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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 163 records · Page 9

Insights into the Cathode–Electrolyte Interphases of High-Energy-Density Cathodes in Lithium-Ion Batteries

Here we present a comprehensive study of cycled high-Ni (LiNi 1–x M x O 2 , M = metals), Li-rich (Li 1+x Mn y M 1–x–y O 2 ), and high-voltage spinel (LiMn 1.5 Ni 0.5 O 4 ) electrodes with time-of-flight secondary ion mass spectrometry (TOF-SIMS) and X-ray photoelectron spectroscopy in conjunction with electrochemical techniques to better understand their evolving cathode–electrolyte interphase structure during cycling. TOF-SIMS provides fragment-specific information regarding the surface film content for each of the electrodes. High-Ni cathodes show thick surface films initially containing Li 2 CO 3 , later developing oxidized organic carbonates throughout cycling. Li-rich electrode surface films develop strong characteristics during their first activation cycles, where released O 2 oxidizes organic carbonates to form polymeric carbons and decomposes LiPF 6 . High-voltage spinel electrodes operate outside the standard electrolyte stability window, generating reactive oxidized electrolyte species that further decompose LiPF 6 . The distribution and concentration of these different chemical fragments measured by TOF-SIMS are finally summarized by color-coded high-resolution images of cycled high-Ni, Li-rich, and high-voltage spinel electrodes.

25 ENERGY STORAGE↗

Advances in imaging of chemically reacting flows

Many important chemically reacting systems are inherently multi-dimensional with spatial and temporal variations in the thermochemical state, which can be strongly coupled to interactions with transport processes. Fundamental insights into these systems require multi-dimensional measurements of the thermochemical state as well as fluid dynamics quantities. Laser-based imaging diagnostics provide spatially and temporally resolved measurements that help address this need. The state of the art in imaging diagnostics is continually progressing with the goal of attaining simultaneous multi-parameter measurements that capture transient processes, particularly those that lead to stochastic events, such as localized extinction in turbulent combustion. Development efforts in imaging diagnostics benefit from advances in laser and detector technology. This article provides a perspective on the progression of increasing dimensionality of laser-based imaging diagnostics and highlights the evolution from single-point measurements to 1D and 2D multi-parameter imaging and 3D high-speed imaging. This evolution is demonstrated using highlights of laser-based imaging techniques in combustion science research as an exemplar of a complex multi-dimensional chemically reacting system with chemistry–transport coupling. Imaging diagnostics impact basic research in other chemically reacting systems as well, such as measurements of near-surface gases in heterogeneous catalysis. The expanding dimensionality of imaging diagnostics leads to larger and more complex datasets that require increasingly demanding approaches to data analysis and provide opportunities for increased collaboration between experimental and computational researchers in tackling these challenges.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-resolution high-throughput spatiotemporal strain imaging reveals loss mechanisms in a surface acoustic wave device

Surface acoustic wave devices are key components for processing radio frequency signals in wireless communication because these devices offer simultaneously high performance, compact size and low cost. The optimization of the device structure requires a quantitative understanding of energy conversion and loss mechanisms. Here we use stroboscopic full-field diffraction x-ray microscopy to reveal an unanticipated acoustic loss in a prototypical one-port resonator device. A non-uniform acoustic excitation in the active area was responsible for the substantial end and side leakages observed at the design frequency. Quantitative analysis of the strain amplitude using a wave decomposition method allowed the determination of several key device parameters. This high-resolution high-throughput spatiotemporal strain imaging technique is more generally applicable to the study of dynamic strain modulation in nanoscale acoustic, electronic, optical and quantum devices. The high sensitivity allows precise measurement of the strain modulation with picometer-scale amplitude.

Zhou, Tao [ESRF - The European Synchrotron, Grenob↗

High spatial resolution neutron imaging of lithium-ion batteries: Correlating microstructure and lithium transport

Thick electrodes for lithium-ion batteries can increase the overall energy density, but increasing the electrode thickness introduces charge transport limitations. These limitations may be mitigated through proper electrode structuring. Here, high spatial resolution neutron imaging was used to understand the correlation between microstructure and lithium transport in lithium-ion anodes. Batteries with distinct graphite anode microstructures were produced and studied with high spatial resolution in operando neutron radiography to observe the effects of structure on transport. High spatial resolution neutron computed tomography was performed following in operando neutron radiography. X-ray computed tomography and scanning electron microscopy were used to observe the finer scale anode structure to complement neutron imaging. Solvent-free anodes containing a tightly-packed layered structure confined lithium movement close to the separator. This structure limited capacity, but supported better rate capability. Conversely, a more open pore structure in the wet cast anodes yielded higher capacity with reduced rate capability. Together, these results show that lithium distributions can be controlled by the macroscopic structure of the electrodes, the microstructural pore network, and the microscale active areas that support electrochemical reactions. Furthermore, multimodal imaging applying the complementary strengths of neutron and X-ray methods is shown as a tool for advancing battery design.

25 ENERGY STORAGE↗

An Internal Digital Image Correlation Technique for High-Strain Rate Dynamic Experiments

Full-field, quantitative visualization techniques, such as digital image correlation (DIC), have unlocked vast opportunities for experimental mechanics. However, DIC has traditionally been a surface measurement technique, and has not been extended to perform measurements on the interior of specimens for dynamic, full-scale laboratory experiments. This limitation restricts the scope of physics which can be investigated through DIC measurements, especially in the context of heterogeneous materials. The focus of this study is to develop a method for performing internal DIC measurements in dynamic experiments. The aim is to demonstrate its feasibility and accuracy across a range of stresses (up to 650 MPa), strain rates (10 3 - 10 6 s -1 ), and high-strain rate loading conditions (e.g., ramped and shock wave loading). Internal DIC is developed based on the concept of applying a speckle pattern at an inner-plane of a transparent specimen. The high-speed imaging configuration is coupled to the traditional dynamic experimental setups, and is focused on the internal speckle pattern. During the experiment, while the sample deforms dynamically, in-plane, two-dimensional deformations are measured via correlation of the internal speckle pattern. In this study, the viability and accuracy of the internal DIC technique is demonstrated for split-Hopkinson (Kolsky) pressure bar (SHPB) and plate impact experiments. The internal DIC experimental technique is successfully demonstrated in both the SHPB and plate impact experiments. In the SHPB setting, the accuracy of the technique is excellent throughout the deformation regime, with measurement noise of approximately 0.2% strain. In the case of plate impact experiments, the technique performs well, with error and measurement noise of 1% strain. The internal DIC technique has been developed and demonstrated to work well for full-scale dynamic high-strain rate and shock laboratory experiments, and the accuracy is quantified. Here, the technique can aid in investigating the physics and mechanics of the dynamic behavior of materials, including local deformation fields around dynamically loaded material heterogeneities.

36 MATERIALS SCIENCE↗

Preliminary Design Needs for High-Temperature Heat Pipe Imaging System

This report provides preliminary design needs for radiological imaging heat pipes to perform in operando assessment for high-temperature alkaline metal charged heat pipes (HPs). The measurement parameters of interest have been summarized for characterizing the operando HP behavior. Based on the current SPHERE experimental facility, the needs and modifications required for the experimental setup have also been identified to enable the X-ray-assisted visualizations for the single HP during its operating conditions.

42 ENGINEERING↗

Neutrino interaction vertex reconstruction in DUNE with Pandora deep learning

The Pandora Software Development Kit and algorithm libraries perform reconstruction of neutrino interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at the Deep Underground Neutrino Experiment, which will operate four large-scale liquid argon time projection chambers at the far detector site in South Dakota, producing high-resolution images of charged particles emerging from neutrino interactions. While these high-resolution images provide excellent opportunities for physics, the complex topologies require sophisticated pattern recognition capabilities to interpret signals from the detectors as physically meaningful objects that form the inputs to physics analyses. A critical component is the identification of the neutrino interaction vertex. Subsequent reconstruction algorithms use this location to identify the individual primary particles and ensure they each result in a separate reconstructed particle. A new vertex-finding procedure described in this article integrates a U-ResNet neural network performing hit-level classification into the multi-algorithm approach used by Pandora to identify the neutrino interaction vertex. The machine learning solution is seamlessly integrated into a chain of pattern-recognition algorithms. The technique substantially outperforms the previous BDT-based solution, with a more than 20% increase in the efficiency of sub-1 cm vertex reconstruction across all neutrino flavours.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A Joint Roman Space Telescope and Rubin Observatory Synthetic Wide-Field Imaging Survey

We present and validate 20 deg(2) of overlapping synthetic imaging surveys representing the full depth of the Nancy Grace Roman Space Telescope High-Latitude Imaging Survey (HLIS) and 5 yr of observations of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). The two synthetic surveys are summarized, with reference to the existing 300 deg(2) of LSST simulated imaging produced as part of Dark Energy Science Collaboration (DESC) Data Challenge 2 (DC2). Both synthetic surveys observe the same simulated DESC DC2 universe. For the synthetic Roman survey, we simulate for the first time fully chromatic images along with the detailed physics of the Sensor Chip Assemblies derived from lab measurements using the flight detectors. The simulated imaging and resulting pixel-level measurements of photometric properties of objects span a wavelength range of similar to 0.3-2.0 mu m. We also describe updates to the Roman simulation pipeline, changes in how astrophysical objects are simulated relative to the original DC2 simulations, and the resulting simulated Roman data products. We use these simulations to explore the relative fraction of unrecognized blends in LSST images, finding that 20-30 per cent of objects identified in LSST images with i-band magnitudes brighter than 25 can be identified as multiple objects in Roman images. These simulations provide a unique testing ground for the development and validation of joint pixel-level analysis techniques of ground- and space-based imaging data sets in the second half of the 2020s - in particular the case of joint Roman-LSST analyses.

gravitational lensing↗

High-resolution 3D microwave imaging using an optically tracked linear array

Active three-dimensional microwave or millimeter-wave imaging is typically performed using a linear array that is mechanically scanned over a uniform planar or cylindrical aperture. However, an image can also be formed with a linear array that is scanned over a non-uniform irregular aperture. This requires that the precise position of the array be known for each radar sample. This paper explores high-resolution 3D microwave imaging of stationary targets using an optically tracked manually scanned linear array. The image reconstruction techniques necessary to account for a non-uniform irregular aperture are also developed.

Clark, Richard T.↗

Effect of image resolution on automated classification of chest X-rays

Deep learning (DL) models have received much attention lately for their ability to achieve expert-level performance on the accurate automated analysis of chest X-rays (CXRs). Recently available public CXR datasets include high resolution images, but state-of-the-art models are trained on reduced size images due to limitations on graphics processing unit memory and training time. As computing hardware continues to advance, it has become feasible to train deep convolutional neural networks on high-resolution images without sacrificing detail by downscaling. This study examines the effect of increased resolution on CXR classification performance. We used the publicly available MIMIC-CXR-JPG dataset, comprising 377,110 high resolution CXR images for this study. We applied image downscaling from native resolution to 2048 × 2048 pixels, 1024 × 1024 pixels, 512 × 512 pixels, and 256 × 256 pixels and then we used the DenseNet121 and EfficientNet-B4 DL models to evaluate clinical task performance using these four downscaled image resolutions. We find that while some clinical findings are more reliably labeled using high resolutions, many other findings are actually labeled better using downscaled inputs. We qualitatively verify that tasks requiring a large receptive field are better suited to downscaled low resolution input images, by inspecting effective receptive fields and class activation maps of trained models. Lastly, we show that stacking an ensemble across resolutions outperforms each individual learner at all input resolutions while providing interpretable scale weights, indicating that diverse information is extracted across resolutions.

47 OTHER INSTRUMENTATION↗

Deep Learning with Reflection High-Energy Electron Diffraction Images to Predict Cation Ratio in Sr 2 x Ti 2(1– x ) O 3 Thin Films

Machine learning (ML) with in-situ diagnostics offers a transformative approach to accelerate, understand, and control thin film synthesis by uncovering relationships between synthesis conditions and material properties. In this study, we demonstrate the application of deep learning to predict the stoichiometry of Sr 2x Ti 2(1–x) O 3 thin films using reflection high-energy electron diffraction images acquired during pulsed laser deposition. A gated convolutional neural network trained for regression of the Sr atomic fraction achieved accurate predictions with a small dataset of 31 samples. Explainable AI techniques revealed a previously unknown correlation between diffraction streak features and cation stoichiometry in Sr 2x Ti 2(1–x) O 3 thin films. Here, our results demonstrate how ML can be used to transform a ubiquitous in-situ diagnostic tool, that is usually limited to qualitative assessments, into a quantitative surrogate measurement of continuously valued thin film properties. Such methods are critically needed to enable real-time control, autonomous workflows, and accelerate traditional synthesis approaches.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

High-magnification Faraday rotation imaging and analysis of X-pinch implosion dynamics

An X-pinch load driven by an intense current pulse (>100 kA in ~100 ns) can result in the formation of a small radius, runaway compressional micro-pinch. A micro-pinch is characterized by a hot (>1 keV), current-driven (>100 kA), high-density plasma column (near solid density) with a small neck diameter (1–10 µm), a short axial extent (<1 mm), and a short duration (≲1 ns). With material pressures often well into the multi-Mbar regime, a micro-pinch plasma often radiates an intense, sub-ns burst of sub-keV to multi-keV x rays. A low-density coronal plasma immediately surrounding the dense plasma neck could potentially shunt current away from the neck and thus reduce the magnetic drive pressure applied to the neck. Here, to study the current distribution in the coronal plasma, a Faraday rotation imaging diagnostic (1064 nm) capable of producing simultaneous high-magnification polarimetric and interferometric images has been developed for the MAIZE facility at the University of Michigan. Designed with a variable magnification (1–10×), this diagnostic achieves a spatial resolution of ~35 µm, which is useful for resolving the ~100-μm-scale coronal plasma immediately surrounding the dense core. This system has now been used on a reduced-output MAIZE (100–200 kA, 150 ns) to assess the radial distribution of drive current immediately surrounding the dense micro-pinch neck. The total current enclosed was found to increase as a function of radius, r, from a value of ≈ 50 ± 25 kA at r ≈ 140 µm (at the edge of the dense neck) to a maximal value of ≈150 ± 75 kA for r ≥ 225 µm. This corresponds to a peak magnetic drive pressure of ≈75 ± 50 kbar at r ≈ 225 µm. The limitations of these measurements are discussed in the paper.

47 OTHER INSTRUMENTATION↗

Use of Convolutional Neural Network Image Classification and High-Speed Ion Probe Data Toward Real-Time Detonation Characterization in a Water-Cooled Rotating Detonation Engine

As rotating detonation engines (RDEs) progress in maturity, the importance of monitoring advancements toward development of active control becomes more critical. Experimental RDE data processing at time scales which satisfy real-time diagnostics will likely require the use of machine learning. This study aims to develop and deploy a novel real-time monitoring technique capable of determining detonation wave number, direction, frequency, and individual wave speeds throughout experimental RDE operational windows. To do so, the diagnostic integrates image classification by a convolutional neural network (CNN) and ionization current signal analysis. Wave mode identification through single-image CNN classification bypasses the need to evaluate sequential images and offers instantaneous identification of the wave mode present in the RDE annulus. Here, real-time processing speeds are achieved due to low data volumes required by the methodology, namely one short-exposure image and a short window of sensor data to generate each diagnostic output. The diagnostic acquires live data using a modified experimental setup alongside Pylon and PyDAQmx libraries within a python data acquisition environment. Lab-deployed diagnostic results are presented across varying wave modes, operating conditions, and data quality, currently executed at 3–4 Hz with a variety of iteration speed optimization options to be considered as future work. These speeds exceed that of conventional techniques and offer a proven structure for real-time RDE monitoring. The demonstrated ability to analyze detonation wave presence and behavior during RDE operation will certainly play a vital role in the development of RDE active control, necessary for RDE technology maturation toward industrial integration.

42 ENGINEERING↗

High-Magnification Faraday Rotation Imaging and Analysis of X-pinch Implosion Dynamics

An X-pinch load driven by an intense current pulse (>100 kA in ~100 ns) can result in the formation of a small radius, runaway compressional micro-pinch. A micro-pinch is characterized by a hot (>1 keV), current-driven (>100 kA), high-density plasma column (near solid density) with a small neck diameter (1–10 μm), a short axial extent (<1 mm), and a short duration (.1 ns). With material pressures often well into the multi-Mbar regime, a micro-pinch plasma often radiates an intense, sub-ns burst of sub-keV to multi-keV x-rays. A low-density coronal plasma immediately surrounding the dense plasma neck could potentially shunt current away from the neck and thus reduce the magnetic drive pressure applied to the neck. To study the current distribution in the coronal plasma throughout the implosion process, a Faraday rotation imaging diagnostic (1064 nm) capable of producing simultaneous high-magnification polarimetric and interferometric images has been developed for the 1-MA, 100-ns MAIZE facility at the University of Michigan. Designed with a variable magnification (1–10&times;), this diagnostic achieves a spatial resolution of approximately 35 μm, which is useful for resolving the ~100-μm-scale coronal plasma region immediately surrounding the dense core. Combined with the corresponding interferogram, which provides the radial density distribution in the low-density coronal plasma, the measured rotation can be used to diagnose the delivery of the driver current, and thus the magnetic drive pressure, to the micro-pinch plasma as it approaches minimal radius. Using this technique on MAIZE, we have measured

Dowhan, G. V.↗

A plano–convex thick-lens velocity map imaging apparatus for direct, high resolution 3D momentum measurements of photoelectrons with ion time-of-flight coincidence

Since their inception, velocity map imaging (VMI) techniques have received continued interest in their expansion from 2D to 3D momentum measurements through either reconstructive or direct methods. Recently, much work has been devoted to the latter of these by relating electron time-of-flight (TOF) to the third momentum component. The challenge is having a timing resolution sufficient to resolve the structure in the narrow (<10 ns) electron TOF spread. Here, we build upon the work in VMI lens design and 3D VMI measurement by using a plano–convex thick-lens (PCTL) VMI in conjunction with an event-driven camera (TPX3CAM) providing TOF information for high resolution 3D electron momentum measurements. We perform simulations to show that, with the addition of a mesh electrode to the thick-lens geometry, the resulting plano–convex electrostatic field extends the detectable electron cutoff energy range while retaining the high resolution. This design also extends the electron TOF range, allowing for a better momentum resolution along this axis. We experimentally demonstrate these capabilities by examining above-threshold ionization in xenon, where the apparatus is shown to collect electrons of energy up to ∼7 eV with a TOF spread of ∼30 ns, both of which are improved compared to a previous work by factors of ∼1.4 and ∼3.75, respectively. Finally, the PCTL-VMI is equipped with a coincident ion TOF spectrometer, which is shown to effectively extract unique 3D momentum distributions for different ionic species in a gas mixture. These techniques have the potential to lend themselves to more advanced measurements involving systems where the electron momentum distributions possess non-trivial symmetries.

Instruments & Instrumentation↗

Nanoscale chemical imaging with structured X-ray illumination

High-resolution imaging with compositional and chemical sensitivity is crucial for a wide range of scientific and engineering disciplines. Although synchrotron X-ray imaging through spectromicroscopy has been tremendously successful and broadly applied, it encounters challenges in achieving enhanced detection sensitivity, satisfactory spatial resolution, and high experimental throughput simultaneously. In this work, based on structured illumination, we develop a single-pixel X-ray imaging approach coupled with a generative image reconstruction model for mapping the compositional heterogeneity with nanoscale resolvability. This method integrates a full-field transmission X-ray microscope with an X-ray fluorescence detector and eliminates the need for nanoscale X-ray focusing and raster scanning. We experimentally demonstrate the effectiveness of our approach by imaging a battery sample composed of mixed cathode materials and successfully retrieving the compositional variations of the imaged cathode particles. Bridging the gap between structural and chemical characterizations using X-rays, this technique opens up vast opportunities in the fields of biology, environmental, and materials science, especially for radiation-sensitive samples.

Li, Jizhou↗

A time-resolved, in-chamber x-ray pinhole imager for Z

We have commissioned a new time-resolved, x-ray imaging diagnostic for the Z facility. The primary intended application is for diagnosing the stagnation behavior of Magnetized Liner Inertial Fusion (MagLIF) and similar targets. We have a variety of imaging systems at Z, both time-integrated and time-resolved, that provide valuable x-ray imaging information, but no system at Z up to this time provides a combined high-resolution imaging with multi-frame time resolution; this new diagnostic, called TRICXI for Time Resolved In-Chamber X-ray Imager, is meant to provide time-resolved spatial imaging with high resolution. The multi-frame camera consists of a microchannel plate camera. A key component to achieving the design goals is to place the instrument inside the Z vacuum chamber within 2 m of the load, which necessitates a considerable amount of x-ray shielding as well as a specially designed, independent vacuum system. Here, a demonstration of the imaging capability for a series of MagLIF shots is presented. Predictions are given for resolution and relative image irradiance to guide experimenters in choosing the desired configuration for their experiments.

47 OTHER INSTRUMENTATION↗