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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Symmetric Bloch oscillations of matter waves

Cold atoms in an optical lattice provide an ideal platform for studying Bloch oscillations. Here we extend Bloch oscillations to two superposed optical lattices that are accelerated away from one another, and show that these symmetric Bloch oscillations can split, reflect, and recombine matter waves coherently. Using the momentum parity symmetry of the Hamiltonian, we map out the energy band structure of the process and show that superpositions of momentum states are created by adiabatically following the ground state of the Hamiltonian. The relative phase and velocity of the two lattices completely determines the trajectories of different branches of the matter wave. Experimentally we demonstrate symmetric Bloch oscillations using cold cesium atoms where we form interferometers with up to 240ℏk momentum splitting, one of the largest coherent momentum splittings achieved to date. This work has applications in macroscopic tests of quantum mechanics, measurements of fundamental constants, and searches for new physics.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Building Extraction at Scale Using Convolutional Neural Network: Mapping of the United States

Establishing up-to-date large scale building maps is essential to understand the urban dynamics, such as estimating population, urban planning, and many other applications. Although many computer vision tasks have been successfully carried out with deep convolutional neural networks, there is a growing need to understand their large scale impact on building mapping with remote sensing imagery. In this paper, taking advantage of the scalability of convolutional neural networks (CNNs) and using only few areas with the abundance of building footprints, for the first time we conduct a comparative analysis of four state-of-the-art CNNs for extracting building footprints across the entire continental United States. The four CNN architectures namely: Branch-out CNN, fully convolutional network (FCN), conditional random field as recurrent neural network (CRFasRNN), and SegNet, support semantic pixelwise labeling and focus on capturing textural information at multiscale. We use 1-meter resolution aerial images from National Agriculture Imagery Program as the test-bed, and compare the extraction results across the four methods. In addition, we propose to combine signed-distance labels with SegNet, the preferred CNN architecture identified by our extensive evaluations, to advance building extraction results to instance level. We further demonstrate the usefulness of fusing additional near IR information into the building extraction framework. Large scale experimental evaluations are conducted and reported using metrics that include: Precision, recall rate, intersection over union, and the number of buildings extracted. With the improved CNN model and no requirement of further postprocessing, we have generated building maps for the United States with an average processing time less than one minute for an area of size &#x223C;<!-- ~ --> 56 km 2 . Finally, the quality of extracted buildings and processing time demonstrated that the proposed CNN based framework fits the need of building extraction at scale.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

SU-E-J-210: Characterizing Tissue Equivalent Materials for the Development of a Dual MRI-CT Heterogeneous Anthropomorphic Phantom Designed Specifically for MRI Guided Radiotherapy Systems

Purpose: MRI guided radiotherapy (MRIgRT) is an emerging technology which will eventually require a proficient quality auditing system. Due to different principles in which MR and CT acquire images, there is a need for a multi-imaging-modality, end-to-end QA phantom for MRIgRT. The purpose of this study is to identify lung, soft tissue, and tumor equivalent substitutes that share similar human-like CT and MR properties (i.e. Hounsfield units and relaxation times). Methods: Materials of interested such as common CT QA phantom materials, and other proprietary gels/silicones from Polytek, SmoothOn, and CompositeOne were first scanned on a GE 1.5T Signa HDxT MR. Materials that could be seen on both T1-weighted and T2-weighted images were then scanned on a GE Lightspeed RT16 CT simulator and a GE Discovery 750HD CT scanner and their HU values were then measured. The materials with matching HU values of lung (−500 to −700HU), muscle (+40HU) and soft tissue (+100 to +300HU) were further scanned on GE 1.5T Signa HDx to measure their T1 and T2 relaxation times from varying parameters of TI and TE. Results: Materials that could be visualized on T1-weighted and T2-weighted images from a 1.5T MR unit and had an appropriate average CT number, −650, −685, 46,169, and 168 HUs were: compressed cork saturated with water, Polytek Platsil™ Gel-00 combined with mini styrofoam balls, radiotherapy bolus material, SmoothOn Dragon-Skin™ and SmoothOn Ecoflex™, respectively. Conclusion: Post processing analysis is currently being performed to accurately map T1 and T2 values for each material tested. From previous MR visualization and CT examinations it is expected that Dragon-Skin™, Ecoflex™ and bolus will have values consistent with tissue and tumor substitutes. We also expect compressed cork statured with water, and Polytek™-styrofoam combination to have approximate T1 and T2 values suitable for lung-equivalent materials.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Novel laser-processed CsI:Tl detector for SPECT

Purpose: The aim of this work is to demonstrate the feasibility of a novel technique for fabrication of high spatial resolution CsI:Tl scintillation detectors for single photon emission computed tomography systems. Methods: The scintillators are fabricated using laser-induced optical barriers technique to create optical microstructures (or optical barriers) inside the CsI:Tl crystal bulk. The laser-processed CsI:Tl crystals are 3, 5, and 10 mm in thickness. In this work, the authors focus on the simplest pattern of optical barriers in that the barriers are created in the crystal bulk to form pixel-like patterns resembling mechanically pixelated scintillators. The monolithic CsI:Tl scintillator samples are fabricated with optical barrier patterns with 1.0 × 1.0 mm{sup 2} and 0.625 × 0.625 mm{sup 2} pixels. Experiments were conducted to characterize the fabricated arrays in terms of pixel separation and energy resolution. A 4 × 4 array of multipixel photon counter was used to collect the scintillation light in all the experiments. Results: The process yield for fabricating the CsI:Tl arrays is 100% with processing time under 50 min. From the flood maps of the fabricated detectors exposed to 122 keV gammas, peak-to-valley (P/V) ratios of greater than 2.3 are calculated. The P/V values suggest that regardless of the crystal thickness, the pixels can be resolved. Conclusions: The results suggest that optical barriers can be considered as a robust alternative to mechanically pixelated arrays and can provide high spatial resolution while maintaining the sensitivity in a high-throughput and cost-effective manner.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

TxDOT Road Elevation Model Dataset

This dataset provides three formats of Road Elevation Model (REM) data: 3D road line/polygon GeoPackage (GPKG), road lidar LAZ and COPC LAZ, and road digital surface model (DSM) GeoTIFF. Data are produced from the ~50TB TxGIO (formerly TNRIS) state lidar collections. This dataset is currently organized by maintenance section in each TxDOT district. Computation is done on GPU computing resources at Oak Ridge National Laboratory (ORNL), through a Strategic Partnership Project with UT Austin and an NSF ACCESS computing allocation award that enables fast massive data movement between TACC Corral and ORNL CADES/OLCF using Globus. In addition to this release from ORNL, a copy of this dataset can also be downloaded at https://web.corral.tacc.utexas.edu/nfiedata/road3d/.

13 HYDRO ENERGY↗
DOE OSTI2017

Understanding Extreme Stochastic Events in EUV Resists

© 2017 SPST. The problem of stochastics in photoresist patterning is of significant concern in the commercialization of extreme ultraviolet lithography, especially in patterning of contacts or vias. Traditionally, contact hole critical dimension (CD) variability is characterized as a Gaussian process, however, recent experimental results have demonstrated significant deviations from Gaussian statistics, especially on the small CD side. Modeling results show that this non-Gaussian variation is expected and can be attributed to the non-linear behavior of the contact hole exposure latitude as a function of dose. It is shown that if we consider the noise in the dose or sensitivity domain, it can still be treated as a Gaussian process. The CD statistics are then determined by mapping the Gaussian dose/sensitivity noise through the non-linear and deterministic CD versus dose function.

36 MATERIALS SCIENCE↗
DOE OSTI2026

From microbial diversity to functional potential using dimensionality reduction

The high dimensionality of microbial diversity data from ‘omics observations can be reduced using Machine Learning, with many recent studies showcasing ML utility for exploratory ecological feature finding and process prediction. Here, we compare the Self Organizing Map (SOM) dimensionality reduction method to the well-documented sample-based Principal Coordinate Analysis (PCoA) and taxa-based Weighted Gene Correlation Network Analysis (WGCNA) using near daily 16S rRNA gene amplicon sequencing data from the 2019 to 2020 MOSAiC International Arctic Drift Expedition. We then map k-means clustering outputs from each method to available metagenomes, extracting functionally distinct seasonal microbial ecotypes in the surface Arctic Ocean. Our results indicate the SOM method better represented expected seasonal transitions and identified a greater number of metabolically distinct functional groups than the more traditional PCoA ordination. Ultimately, we identified four community ecotypes with distinct taxonomic and functional cut-offs driven by seasonality, water mass, and substrate turnover, highlighting the importance of succession in functional diversity for the central Arctic Ocean. These results reinforce ML dimensionality reduction as a meaningful translator in the mining of historical amplicon datasets to address modern mechanistic questions and potentially provide ’omics informed ecotype diversity to leverage in mechanistic biogeochemical models.

Arctic Ocean↗
DOE OSTI2016

Quantitative assessment of AOD from 17 CMIP5 models based on satellite-derived AOD over India

Aerosol optical depth (AOD) values from 17 CMIP5 models are compared with Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR) derived AODs over India. The objective is to identify the cases of successful AOD simulation by CMIP5 models, considering satellite-derived AOD as a benchmark. Six years of AOD data (2000–2005) from MISR and MODIS are processed to create quality-assured gridded AOD maps over India, which are compared with corresponding maps of 17 CMIP5 models at the same grid resolution. Intercomparison of model and satellite data shows that model-AOD is better correlated with MISR-derived AOD than MODIS. The correlation between model-AOD and MISR-AOD is used to segregate the models into three categories identifying their performance in simulating the AOD over India. Maps of correlation between model-AOD and MISR-/MODIS-AOD are generated to provide quantitative information about the intercomparison. The two sets of data are examined for different seasons and years to examine the seasonal and interannual variation in the correlation coefficients. In conclusion, latitudinal and longitudinal variations in AOD as simulated by models are also examined and compared with corresponding variations observed by satellites.

(aerosols and particles)↗
DOE OSTI2026

Impact of front-end parameters of the ARCADIA MD3 on charged particle detection

The ARCADIA INFN R&D project developed a Fully Depleted Monolithic Active Pixel Sensor (FD-MAPS) using a customized LFoundry 110 nm CIS process. The first in-beam characterization of the ARCADIA Main Demonstrator 3 (MD3) sensor with 200 $μ$m active thickness has been performed at the Fermilab Test Beam Facility with a 120 GeV proton beam. The Device Under Test (DUT) is tested with a trigger-less telescope composed of two ARCADIA MD3 tracking planes. This early study investigates the effect of the front-end parameters on the tracking performance.

Pantouvakis, C. [Padua U.; INFN, Padua]↗
DOE OSTI2020

Scanning Probe Microscope to Map Thermal and Thermoelectric Properties of Combinatorial Materials

The combinatorial methodology offers a high-throughput process for developing radiation-resistant sensor materials for nuclear energy applications through the synthesis and screening of large numbers of compositions and processing conditions in a single process. The combinatorial materials fabrication coupled with an automated screening process enables us to identify the optimal materials composition and processing conditions that yield both desired properties and required irradiation resistance in the most efficient and economic manner. The report focuses on the development of scanning probe technique to map with high resolution the thermal conductivity, Seebeck coefficient and electrical conductivity of combinatory materials with gradient compositions, which has been a key challenge in combinatory materials science. The above three properties play important roles in many sensor materials for nuclear energy applications.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Probing lithiation and delithiation of thick sintered lithium-ion battery electrodes with neutron imaging

As lithium-on (Li-ion) batteries increase in their prevalence and the range of applications expands, there is a need to understand and exploit the limits of electrochemical performance. Probing the internal processes in Li-ion batteries provides insights into the electrochemical characteristics of the cells as well as information necessary for rational cell design. In this manuscript an in situ method, neutron imaging, is applied to Li-ion full cells to track the lithiation/delithiation processes in the electrodes during discharge. The electrodes comprise thick sintered films of only active material, which improves the number of discrete points that are mapped for net changes in neutron intensity through the electrode. The lithiation/delithiation processes are qualitatively consistent with calculations of the Li + concentration and discharge profiles of the cells. These results illustrate that neutron imaging can experimentally probe and confirm limitations in the electrochemical performance of Li-ion full cells, particularly those with thick electrodes.

25 ENERGY STORAGE↗
DOE OSTI2016

Utilization of Tabula Rasa to Stabilize Bulk Lifetimes in n-Cz Silicon for High-Performance Solar Cell Processing

We investigate a high temperature, high cooling-rate anneal Tabula Rasa (TR) and report its implications on n-type Czochralski-grown silicon (n-Cz Si) for photovoltaic fabrication. Tabula Rasa aims at dissolving and homogenizing oxygen precipitate nuclei that can grow during the cell process steps and degrade the cell performance due to their high internal gettering and recombination activity. The Tabula Rasa thermal treatment is performed in a clean tube furnace with cooling rates >100 degrees C/s. We characterize the bulk lifetime by Sinton lifetime and photoluminescence mapping just after Tabula Rasa, and after the subsequent cell processing. After TR, the bulk lifetime surprisingly degrades to <; 0.1ms, only to recover to values equal or higher than the initial non-treated wafer (several ms), after typical high temperature cell process steps. Those include boron diffusion and oxidation; phosphorus diffusion/oxidation; ambient annealing at 850 degrees C; and crystallization annealing of tunneling-passivating contacts (doped polycrystalline silicon on 1.5 nm thermal oxide). The drastic lifetime improvement during high temperature cell processing is attributed to improved external gettering of metal impurities and annealing of intrinsic point defects. Time and injection dependent lifetime spectroscopy further reveals the mechanisms of lifetime improvement after Tabula Rasa treatment. Additionally, we report the efficacy of Tabula Rasa on n-type Cz-Si wafers and its dependence on oxygen concentration, correlated to position within the ingot.

14 SOLAR ENERGY↗
DOE OSTI2024

2-D soil zymography: Accounting for the spatial variation of pH

Soil zymography is commonly used to quantify spatial distribution of hydrolytic enzyme activities on soil and plant root surfaces. It is recommended to adjust pH in zymography substrates and calibration solutions with respect to soil/root pH. However, pH values may vary greatly within a few mm of plant rhizosphere, potentially altering the distribution of pH in zymography membranes. Despite the fact that the effect of pH on the calibration of zymography membranes is generally known, its potential impact on zymography results is unaccounted for in processing zymography images and calculations of enzyme activity. In this study we assessed the effect of pH variations on the persistency of the methylumbelliferone (MUF) calibration. The studied pH values ranged from 4.5 to 7.5. The MUF calibration curves greatly deviated from that at a reference pH of 6.5, with a marked nonlinear increase of deviation with greater membrane brightness. We suggest that the problem can be partially alleviated by reducing the membrane incubation time. However, such deviations suggest the need for a more comprehensive resolution via mapping pH and using pH-specific calibrations to process zymography images. Here, we developed a MATLAB code to implement a pixel-based correction of enzyme activity for pH in processing time-lapse zymography images.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Sparse Bayesian mass mapping with uncertainties: hypothesis testing of structure

ABSTRACT A crucial aspect of mass mapping, via weak lensing, is quantification of the uncertainty introduced during the reconstruction process. Properly accounting for these errors has been largely ignored to date. We present a new method to reconstruct maximum a posteriori (MAP) convergence maps by formulating an unconstrained Bayesian inference problem with Laplace-type l1-norm sparsity-promoting priors, which we solve via convex optimization. Approaching mass mapping in this manner allows us to exploit recent developments in probability concentration theory to infer theoretically conservative uncertainties for our MAP reconstructions, without relying on assumptions of Gaussianity. For the first time, these methods allow us to perform hypothesis testing of structure, from which it is possible to distinguish between physical objects and artefacts of the reconstruction. Here, we present this new formalism, and demonstrate the method on simulations, before applying the developed formalism to two observational data sets of the Abell 520 cluster. Initial reconstructions of the Abell 520 catalogues reported the detection of an anomalous ‘dark core’ – an overdense region with no optical counterpart – which was taken to be evidence for self-interacting dark matter. In our Bayesian framework, it is found that neither Abell 520 data set can conclusively determine the physicality of such dark cores at $99{{\ \rm per\ cent}}$ confidence. However, in both cases the recovered MAP estimators are consistent with both sets of data.

Price, M. A.↗
DOE OSTI2016

SU-G-IeP1-12: Size Selective Arterial Cerebral Blood Volume Mapping Using Multiple Inversion Time Arterial Spin Labeling

Purpose: To demonstrate the feasibility of a novel method for size specific arterial cerebral blood volume (aCBV) mapping using pseudo-continuous arterial spin labeling (PCASL), with multiple TI. Methods: Multiple PCASL images were obtained from a subject with TI of [300, 400, 500, 600, 700, 800, 900, 1000, 1500, 2000, 2500, 3000, 3500, 4000] ms. Each TI pair was averaged six times. Two scans were performed: one without a flow crusher gradient and the other with a crusher gradient (10cm/s in three directions) to remove signals from large arteries. Scan times were 5min. without a crusher gradient and 5.5 min with a crusher gradient. Non-linear fitting algorithm finds the minimum mean squared solution of per-voxel based aCBV, cerebral blood flow, and arterial transit time, and fits the data into a hemodynamic model that represents superposition of blood volume and flow components within a single voxel. Results: aCBV maps with a crusher gradient represent signals from medium and small sized arteries, while those without a crusher gradient represent signals from all sized arteries, indicating that flow crusher gradients can be effectively employed to achieve size-specific aCBV mapping. Regardless of flow crusher, the CBF and ATT maps are very similar in appearance. Conclusion: Quantitative size selective blood volume mapping controlled by a flow crusher is feasible without additional information because the ASL quantification process doesn’t require an arterial input function measured from a large artery. The size specific blood volume mapping is not interfered by sSignals from large arteries do not interfere with size specific aCBV mapping in the applications of interest in for applications in which only medium or small arteries are of interest.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Electrical Resistivity Changes During Heating Experiments Unravel Heterogeneous Thermal‐Hydrological‐Mechanical Processes in Salt Formations

Abstract Rock salt is considered a suitable medium for the permanent disposal of heat‐generating radioactive waste due to its isolation properties. However, excavation damage and heating induce complex and heterogeneous thermal‐hydrological‐mechanical (THM) processes across different zones. Quantifying this heterogeneity is crucial for accurate long‐term performance assessment models, but traditional methods lack the necessary resolution. This study employs 4D electrical resistivity tomography (ERT) monitoring during controlled heating experiments in a salt formation to unravel the spatiotemporal dynamics of THM processes. Advanced time‐lapse inversion and clustering analysis quantify subsurface properties and map the heterogeneity of THM dynamics. The ERT results can estimate subsurface properties and delineate the damaged and intact zones, enabling appropriate parameterization and representation of processes for long‐term modeling. This approach may be used in further improving the predictive models and ensuring the safe long‐term disposal of radioactive waste in rock salt.

58 GEOSCIENCES↗
DOE OSTI2022

Connecting Matrix Elements to Multi-Hadron Form-Factors

We discuss developments in calculating multi-hadron form-factors and transition processes via lattice QCD. Our primary tools are finite-volume scaling relations, which map spectra and matrix elements to the corresponding multi-hadron infinite-volume amplitudes. We focus on two hadron processes probed by an external current, and provide various checks on the finite-volume formalism in the limiting cases of perturbative interactions and systems forming a bound state. By studying model-independent properties of the infinite-volume amplitudes, we are able to rigorously define form-factors of resonances.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗