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Results for “quantum image processing”

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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

On the turbulent flow in piston engines: Coupling of statistical theory quantities and instantaneous turbulence

Planar particle image velocimetry (PIV) and tomographic PIV (TPIV) measurements are utilized to analyze turbulent statistical theory quantities and the instantaneous turbulence within a single-cylinder optical engine. Measurements are performed during the intake and mid-compression stroke at 800 and 1500 RPM. TPIV facilitates the evaluation of spatially resolved Reynolds stress tensor (RST) distributions, anisotropic Reynolds stress invariants, and instantaneous turbulent vortical structures. The RST analysis describes distributions of individual velocity fluctuation components that arise from unsteady turbulent flow behavior as well as cycle-to-cycle variability (CCV). A conditional analysis, for which instantaneous PIV images are sampled by their tumble center location, reveals that CCV and turbulence have similar contributions to RST distributions at the mean tumble center, but turbulence is dominant in regions peripheral to the tumble center. Analysis of the anisotropic Reynolds stress invariants reveals the spatial distribution of axisymmetric expansion, axisymmetric contraction, and 3D isotropy within the cylinder. Findings indicate that the mid-compression flow exhibits a higher tendency toward 3D isotropy than the intake flow. A novel post-processing algorithm is utilized to classify the geometry of instantaneous turbulent vortical structures and evaluate their frequency of occurrence within the cylinder. Findings are coupled with statistical theory quantities to provide a comprehensive understanding of the distribution of turbulent velocity components, the distribution of anisotropic states of turbulence, and compare the turbulent vortical flow distribution that is theoretically expected to what is experimentally observed. The analyses reveal requisites of important turbulent flow quantities and discern their sensitivity to the local flow topography and engine operation.

42 ENGINEERING↗
DOE OSTI2015

Phase-selective vanadium dioxide (VO{sub 2}) nanostructured thin films by pulsed laser deposition

Thin films of monoclinic nanostructured vanadium dioxide are notoriously difficult to produce in a selective manner. To date, post-annealing, after pulsed laser deposition (PLD), has been used to revert the crystal phase or to remove impurities, and non-glass substrates have been employed, thus reducing the efficacy of the transparency switching. Here, we overcome these limitations in PLD by optimizing a laser-ablation and deposition process through optical imaging of the laser-induced plasma. We report high quality monoclinic rutile-type vanadium dioxide (VO{sub 2}) (M1) nanoparticles without post-annealing, and on a glass substrate. Our samples demonstrate a reversible metal-to-insulator transition at ∼43 °C, without any doping, paving the way to switchable transparency in optical materials at room temperature.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Characterizing Dynamic Structure in Battery Electrodes by Time-Resolved Cryo-TEM

In recent years, cryogenic transmission electron microscopy (cryo-TEM) has enabled high-resolution characterization of sensitive battery materials by minimizing electron beam-induced artifacts and damage. Success of this technique relies on the preparation of thin, rapidly frozen samples, generally by disassembling batteries under inert atmosphere, transferring materials of interest to a TEM grid, and finally plunge freezing into a cryogen. In material degradation studies, this extensive time between electrochemical cycling and cryo-TEM characterization leaves room for structural relaxation, diffusion, and other dynamic processes that make it difficult to precisely correlate the imaged structure with the native structure that evolves during battery cycling or aging. Here, we present a method to integrate battery cycling with fast preparation of electrode samples for cryo-TEM. This enables higher fidelity between the structures characterized and the electrochemical state of interest, which we use to study deformation in silicon nanoparticle anodes for lithium-ion batteries.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS↗
DOE OSTI2016

Magnetization reversal of the domain structure in the anti-perovskite nitride Co{sub 3}FeN investigated by high-resolution X-ray microscopy

We performed X-ray magnetic circular dichroism (XMCD) photoemission electron microscopy imaging to reveal the magnetic domain structure of anti-perovskite nitride Co{sub 3}FeN exhibiting a negative spin polarization. In square and disc patterns, we systematically and quantitatively determined the statistics of the stable states as a function of geometry. By direct imaging during the application of a magnetic field, we revealed the magnetic reversal process in a spatially resolved manner. We compared the hysteresis on the continuous area and the square patterns from the magnetic field-dependent XMCD ratio, which can be explained as resulting from the effect of the shape anisotropy, present in nanostructured thin films.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

State-to-State Molecular Reactions in the Ultracold Regime (Final Scientific Report)

We have achieved the proposed goal to experimentally probe the AB + CD and AB + C types of reactions with state-to-state resolution, which we also compared to advanced theoretical calculations to help elucidate the role of quantum mechanics in the processes of bond breakage and formation. Our approach uses reactants that are prepared at ultracold temperatures (< 1µK) such that the quantum effects of translational motion are an important factor. Specific example reactions, including the potassium-rubidium metathesis reaction KRb + KRb → K 2 + Rb 2 as well as the atom exchange reaction Rb + KRb → Rb2 + K, are chosen because the technology of quantum internal and motional state control of these types of molecules is particularly advanced. The results for the entire funding period are fruitful. For the majority of this grant, we have constructed a one-of-the-kind quantum degenerate gas apparatus that integrates ion detection and velocity map imaging capabilities, allowing us to explore the KRb + KRb → K 2 + Rb 2 bimolecular reaction in detail. Specifically, we first verified such a reaction indeed proceed at ultracold temperatures by direct detection of reaction products. We then mapped out the complete product state distribution, which was compared to a state-counting model based on statistical theory. Our results show an overall agreement with the statistical state counting model, but also reveal several deviating state-pairs. An exact quantum calculation for molecule-molecule collisions, that is needed to understand these deviations, is however beyond the current state-of-the-art. Beside scrutinizing the reaction products, we also directly observe the reaction intermediate complex, which was quite a surprise to us. The intermediate complexes are long-lived and can interact with the inferred light that we use to trap the ultracold gas. After molecule-molecule collisions, we then explored the more theoretically tractable Rb + KRb reaction, which is endothermic. Surprisingly, we observed an exceedingly long-lived KRb$^*_2$ collisional complexes, with our experimentally measured complex lifetime deviating from conventional theoretical calculations by five orders of magnitude. This discrepancy has motivated many explorations of possible underlying causes, though no model yet captures this phenomenon completely. In the final year and the work that continues today, we extend upon these atom-molecule collision experiments to explore the origin of the long-lived KRb$^*_2$ complex lifetime and develop means to control the outcome of the reaction complex. The 5-year funded work advanced our understanding of chemical reactions at the lowest possible temperatures and at the same time opened up many new questions that are beyond our initial imaginations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Microfluidic electrochemical device and process for chemical imaging and electrochemical analysis at the electrode-liquid interface in-situ

A microfluidic electrochemical device and process are detailed that provide chemical imaging and electrochemical analysis under vacuum at the surface of the electrode-sample or electrode-liquid interface in-situ. The electrochemical device allows investigation of various surface layers including diffuse layers at selected depths populated with, e.g., adsorbed molecules in which chemical transformation in electrolyte solutions occurs.

42 ENGINEERING↗
DOE OSTI2016

Insights on finite size effects in ab initio study of CO adsorption and dissociation on Fe 110 surface

Adsorption and dissociation of hydrocarbons on metallic surfaces represent crucial steps on the path to carburization, eventually leading to dusting corrosion. While adsorption of CO molecules on Fe surface is a barrier-less exothermic process, this is not the case for the dissociation of CO into C and O adatoms and the diffusion of C beneath the surface that are found to be associated with large energy barriers. In practice, these barriers can be affected by numerous factors that combine to favour the CO-Fe reaction such as the abundance of CO and other hydrocarbons as well as the presence of structural defects. From a numerical point of view, studying these factors is challenging and a step-by-step approach is necessary to assess, in particular, the influence of the finite box size on the reaction parameters for adsorption and dissociation of CO on metal surfaces. Here, we use density functional theory (DFT) total energy calculations with the climbing-image nudged elastic band method to estimate the adsorption energies and dissociation barriers for different CO coverages with surface supercells of different sizes. We further compute the effect of periodic boundary condition for DFT calculations and find that the contribution from van der Waals interaction in the computation of adsorption parameters is important as they contribute to correcting the finite-size error in small systems. The dissociation process involves carbon insertion into the Fe surface causing a lattice deformation that requires a larger surface system for unrestricted relaxation. We show that, in the larger surface systems associated with dilute CO-coverages, C-insertion is energetically more favourable, leading to a significant decrease in the dissociation barrier. This observation suggests that a large surface system with dilute coverage is necessary for all similar metal-hydrocarbon reactions in order to study their fundamental electronic mechanisms, as an isolated phenomenon, free from finite-size effects.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Theoretical scheme of thermal-light many-ghost imaging by Nth-order intensity correlation

In this paper, we propose a theoretical scheme of many-ghost imaging in terms of Nth-order correlated thermal light. We obtain the Gaussian thin lens equations in the many-ghost imaging protocol. We show that it is possible to produce N-1 ghost images of an object at different places in a nonlocal fashion by means of a higher order correlated imaging process with an Nth-order correlated thermal source and correlation measurements. We investigate the visibility of the ghost images in the scheme and obtain the upper bounds of the visibility for the Nth-order correlated thermal-light ghost imaging. It is found that the visibility of the ghost images can be dramatically enhanced when the order of correlation becomes larger. It is pointed out that the many-ghost imaging phenomenon is an observable physical effect induced by higher order coherence or higher order correlations of optical fields.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Randomized Algorithms for Scientific Computing (RASC)

Randomized algorithms have propelled advances in artificial intelligence (AI) and represent a foundational research area in advancing AI for Science. Future advancements in DOE Office of Science priority areas such as climate science, astrophysics, fusion, advanced materials, combustion, and quantum computing all require randomized algorithms for surmounting challenges of complexity, robustness, and scalability. Advances in data collection and numerical simulation have changed the dynamics of scientific research and motivate the need for randomized algorithms. For instance, advances in imaging technologies such as X-ray ptychography, electron microscopy, electron energy loss spectroscopy, or adaptive optics lattice light-sheet microscopy collect hyperspectral imaging and scattering data in terabytes, at breakneck speed enabled by state-of-the-art detectors. The data collection is exceptionally fast compared with its analysis. Likewise, advances in high-performance architectures have made exascale computing a reality and changed the economies of scientific computing in the process. Floating-point operations that create data are essentially free in comparison with data movement. Thus far, most approaches have focused on creating faster hardware. Ironically, this faster hardware has exacerbated the problem by making data still easier to create. Under such an onslaught, scientists often resort to heuristic deterministic sampling schemes (e.g., low-precision arithmetic, sampling every nth element) and sacrifice potentially valuable accuracy. Dramatically better results can be achieved via randomized algorithms, reducing the data size as much as or more than naive deterministic subsampling can achieve, while retaining the high accuracy of computing on the full data set. By randomized algorithms we mean those algorithms that employ some form of randomness in internal algorithmic decisions to accelerate time to solution, increase scalability, or improve reliability. Examples include matrix sketching for solving large-scale least-squares problems (see Figure 1) and stochastic gradient descent for training machine learning models. We are not recommending heuristic methods but rather randomized algorithms that have certificates of correctness and probabilistic guarantees of optimality and near-optimality. Such approaches can be useful beyond acceleration, for example, in understanding how to avoid measure zero worst-case scenarios that plague methods such as QR matrix factorization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Surface Chemistry and Reactions for Bimetallic Au Catalysis (Final Report)

Gold-based catalysts offer tremendous opportunities for developing new technologies for selective oxidation reactions that directly use gas-phase oxygen as a benign reagent and produce either no byproducts or water as the only byproduct. These processes are urgently needed and critical for achieving the sustainable production of chemicals. While recent studies demonstrate that the catalytic properties of gold can be significantly enhanced by addition of other metals, the development of these catalysts with sufficient performance for commercialization is hindered by a lack of fundamental understanding of how the catalytic properties of gold can be controlled and tailored. This project addressed this need by synergistically combining experimental and computational studies to establish fundamental composition-structure-activity relationships for gold-based catalysts for several industrially important reactions. Results from surface spectroscopy, atomic imaging and thermal desorption experiments were combined with molecular models and reaction mechanisms from quantum chemical calculations to link observable reaction rates to the structure and composition of surfaces at the molecular level. The results were used to develop improved catalyst formulations and identify optimized reaction conditions for gold-based catalysts. For broader impacts, the developed methodology was extended to other metallic catalysts, such as silver, platinum-molybdenum and nickel-tin, for improved catalytic efficiency and sustainable production of specialty and commodity chemicals.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Postprocessing Algorithm for Driving Conventional Scanning Tunneling Microscope at Fast Scan Rates

We present an image postprocessing framework for Scanning Tunneling Microscope (STM) to reduce the strong spurious oscillations and scan line noise at fast scan rates and preserve the features, allowing an order of magnitude increase in the scan rate without upgrading the hardware. The proposed method consists of two steps for large scale images and four steps for atomic scale images. For large scale images, we first apply for each line an image registration method to align the forward and backward scans of the same line. In the second step we apply a “rubber band” model which is solved by a novel Constrained Adaptive and Iterative Filtering Algorithm (CIAFA). The numerical results on measurement from copper(111) surface indicate the processed images are comparable in accuracy to data obtained with a slow scan rate, but are free of the scan drift error commonly seen in slow scan data. For atomic scale images, an additional first step to remove line-by-line strong background fluctuations and a fourth step of replacing the postprocessed image by its ranking map as the final atomic resolution image are required. The resulting image restores the lattice image that is nearly undetectable in the original fast scan data.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Portraying double Higgs at the Large Hadron Collider

We examine the discovery potential for double Higgs production at the high luminosity LHC in the final state with two b-tagged jets, two leptons and missing transverse momentum. Although this dilepton final state has been considered a difficult channel due to the large backgrounds, we argue that it is possible to obtain sizable signal significance, by adopting a deep learning framework making full use of the relevant kinematics along with the jet images from the Higgs decay. For the relevant number of signal events we obtain a substantial increase in signal sensitivity over existing analyses. We discuss relative improvements at each stage and the correlations among the different input variables for the neutral network. The proposed method can be easily generalized to the semi-leptonic channel of double Higgs production, as well as to other processes with similar final states.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Continuous injection synthesis of indium arsenide quantum dots emissive in the short-wavelength infrared

With the emergence of applications based on short-wavelength infrared light, indium arsenide quantum dots are promising candidates to address existing shortcomings of other infrared-emissive nanomaterials. However, III–V quantum dots have historically struggled to match the high-quality optical properties of II–VI quantum dots. Here we present an extensive investigation of the kinetics that govern indium arsenide nanocrystal growth. Based on these insights, we design a synthesis of large indium arsenide quantum dots with narrow emission linewidths. We further synthesize indium arsenide-based core-shell-shell nanocrystals with quantum yields up to 82% and improved photo- and long-term storage stability. We then demonstrate non-invasive through-skull fluorescence imaging of the brain vasculature of murine models, and show that our probes exhibit 2–3 orders of magnitude higher quantum yields than commonly employed infrared emitters across the entire infrared camera sensitivity range. Finally, we anticipate that these probes will not only enable new biomedical imaging applications, but also improved infrared nanocrystal-LEDs and photon-upconversion technology.

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

Imaging conical intersection dynamics during azobenzene photoisomerization by ultrafast X-ray diffraction

Significance Vibronic coherences are unique features that emerge in the decisive moments of photochemistry and photophysics. Here we demonstrate how X-ray diffraction can access fundamental information about these coherences. This is enabled by recent developments at free-electron lasers, working toward temporal resolution and single-molecule accessibility of scattering-based measurements. Time-resolved diffraction patterns of the isomerization of azobenzene are simulated. The process is monitored in time via the momentum-space signal, with a special focus on the mixed elastic/inelastic scattering from coherences. We give practical ideas on how this relatively weak contribution to the signal can potentially be retrieved. A direct connection to the real-space movie of the conical intersection dynamics is made, enabling the observation of quantum coherences that direct chemical processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Unsupervised classification-based hyperspectral data processing: lossy compression

The existing lossy compression algorithms play an important role in reducing the cost of storage equipment and bandwidth for hyperspectral (HS) application. However, none of the lossy compression algorithms considers the real-time classification of HS data. In this paper, we present a new lossy compression method for HS data that aims to optimally compress in both spatial and spectral domains and simultaneously maximize classification performance. For this target, Harsanyi–Farrand–Chang (HFC) and k-means++ algorithms are applied to achieve a spectral library and an index matrix for HS image. Spectral angle mapping and Euclidean distance are used to update the spectral library and the index matrix. The experiment results indicate that the proposed method has a good classification performance. The results also reveal that the proposed method works well in real-time classification and compression of HS data with a large volume and achieves a high compression ratio. It is noteworthy to mention that the superiority of our method in compression becomes more apparent as the volume of HS data grows. Consequently, the proposed method has a strong advantage in HS applications that require both compression and classification.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Automated analysis of hot spot X-ray images at the National Ignition Facility

At the National Ignition Facility, the symmetry of the hot spot of imploding capsules is diagnosed by imaging the emitted x-rays using gated cameras and image plates. The symmetry of an implosion is an important factor in the yield generated from the resulting fusion process. The x-ray images are analyzed by decomposing the image intensity contours into Fourier and Legendre modes. This paper focuses on the additional protocols for the time-integrated shape analysis from image plates. For implosions with temperatures above ∼4 keV, the hard x-ray background can be utilized to infer the temperature of the hot spot.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Observation of room temperature optical absorption in InP/GaAs type-II ultrathin quantum wells and quantum dots

Room temperature optical absorption process is observed in ultrathin quantum wells (QWs) and quantum dots (QDs) of InP/GaAs type-II band alignment system using surface photovoltage spectroscopy technique, where no measurable photoluminescence signal is available. Clear signature of absorption edge in the sub band gap region of GaAs barrier layer is observed for the ultrathin QWs and QDs, which red shifts with the amount of deposited InP material. Movement of photogenerated holes towards the sample surface is proposed to be the main mechanism for the generation of surface photovoltage in type-II ultrathin QWs and QDs. QDs of smaller size are found to be free from the dislocations as confirmed by the high resolution transmission electron microscopy images.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Revealing Possible Coherence Limiting Sources in Superconducting Qubit with Advanced Electron Microscopy

Superconducting materials hold great potential for solid-state quantum computing. Their fabrication relies on established semiconductor fabrication techniques, such as thin film deposition and lithography, but the complex processing steps can result in defects at the qubits' interfaces and surfaces that can negatively impact coherence time. To improve superconducting qubit performance, it is essential to understand the structural features, at the atomic scale, that may act as sources of decoherence limiting factor in both the Josephson junction (JJ) and resonators, which are key components of superconducting qubit. This talk will present our recent studies on the microstructures in a 2D-transmon, with an emphasis on the JJ. For this research, a combination of advanced microscopy techniques, including high-resolution (S)TEM imaging, and spectroscopy (EDS and EELS) are used to identify possible coherence-limiting defects or structural features.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗