphere, typically an equivalent volume or equivalent cross-section area sphere. Using equivalent volume spheres, values of r(sub e) obtained over Lake Michigan on October 28, 1986, during FIRE phase I varied from 200 mu m (King Air 2D Imaging probes) to 60 mu m (Landsat reflectances at 0.83, 1.65, and 2.2 mu m), to 25 mu m (HIS spectrometer thermal emission between 8 and 12 mu m). Three major uncertainties were identified in this comparison: small ice particles missed by the 2D-C aircraft probes, uncertain ice refractive index, and uncertainties in the single scatter albedos and scattering phase functions used in the radiative calculations. Since the first FIRE cirrus results, advances have been made in all three areas. The present paper reports on improvements in the radiative modeling of ice particles at 0.83, 1.65, and 2.21 mu m wavelengths appropriate for comparisons to Landsat Thematic Mapper data. The paper also includes new results for Landsat observations of ice clouds in the eastern and western tropical Pacific.

Wielicki, Bruce A.↗
NASA NTRS1995

Hubble Space Telescope imaging of a radio-quiet galaxy at redshift z = 3.4

We have observed with the Wide Field/Planetary Camera (WF/PC) on the Hubble Space Telescope (HST) a radio-quiet Ly alpha-emitting galaxy at redshift z = 3.428 (G2 below). The images probe the rest-frame UV light around 1250 A with an angular resolution of approx. = 0.1 sec, corresponding to 1.4 h(exp -1, sub 50) kpc at redshift z = 3.4 (in this Letter we use q(sub 0) = 0 and H(sub 0) = 50 h(exp -1, sub 50) km/s/Mpc). The light profile of the central approx. 10h(exp -1, sub 50) kpc region is well fitted by an r(exp 1/4) law with r(sub e) approx. = 1.3 h(exp -1, sub 50) kpc, suggesting a dynamically relaxed state. The outer regions are characterized by the presence of substructures, such as an elongated formation and low surface brightness nebulosities. The isophotal analysis shows no evidence of an active galactic nuclei (AGN)-like unresolved source in the center. The structural properties of G2 are consistent with a dynamically hot stellar system observed during an early phase of star formation, very likely the progenitor of an elliptical or the bulge of a spiral galaxy.

Giavalisco, Mauro↗
NASA NTRS2002

Advanced Ultrasonic Diagnosis of Extremity Trauma: The Faster Exam

Ultrasound is of prO)len accuracy in abdominal and thoracic trauma and may be useful to diagnose extremity injury in situations where radiography is not available such as military and space applications. We prospectively evaluated the utility of extremity , ultrasound performed by trained, non-physician personnel in patients with extremity trauma, to simulate remote aerospace or military applications . Methods: Patients with extremity trauma were identified by history, physical examination, and radiographic studies. Ultrasound examination was performed bilaterally by nonphysician personnel with a portable ultrasound device using a 10-5 MHz linear probe, Images were video-recorded for later analysis against radiography by Fisher's exact test. The average time of examination was 4 minutes. Ultrasound accurately diagnosed extremity, injury in 94% of patients with no false positive exams; accuracy was greater in mid-shaft locations and least in the metacarpa/metatarsals. Soft tissue/tendon injury was readily visualized . Extremity ultrasound can be performed quickly and accurately by nonphysician personnel with excellent accuracy. Blinded verification of the utility of ultrasound in patients with extremity injury should be done to determine if Extremity and Respiratory evaluation should be added to the FAST examination (the FASTER exam) and verify the technique in remote locations such as military and aerospace applications.

Dulchavsky, S. A.↗
NASA NTRS2012

Direct Imaging of Extra-Solar Planets in Star Forming Regions: Lessons Learned from a False Positive Around IM Lup

Context. Most exoplanet imagers consist of ground-based adaptive optics coronagraphic cameras which are currently limited in contrast, sensitivity and astrometric precision, but advantageously observe in the near-infrared window (1 5 m). Because of these practical limitations, our current observational aim at detecting and characterizing planets puts heavy constraints on target selection, observing strategies, data reduction, and follow-up. Most surveys so far have thus targeted young systems (1 100 Myr) to catch the putative remnant thermal radiation of giant planets, which peaks in the near-infrared. They also favor systems in the solar neighborhood (d less than 80 pc), which eases angular resolution requirements but also ensures a good knowledge of the distance and proper motion, which are critical to secure the planet status, and enable subsequent characterization. Aims. Because of their youth, it is very tempting to target the nearby star forming regions, which are typically twice as far as the bulk of objects usually combed for planets by direct imaging. Probing these interesting reservoirs sets additional constraints that we review in this paper by presenting the planet search that we initiated in 2008 around the disk-bearing T Tauri star IM Lup, which is part of the Lupus star forming region (140-190 pc). Methods. We show and discuss why age determination, the choice of evolutionary model for both the central star and the planet, precise knowledge of the host star proper motion, relative or absolute (between different instruments) astrometric accuracy (including plate scale calibration), and patience are the key ingredients for exoplanet searches around more distant young stars. Results. Unfortunately, most of the time, precision and perseverance are not paying off: we discovered a candidate companion around IM Lup in 2008, which we report here to be an unbound background object. We nevertheless review in details the lessons learned from our endeavor, and additionally present the best detection limits ever calculated for IM Lup. We also accessorily report on the successful use of innovative data reduction techniques, such as the damped-LOCI and iterative roll subtraction.

D Mawet↗
NASA NTRS2013

A Summary of Large Raindrop Observations from GPM GV Field Campaigns

NASA's Global Precipitation Measurement Mission (GPM) has conducted as series of Ground Validation (GV) studies to assist algorithm development for the GPM core satellite. Characterizing the drop size distribution (DSD) for different types of precipitation systems is critical in order to accurately estimate precipitation across the majority of the planet. Thus far, GV efforts have sampled DSDs in a variety of precipitation systems from Finland to Oklahoma. This dataset consists of over 33 million raindrops sampled by GPM GV's two‐dimensional video disdrometers (2DVD) and includes RSD observations from the LPVEx, MC3E, GCPEx, HyMEx and IFloodS campaigns as well as from GV sites in Huntsville, AL and Wallops Island, VA. This study focuses on the larger end of the raindrop size spectrum, which greatly influences radar reflectivity and has implications for moment estimation. Thus knowledge of the maximum diameter is critical to GPM algorithm development. There are over 24,000 raindrops exceeding 5 mm in diameter contained within this disdrometer dataset. The largest raindrops in the 2DVD dataset (>7‐8 mm in diameter) are found within intense convective thunderstorms, and their origins are believed to be hailstones. In stratiform rainfall, large raindrops have also been found to fall from lower and thicker melting layers. The 2DVD dataset will be combined with that collected by dual‐polarimetric radar and aircraft particle imaging probes to "follow" the vertical evolution of the DSD tail (i.e., retrace the large drops from the surface to their origins aloft).

Gatlin, Patrick N.↗
NASA NTRS2018

Profiling Supercooled Liquid Water Clouds with Multi-Frequency Radar

An optimal estimation scheme is employed to demonstrate the utility of using multi-band radar observations for estimating supercooled liquid profiles. Qualitative comparisons with microphysical probe images show that the retrievals are capable of producing supercooled liquid consistent with in situ data. Finally, a path forward for quantifying performance and extending the study to a more robust measurement suite is given.

supercooled liquid↗
NASA NTRS2021

Preconditioning of overcast-to-broken cloud transitions by riming in marine cold air outbreaks

Marine cold air outbreaks (CAOs) commonly form overcast cloud decks that transition into broken cloud fields downwind, dramatically altering the local radiation budget. In this study, we investigate the impact of frozen hydrometeors on these transitions. We focus on a CAO case in the NW Atlantic, the location of the multi-year flight campaign ACTIVATE (Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment). We use MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, version 2) reanalysis fields to drive large eddy simulations with mixed-phase two-moment microphysics in a Lagrangian framework. We find that transitions are triggered by substantial rain (rainwater paths >25 g m−2), and only simulations that allow for aerosol depletion result in sustained breakups, as observed. Using a range of diagnostic ice nucleating particle concentrations, Ninp, we find that increasing ice progressively accelerates transitions, thus abbreviating the overcast state. Ice particles affect the cloud-topped boundary layer evolution, primarily through riming-related processes prior to substantial rain, leading to (1) a reduction in cloud liquid water, (2) early consumption of cloud condensation nuclei, and (3) early and light precipitation cooling and moistening below cloud. We refer to these three effects collectively as “preconditioning by riming”. Greater boundary layer aerosol concentrations available as cloud condensation nuclei (CCN) delay the onset of substantial rain. However, cloud breakup and low CCN concentration final stages are found to be inevitable in this case, due, primarily, to liquid water path buildup. An ice-modulated cloud transition speed suggests the possibility of a negative cloud–climate feedback. To address prevailing uncertainties in the model representation of mixed-phase processes, the magnitude of ice formation and riming impacts and, thereby, the strength of an associated negative cloud–climate feedback process, requires further observational evaluation by targeting riming hot spots with in situ imaging probes that allow for both the characterization of ice particles and abundance of supercooled droplets.

Marine cold air outbreaks↗
NASA NTRS2023

Evaluation of SWER(Ze) Relationships by Precipitation Imaging Package (PIP) during ICE-POP 2018

Improving estimation of snow water equivalent rate (SWER) from radar reflectivity (Ze), known as a SWER(Ze) relationship, is a priority for NASA’s Global Precipitation Measurement (GPM) mission ground validation program as it is needed to comprehensively validate spaceborne precipitation retrievals. This study investigates the performance of eight operational and four research-based SWER(Ze) relationships utilizing Precipitation Imaging Probe (PIP) observations from the International Collaborative Experiment for Pyeongchang 2018 Olympic and Paralympic Winter Games (ICE-POP 2018) field campaign. During ICE-POP 2018, there were 10 snow events that are classified by synoptic conditions as either cold low or warm low, and a SWER(Ze) relationship is derived for each event. Additionally, a SWER(Ze) relationship is derived for each synoptic classification by merging all events within each class. Two new types of SWER(Ze) relationships are derived from PIP measurements of bulk density and habit classification. These two physically based SWER(Ze) relationships provided superior estimates of SWER when compared to the operational, event-specific, and synoptic SWER(Ze) relationships. For estimates of the event snow water equivalent total, the event-specific, synoptic, and best-performing operational SWER(Ze) relationships outperformed the physically based SWER(Ze) relationship, although the physically based relationships still performed well. This study recommends using the density or habit-based SWER(Ze) relationships for microphysical studies, whereas the other SWER(Ze) relationships are better suited toward hydrologic application.

Ali Tokay↗
DOE OSTI2020

Inorganic semiconductor quantum dots as a saturated excitation (SAX) probe for subdiffraction imaging

The photoluminescence (PL) saturation of CdSe/ZnS core/shell inorganic semiconductor quantum dots (QDs) and its utility as a probe for saturated excitation (SAX) microscopy are reported. Under saturating excitation power densities, the PL signal was demodulated and recorded at harmonics of the fundamental frequency. For commercially available Qdot® 655 ITK™ QDs, the power density required to achieve saturation was dependent upon the local environment of the QDs. For QDs deposited and dried on a glass substrate, the excitation power density required for PL saturation was less than 1 kW/cm 2 . Compared to this, saturation of PL for QDs dispersed in water required an excitation power density greater than 200 kW/cm 2 . This observation is manifested as a limitation in the imaging of hydrated samples, as demonstrated for HeLa cells labelled with biotinylated-phalloidin followed by labelling with streptavidin-coated QDs. Finally as saturation affects the obtained spatial resolution in several imaging formats, including confocal imaging, the provided data will aid in obtaining the optimal spatial resolution when using QD probes to image biological samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗