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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The Development of a Generalized Riser Flow Regime Map Based Upon Higher Moment and Chaotic Statistics Using Electrical Capacitance Volume Tomography (ECVT)

Dynamic analyses have been applied to the temporal signals from an Electro Capacitance Volume Tomography instrument located near mid-height on the riser of an industrial-scale cold-flow circulating fluidized bed to characterize gas-solids flow behavior in the riser. Twelve capacitance electrodes surround the cylindrical riser over a height of 1.3 m. The instrument used a neural network deconvolution algorithm to determine the spatially resolved solids fraction recorded at 52 Hz. Experiments were carried out over a range of gas and solids flows in the transport regime using a Geldart Group B bed material, high density polyethylene with mean particle size of 880 μm. The radial solids distribution was found to vary from one-time step to the next between profiles typical of laminar and turbulent flow. The duration of time spent in each of these flow profiles depended upon the operating regime – dilute, core-annular, or fast fluidized bed. The chaotic structure of the temporal data was characterized using the three conventional approaches: the first 4 moments from the distribution of signal in time, system memory parameters from the autocorrelation function and the Hurst exponent, and analysis of the correlationentropy and correlation dimension of the attractor. These signal analysis techniques were used to clearly distinguish differences between different transport operating regimes. Specifically, it was experimentally observed that a riser transitions from core annular flow profile to dilute and dense regimes via increasing the frequency of short term transients to either dilute or dense flow profiles, respectively. A regime map was generated based upon these dynamics using solids flux and gas velocity axes. Fast fluidized, core annular, and dilute each exhibited different degree of dynamic characteristics typical of fluid dominated or particle compromising behavior. It should be noted that the magnitude for the different statistics was in the same range regardless of the regime, it was the radial profile for the statistic that changed and subsequently identified that there was a change in the regime. Finally, a reduced regime map was developed consisting of plotting the gas velocity normalized by the upper transport velocity versus the solids flux normalized by the saturation carrying capacity. The use of this reduced plot allowed the data from widely different conditions to be plotted and compared on the same<p>graph. Note that in many instances, some of the statistics identified the operating point as being in one regime while others indicated that it was in another indicating a transition region between dilute or core annular regimes and between the core annular and fast fluidization regimes. This now provides a tool that can be used to optimize process performance, identify changes in operating states, or replicate process dynamics during process scaling or changing operating parameters. </p>

Breault, Ronald↗
DOE OSTI2024

Leveraging Extremal Dependence to Better Characterize the 2021 Pacific Northwest Heatwave

Abstract In late June, 2021, a devastating heatwave affected the US Pacific Northwest and western Canada, breaking numerous all-time temperature records by large margins and directly causing hundreds of fatalities. The observed 2021 daily maximum temperature across much of the U.S. Pacific Northwest exceeded upper bound estimates obtained from single-station temperature records even after accounting for anthropogenic climate change, meaning that the event could not have been predicted under standard univariate extreme value analysis assumptions. In this work, we utilize a flexible spatial extremes model that considers all stations across the Pacific Northwest domain and accounts for the fact that many stations simultaneously experience extreme temperatures. Our analysis incorporates the effects of anthropogenic forcing and natural climate variability in order to better characterize time-varying changes in the distribution of daily temperature extremes. We show that greenhouse gas forcing, drought conditions and large-scale atmospheric modes of variability all have significant impact on summertime maximum temperatures in this region. Our model represents a significant improvement over corresponding single-station analysis, and our posterior medians of the upper bounds are able to anticipate more than 96% of the observed 2021 high station temperatures after properly accounting for extremal dependence. Supplementary materials accompanying this paper appear online.

Zhang, Likun (ORCID:0000000154584556)↗
DOE OSTI2021

How much information on precipitation is contained in satellite infrared imagery?

Satellite infrared (IR) brightness temperature providing information on the characteristics of cloud tops is one of the primary input data used for estimating precipitation from satellites. Thus, the natural questions to ask are: Does IR imagery contain more information about precipitation in some regions more than others? What are the factors that lead to such differences? Should we expect the amount of information provided by IR imagery to change with respect to temporal or spatial aggregation? Comprehensive analysis of the accuracy of satellite-based precipitation estimates obtained from any given algorithm may provide qualitative answers to the above questions. However, such an approach only offers conclusions within the limited context of the algorithm used to obtain precipitation estimates; that is, patterns caused by the inherent information content of IR imagery are inextricable from those induced by assumptions embedded in the precipitation estimation algorithm. Here, we address the abovementioned questions from a different perspective using an information-theoretic measure, free of structural assumptions and general to a wide range of relationships, to characterize the average and seasonal dependence between IR imagery provided by satellite sensors in the spectral range (10.7–11.5 μm) and precipitation rates in the contiguous United States (CONUS) across distinct temporal and spatial scales. We analyze a total of more than 1.3 billion pairs of IR and precipitation observations over CONUS, and we observe interesting patterns. First, we show that there is a strong inverse relationship (ρ = - 0.73) between the information content of IR data and the number of no-rain observations; however, its robustness varies regionally and seasonally with less significant correlation during the warm season. Second, we demonstrate that the intuitive relationship of increasing dependence between IR and precipitation as a result of temporal or spatial aggregation exhibits a diminishing returns behavior. For instance, temporal aggregation from 1 to 3 h increases the dependence approximately 7 times as much as temporal aggregation from 12 to 24 h. Furthermore, we quantitatively examine and re-confirm several statements previously reported in the literature such as the strong association between IR and precipitation in convective storms and the low association in orographic rainfall. Finally, we conclude by illustrating the potential of the analysis in diagnosis of operational algorithms for estimating precipitation from IR brightness temperature. The findings of this study pinpoint spatial domains and time scales at which IR is not an adequate proxy for estimating precipitation. Thus, they can potentially guide the development of operational algorithms that utilize satellite Infrared imagery for estimating, downscaling and data fusion of precipitation. Finally, the analysis presented here opens up the possibility of developing new methodologies for diagnosis of satellite-based precipitation estimation algorithms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Mapping foliar photosynthetic capacity in sub-tropical and tropical forests with UAS-based imaging spectroscopy: Scaling from leaf to canopy

Accurate understanding of the variability in foliar physiological traits across landscapes is critical to improve parameterization and evaluation of terrestrial biosphere models (TBMs) that seek to represent the response of terrestrial ecosystems to a changing climate. Numerous studies suggest imaging spectroscopy can characterize foliar biochemical and morphological traits at the canopy scale, but there is only limited evidence for retrieving canopy photosynthetic capacity (e.g., maximum carboxylation rate, V c,max and maximum electron transport rate, J max ). Moreover, the effect of canopy structure within forest communities on scaling up spectra-trait relationships from leaf to canopy level is not well known. To advance the spectra-trait approach and enable the estimation of key traits using remote sensing, we collected imaging spectroscopy data from an Unoccupied Aerial System (UAS) platform over two forest sites in China (a subtropical forest in Mt. Dinghu and a tropical rainforest in Xishuangbanna). At these sites, we also collected ground measurements of leaf spectra and traits, including biochemical (leaf nitrogen, phosphorus, chlorophyll, and water content), morphological (leaf mass per area, LMA) and physiological (V c,max25 and J max25 ) traits (n=135 tree-crowns from 42 species across two sites). Using a partial least-squares regression (PLSR) approach, we built and tested spectra-trait models with repeated cross-validation. The spectral models developed with leaf spectra were directly transferred to canopy spectra to evaluate the effect of canopy structure. Here we further applied canopy spectral models to map these traits at individual tree-crown scale. The results demonstrate that (1) UAS-based canopy spectra can be used to estimate V c,max (R 2 =0.55, nRMSE=11.79%), Jmax (R 2 =0.54, nRMSE=12.34%), and five additional foliar traits (R 2 =0.38-0.60, nRMSE=10.11-13.56%) at the tree-crown scale with demonstrated generalizability across two sites; (2) canopy structure strongly affects the spectratrait relationships from leaf to canopy level, but the effects vary considerably across foliar traits and cannot be well captured by the 4SAIL canopy radiative transfer model. UAS-based imaging spectroscopy maps large variability in all foliar traits (including physiological traits) with spatially explicit information, reproducing the field-observed inter- and intra-specific variations. These results demonstrate the capability of using UAS-based imaging spectroscopy for characterizing the variability of foliar physiological traits at individual tree-crown scale over forest landscapes and highlight the similar generalizability but different biophysical mechanisms underlying spectra-trait relationships at leaf and canopy levels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Synthesizing models useful for ecohydrology and ecohydraulic approaches: An emphasis on integrating models to address complex research questions

Ecohydrology combines empiricism, data analytics, and the integration of models to characterize linkages between ecological and hydrological processes. A challenge for practitioners is determining which models best generalizes heterogeneity in hydrological behaviour, including water fluxes across spatial and temporal scales, integrating environmental and socio–economic activities to determine best watershed management practices and data requirements. We conducted a literature review and synthesis of hydrologic, hydraulic, water quality, and ecological models designed for solving interdisciplinary questions. We reviewed 1,275 papers and identified 178 models that have the capacity to answer an array of research questions about ecohydrology or ecohydraulics. Of these models, 43 were commonly applied due to their versatility, accessibility, user–friendliness, and excellent user–support. Forty–one of 43 reviewed models were linked to at least 1 other model especially: Water Quality Analysis Simulation Program (linked to 21 other models), Soil and Water Assessment Tool (19), and Hydrologic Engineering Center's River Analysis System (15). However, model integration was still relatively infrequent. There was substantial variation in model applications, possibly an artefact of the regional focus of research questions, simplicity of use, quality of user–support efforts, or a limited understanding of model applicability. Simply increasing the interoperability of model platforms, transformation of models to user–friendly forms, increasing user–support, defining the reliability and risk associated with model results, and increasing awareness of model applicability may promote increased use of models across subdisciplines. Furthermore, the current availability of models allows an array of interdisciplinary questions to be addressed, and model choice relates to several factors including research objective, model complexity, ability to link to other models, and interface choice.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

A hierarchical analysis of the impact of methodological decisions on statistical downscaling of daily precipitation and air temperatures

Despite the widespread application of statistical downscaling tools, uncertainty remains regarding the role of model formulation in determining model skill for daily maximum and minimum temperature (Tmax and Tmin), and precipitation occurrence and intensity. Impacts of several key aspects of statistical transfer function form on model skill are evaluated using a framework resistant to model overspecification. We focus on: (a) model structure: simple (generalized linear models, GLMs) versus complex (artificial neural networks, ANNs) models. (b) Predictor selection: Fixed number of predictors chosen a priori versus stepwise selection of predictors and inclusion of grid point values versus predictors derived from application of principal components analysis (PCA) to spatial fields. We also examine the influence of domain size on model performance. For precipitation downscaling, we consider the role of the threshold used to characterize a wet day and apply three approaches (Poisson and Gamma distributions in GLM and ANN) to downscale wet-day precipitation amounts. While no downscaling formulation is optimal for all predictands and at 10 locations representing diverse U.S. climates, and due to the exclusion of variance inflation all of the downscaling formulations fail to reproduce the range of observed variability, models with larger suites of prospective predictors generally have higher skill. For temperature downscaling, ANNs generally outperform GLM, with greater improvements for T min than T max . Furthermore, use of PCA-derived predictors does not systematically improve model skill, but does improve skill for temperature extremes. Model skill for precipitation occurrence generally increases as the wet-day threshold increases and models using PCA-derived predictors tend to outperform those based on grid cell predictors. Each model for wet-day precipitation intensity overestimates annual total precipitation and underestimates the proportion derived from extreme precipitation events, but ANN-based models and those with larger predictor suites tend to have the smallest bias.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Goldstone boson equivalence for inflation

The effective field theory of single-field inflation characterizes the inflationary epoch in terms of a pattern of symmetry breaking. An operator acquires a time-dependent vacuum expectation value, defining a preferred spatial slicing. In the absence of dynamical gravity, the fluctuations around the time-dependent background are described by the Goldstone boson associated with this symmetry breaking process. With gravity, the Goldstone is eaten by the metric, becoming the scalar metric fluctuation. In this paper, we will show that in general single-field inflation, the statistics of scalar metric fluctuations are given by the statistics of this Goldstone boson decoupled from gravity up to corrections that are controlled as an expansion in slow-roll parameters. This even holds in the presence of additional parameters, like the speed of sound, that naively enhance the impact of the gravitational terms. In the process, we derive expressions for leading and sub-leading gravitational corrections to all-orders in the Goldstone boson.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Ordering effects on deformation substructures and strain hardening behavior of a CrCoNi based medium entropy alloy

Here, a CrCoNi based medium entropy alloy with small additions of Ti, Al and Nb (denoted as (CrCoNi) 93 Al 4 Ti 2 Nb) in the as-quenched condition, exhibits tensile properties comparable to those of the equiatomic CrCoNi alloy at room temperature. Dark field transmission electron microscopy (TEM), atomic resolution high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) together with atom probe tomography (APT) show that spatially-localized long range ordering (LRO) L1 2 domains exist in this alloy. The evolution of deformation substructure with plastic deformation in this alloy was characterized using electron backscatter diffraction (EBSD), electron channeling contrast imaging (ECCI) and STEM based techniques including the recently developed weak beam dark field STEM imaging. Plastic deformation occurs by the slip of a/2<110>dislocations, which are narrowly dissociated into Shockley partial dislocations on {111} slip planes. Their dissociation distances in the (CrCoNi) 93 Al 4 Ti 2 Nb alloy are much smaller than the widths of the corresponding partials in the equiatomic CrCoNi alloy due to one or more of the minor alloying elements (Al, Ti, Nb). Dislocation slip in this alloy has a pronounced planar character. The leading dislocations in slip bands glide as pairs due to the existence of LRO domains. Multipoles were formed through the slip of dislocations with opposite signs on adjacent {111} slip planes. Those multipoles serve as building blocks for the formation of subgrain structures consisting of fine slip bands. The distances between slip bands were continuously refined during plastic deformation and dynamic refinement of slip bands plays a crucial role in strain hardening. The effects of LRO domains on planar dislocation slip, the deactivation of deformation twinning and strain hardening of this alloy are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A hybrid architecture for volt-var control in active distribution grids

Modern active distribution grids are characterized by the increasing penetration of distributed energy resources (DERs). The proper coordination and scheduling of a large numbers of these small-scale and spatially distributed DERs is necessary, and warrants the use of novel distributed approaches. In this paper, we propose a hybrid volt-var control architecture for the distribution grid, which leverages existing centralized and local approaches to planning, decision making, and control, and augments it with distributed optimization and distributed control for DER management. First, we propose a convex model to describe the power physics of distribution grids of meshed topology and unbalanced structure, based on current injection and McCormick Envelopes. Second, we employ the distributed proximal atomic coordination (PAC) algorithm to coordinate DERs to provide voltage support. We implement volt-var optimization by optimally coordinating DERs including PV smart inverters and demand response. We present results using the IEEE-34 bus network, using real data from a distribution feeder in Hawaii, to model load and PV generation. Different levels of DER penetration and objective functions are simulated. Finally, our results show the need for the coordination of DERs to improve voltage profiles, even in networks with existing voltage control devices. Further, we show the need for flexible reactive power capabilities to achieve desired grid performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

In-situ visualization of corrosion behavior of Al CoCrFeNi high-entropy alloys during electrochemical polarization

In this study, the corrosion behavior of the Al x CoCrFeNi (x = 0.3, 0.5, 0.7) high-entropy alloys (HEAs) is investigated by an in-situ visualization system. Surface morphology changes on both micro-spatial and temporal scales are monitored in the 3.5 wt% NaCl solution during the potentiodynamic polarization. The microstructures of the Al x CoCrFeNi HEAs are characterized by SEM, EBSD, and EDS. The results show that the microstructure evolves from singe face-centered cubic (FCC) phase to multi-phases by increasing the Al content. The in-situ observations directly reveal the different localized corrosion processes in the AlxCoCrFeNi HEAs. In the single FCC phase Al 0.3 CoCrFeNi HEA, localized corrosion shows in the form of pitting. In the Al 0.5 CoCrFeNi and Al 0.7 CoCrFeNi alloys, which possess FCC and body-centered cubic (BCC) phases, the localized corrosion initiates and propagates in the Cr-depleted BCC phase. In addition, the in-situ visualization uncovers the evolution of current serration, which represents the propagation and repassivation of metastable pit during the polarization. The frequent occurrence of metastable pits indicates distinct repassivation ability of the Al 0.3 CoCrFeNi HEA.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Accelerating Quantum Materials Development with Advances in Transmission Electron Microscopy

Quantum materials are driving a technology revolution in sensing, communication, and computing, while simultaneously testing many core theories of the past century. Materials such as topological insulators, complex oxides, superconductors, quantum dots, color center-hosting semiconductors, and other types of strongly correlated materials can exhibit exotic properties such as edge conductivity, multiferroicity, magnetoresistance, superconductivity, single photon emission, and optical-spin locking. These emergent properties arise and depend strongly on the material’s detailed atomic-scale structure, including atomic defects, dopants, and lattice stacking. In this review, we describe how progress in the field of electron microscopy (EM), including in situ and in operando EM, can accelerate advances in quantum materials and quantum excitations. We begin by describing fundamental EM principles and operation modes. We then discuss various EM methods such as (i) EM spectroscopies, including electron energy loss spectroscopy (EELS), cathodoluminescence (CL), and electron energy gain spectroscopy (EEGS); (ii) four-dimensional scanning transmission electron microscopy (4D-STEM); (iii) dynamic and ultrafast EM (UEM); (iv) complementary ultrafast spectroscopies (UED, XFEL); and (v) atomic electron tomography (AET). We describe how these methods could inform structure–function relations in quantum materials down to the picometer scale and femtosecond time resolution, and how they enable precision positioning of atomic defects and high-resolution manipulation of quantum materials. For each method, we also describe existing limitations to solve open quantum mechanical questions, and how they might be addressed to accelerate progress. Among numerous notable results, our review highlights how EM is enabling identification of the 3D structure of quantum defects; measuring reversible and metastable dynamics of quantum excitations; mapping exciton states and single photon emission; measuring nanoscale thermal transport and coupled excitation dynamics; and measuring the internal electric field and charge density distribution of quantum heterointerfaces- all at the quantum materials’ intrinsic atomic and near atomic-length scale. Finally, we conclude by describing open challenges for the future, including achieving stable sample holders for ultralow temperature (below 10K) atomic-scale spatial resolution, stable spectrometers that enable meV energy resolution, and high-resolution, dynamic mapping of magnetic and spin fields. With atomic manipulation and ultrafast characterization enabled by EM, quantum materials will be poised to integrate into many of the sustainable and energy-efficient technologies needed for the 21st century.

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

Quartz Dissolution Effects on Flow Channelization and Transport Behavior in Three‐Dimensional Fracture Networks

We perform a set of reactive transport simulations in three-dimensional fracture networks to characterize the impact of geochemical reactions on flow channelization. Flow channelization, a frequently observed phenomenon in porous and fractured subsurface rock formations, results from the spatially variable hydraulic resistance offered by a geological structure. In addition to geo-structural features such as network connectivity, geometry, and hydraulic resistance, geochemical reactions, for example, dissolution and precipitation, can dynamically inhibit or enhance flow channelization. These geochemical processes can change the fracture permeability leading to increased flow channelization, which are localized connected regions of high volumetric flow rates that are seemingly ubiquitous in the subsurface. In our simulations, fractures partially filled with quartz are gradually dissolved until quasi-steady state conditions are obtained. We compare the flow field's initial unreacted and final dissolved states in terms of flow and transport observations. We observe that the dissolved fracture networks provide less resistance to flow and exhibit increased flow channelization when compared to their unreacted counterparts. However, there is substantial variability in the magnitude of these changes which implies that the channelization strongly depends on the network structure. In turn, we identify the interplay between the particular network structure and the impact of geochemical dissolution on flow channelization. The presented results indicate that geological systems that have been weathering or reactive for longer times in older landscapes are likely to have increased flow channelization compared to their equivalent but younger counterparts, which implies a time dependence on flow channelization in fractured media.

Hyman, Jeffrey D.↗
DOE OSTI2021

Optical transient grating pumped X-ray diffraction microscopy for studying mesoscale structural dynamics

Abstract A fundamental understanding of materials’ structural dynamics, with fine spatial and temporal control, underpins future developments in electronic and quantum materials. Here, we introduce an optical transient grating pump and focused X-ray diffraction probe technique (TGXD) to examine the structural evolution of materials excited by modulated light with a precisely controlled spatial profile. This method adds spatial resolution and direct structural sensitivity to the established utility of a sinusoidal transient-grating excitation. We demonstrate TGXD using two thin-film samples: epitaxial BiFeO 3 , which exhibits a photoinduced strain (structural grating) with an amplitude proportional to the optical fluence, and FeRh, which undergoes a magnetostructural phase transformation. In BiFeO 3 , structural relaxation is location independent, and the strain persists on the order of microseconds, consistent with the optical excitation of long-lived charge carriers. The strain profile of the structural grating in FeRh, in comparison, deviates from the sinusoidal excitation and exhibits both higher-order spatial frequencies and a location-dependent relaxation. The focused X-ray probe provides spatial resolution within the engineered optical excitation profile, resolving the spatiotemporal flow of heat through FeRh locally heated above the phase transition temperature. TGXD successfully characterizes mesoscopic energy transport in functional materials without relying on a specific transport model.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Tunable optical metamaterial-based sensors enabled by closed bipolar electrochemistry

Enabled by the proliferation of nanoscale fabrication techniques required to create spatially repeating, sub-wavelength structures to manipulate the behavior of visible-wavelength radiation, optical metamaterials are of increasing interest. Here we develop and characterize a chemical sensing approach based on electrochemical tuning of the optical response function of large-area, inexpensive nanoaperture metamaterials at visible and near-IR wavelengths. Nanosphere lithography is used to create an ordered array of sub-wavelength apertures in a Au film. The spacing of these apertures is established during fabrication, based on the size of the polystyrene nanospheres. Tunable shifts in the transmission spectrum can be produced post-fabrication by electrodeposition of a dissimilar metal, Ag, using the nanoaperture film as one electrode in a 2- electrode closed bipolar electrochemical (CBE) cell, altering hole size, film thickness, and film composition while maintaining hole spacing dictated by the original pattern. Optical transmission spectra acquired under galvanostatic conditions can be expressed as a linear combination of the initial and final (saturated) spectra, and the resulting response function exhibits a sigmoidal response with respect to the amount of charge (or metal) deposited. This architecture is then used to perform optical coulometry of model analytes in a CBE-based analyte-reporter dual cell device, thus expanding the capability of CBE-based sensors. Increasing the exposed electrode area of the analyte cell increases the response of the device, while modifying the circuit resistance alters the balance between sensitivity and dynamic range. These tunable nanoaperture metamaterials exhibit enhanced sensitivity compared to CBE electrochromic reporter cells to the μM to nM concentration range, suggesting further avenues for development of CBE-based chemical sensors as well as application to inexpensive, point-of-care diagnostic devices.

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

Slow electron-phonon relaxation controls the dynamics of the superconducting resistive transition

Here, we investigate the temporal and spatial scales of resistance fluctuations (𝑅 fluctuations) at the superconducting resistive transition accessed through voltage fluctuation measurements in thin epitaxial TiN films. This material is characterized by slow electron-phonon relaxation, which puts it far beyond the applicability range of the textbook scenario of superconducting fluctuations. The measured Lorentzian spectrum of the 𝑅 fluctuations identifies their correlation time, which is nearly constant across the transition region and has no relation to the conventional Ginzburg-Landau timescale. Instead, the correlation time coincides with the energy relaxation time determined by a combination of the electron-phonon relaxation and the relaxation via diffusion into reservoirs. Our data are quantitatively consistent with the model of spontaneous temperature fluctuations and highlight the lack of understanding of the resistive transition in materials with slow electron-phonon relaxation.

critical phenomena↗
DOE OSTI2024

Visual Analytics of Performance of Quantum Computing Systems and Circuit Optimization

Driven by potential exponential speedups in business, security, and scientific scenarios, interest in quantum computing is surging. This interest feeds the development of quantum computing hardware, but several challenges arise in optimizing application performance for hardware metrics (e.g., qubit coherence and gate fidelity). In this work, we describe a visual analytics approach for analyzing the performance properties of quantum devices and quantum circuit optimization. Our approach allows users to explore spatial and temporal patterns in quantum device performance data and it computes similarities and variances in key performance metrics. Detailed analysis of the error properties characterizing individual qubits is also supported. We also describe a method for visualizing the optimization of quantum circuits. The resulting visualization tool allows researchers to design more efficient quantum algorithms and applications by increasing the interpretability of quantum computations.

Chae, Junghoon↗
DOE OSTI2018

Spatial and Quantum Confinement of Si Nanoparticles Deposited by Laser Electrodispersion onto Crystalline Si

C–V characteristics and DLTS spectra of heterostructures made up of layers of closely packed amorphous Si nanoparticles deposited by laser electrodispersion onto single-crystal p-Si substrates have been examined. The patterns observed in the behavior of the C–V characteristics and DLTS spectra measured in the dark and under illumination with white light at various bias pulse voltages U{sub b} and filling pulse voltages U{sub f} suggest that the spatially localized amorphous Si nanoparticles have an average size of less than 2 nm, which is comparable with the de Broglie electron wavelength, and are characterized by quantum confinement. The ground and excited states of quantum dots are formed and exhibit the Stark effect and effects of electricdipole and controllable metastable occupancy under illumination.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Measuring Local Turbulence Along the Optical Path: Multi-Beam Optical Seeing Sensor

Deflection of light along the optical path is a major source of image degradation for ground-based telescopes. Methods have been developed to measure upper atmospheric seeing based on models of the turbulence in the atmosphere, but due to boundary conditions, transmission within telescope enclosures is more complex. The Multi-beam Optical Seeing Sensor (MOSS) directly measures the component of the image quality degradation from inhomogeneity of the index of refraction within the telescope dome. MOSS outputs four near-parallel beams of light that travel along the optical path and are imaged by the telescope’s detector, landing like starlight on the telescope’s focal plane. By using a strobed light source, we can ‘freeze’ the instantaneous index variations transverse to the optical path. This system captures both ‘dome’ and ‘mirror’ seeing. Through plotting the standard deviation of differential motion between pairs of beams, MOSS enables characterization of the length scale of turbulence within the dome. The temporal coherence of temperature gradients can be probed with different pulse lengths, and the spatial coherence by comparing pairs at different separations across the aperture of the telescope. Optical path turbulence measurements, alongside other telemetry metrics, will guide thermal and airflow management to optimize image quality. A MOSS prototype was installed in the 1.2[Formula: see text]m Auxiliary Telescope (AuxTel) at the Vera C. Rubin Observatory in Chile, and preliminary data constrain the optical path turbulence with a lower bound of 1.4 arcsec. The optical path turbulence varied throughout the night of observing.

Astronomical seeing↗