Effect of lattice mismatch and shell thickness on strain in core@shell nanocrystals
Abstract not provided
Gamler, Jocelyn T.L.↗
SEARCH · Engineering Papers
Results for “imaging simulators”
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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Quantitative assessment of fitting errors associated with streak camera noise in Thomson scattering data analysis
Thomson scattering measurements in high energy density experiments are often recorded using optical streak cameras. In the low-signal regime, noise introduced by the streak camera can become an important and sometimes the dominant source of measurement uncertainty. In this paper, we present a formal method of accounting for the presence of streak camera noise in our measurements. We present a phenomenological description of the noise generation mechanisms and present a statistical model that may be used to construct the covariance matrix associated with a given measurement. This model is benchmarked against simulations of streak camera images. We demonstrate how this covariance may then be used to weight fitting of the data and provide quantitative assessments of the uncertainty in the fitting parameters determined by the best fit to the data and build confidence in the ability to make statistically significant measurements in the low-signal regime, where spatial correlations in the noise become apparent. These methods will have general applicability to other measurements made using optical streak cameras.
47 OTHER INSTRUMENTATION↗
Elongation factor-Tu can repetitively engage aminoacyl-tRNA within the ribosome during the proofreading stage of tRNA selection
The substrate for ribosomes actively engaged in protein synthesis is a ternary complex of elongation factor Tu (EF-Tu), aminoacyl-tRNA (aa-tRNA), and GTP. EF-Tu plays a critical role in mRNA decoding by increasing the rate and fidelity of aa-tRNA selection at each mRNA codon. Here, using three-color single-molecule fluorescence resonance energy transfer imaging and molecular dynamics simulations, we examine the timing and role of conformational events that mediate the release of aa-tRNA from EF-Tu and EF-Tu from the ribosome after GTP hydrolysis. Our investigations reveal that conformational changes in EF-Tu coordinate the rate-limiting passage of aa-tRNA through the accommodation corridor en route to the peptidyl transferase center of the large ribosomal subunit. Experiments using distinct inhibitors of the accommodation process further show that aa-tRNA must at least partially transit the accommodation corridor for EF-Tu∙GDP to release. aa-tRNAs failing to undergo peptide bond formation at the end of accommodation corridor passage after EF-Tu release can be reengaged by EF-Tu∙GTP from solution, coupled to GTP hydrolysis. These observations suggest that additional rounds of ternary complex formation can occur on the ribosome during proofreading, particularly when peptide bond formation is slow, which may serve to increase both the rate and fidelity of protein synthesis at the expense of GTP hydrolysis.
59 BASIC BIOLOGICAL SCIENCES↗
Mechanical design of the highly porous cuttlebone: A bioceramic hard buoyancy tank for cuttlefish
Cuttlefish, a unique group of marine mollusks, produces an internal biomineralized shell, known as cuttlebone, which is an ultra-lightweight cellular structure (porosity, ~93 vol%) used as the animal’s hard buoyancy tank. Although cuttlebone is primarily composed of a brittle mineral, aragonite, the structure is highly damage tolerant and can withstand water pressure of about 20 atmospheres (atm) for the species Sepia officinalis . Currently, our knowledge on the structural origins for cuttlebone’s remarkable mechanical performance is limited. Combining quantitative three-dimensional (3D) structural characterization, four-dimensional (4D) mechanical analysis, digital image correlation, and parametric simulations, here we reveal that the characteristic chambered “wall–septa” microstructure of cuttlebone, drastically distinct from other natural or engineering cellular solids, allows for simultaneous high specific stiffness (8.4 MN∙m/kg) and energy absorption (4.4 kJ/kg) upon loading. We demonstrate that the vertical walls in the chambered cuttlebone microstructure have evolved an optimal waviness gradient, which leads to compression-dominant deformation and asymmetric wall fracture, accomplishing both high stiffness and high energy absorption. Moreover, the distribution of walls is found to reduce stress concentrations within the horizontal septa, facilitating a larger chamber crushing stress and a more significant densification. Overall, the design strategies revealed here can provide important lessons for the development of low-density, stiff, and damage-tolerant cellular ceramics.
42 ENGINEERING↗
Unveiling the complexity of nanodiamond structures
Understanding nanodiamond structures is of great scientific and practical interest. It has been a long-standing challenge to unravel the complexity underlying nanodiamond structures and to resolve the controversies surrounding their polymorphic forms. Here, we use transmission electron microscopy with high-resolution imaging, electron diffraction, multislice simulations, and other supplementary techniques to study the impacts of small sizes and defects on cubic diamond nanostructures. The experimental results show that common cubic diamond nanoparticles display the (200) forbidden reflections in their electron diffraction patterns, which makes them indistinguishable from new diamond (n-diamond). The multislice simulations demonstrate that cubic nanodiamonds smaller than 5 nm can present the d -spacing at 1.78 Å corresponding to the (200) forbidden reflections, and the relative intensity of these reflections increases as the particle size decreases. Our simulation results also reveal that defects, such as surface distortions, internal dislocations, and grain boundaries can also make the (200) forbidden reflections visible. These findings provide valuable insights into the diamond structural complexity at nanoscale, the impact of defects on nanodiamond structures, and the discovery of novel diamond structures.
36 MATERIALS SCIENCE↗
Wire, hybrid, and laser-cut X-pinches as Talbot–Lau backlighters for electron density diagnostics
Talbot–Lau x-ray deflectometry (TXD) enables refraction-based imaging for high-energy-density physics experiments, and thus, it has been studied and developed with the goal of diagnosing plasmas relevant to inertial confinement and magnetic liner inertial fusion. X-pinches, known for reliably generating fast (~1 ns), small (~1 µm) x-ray sources, were driven on the compact current driver generator for ablation structure and implosion studies (~200 kA, 150 ns) as a potential backlighter source for TXD. Considering that different X-pinch configurations have characteristic advantages and drawbacks as x-ray generating loads, three distinct copper X-pinch configurations were studied: the wire X-pinch, the hybrid X-pinch, and the laser-cut X-pinch. Furthermore, the Cu K-shell emission from each configuration was characterized and analyzed regarding the specific backlighter requirements for an 8 keV TXD system: spatial and temporal resolution, number of sources, time of emission, spectrum, and reproducibility. Recommendations for future experimental improvements and applications are presented. The electron density of static objects was retrieved from Moiré images obtained through TXD. This allowed to calculate the mass density of static samples within 4% of the expected value for laser-cut X-pinches, which were found to be the optimal X-pinch configuration for TXD due to their high reproducibility, small source size (≤5 µm), short duration (~1 ns), and up to 106 W peak power near 8 keV photon energy. Plasma loads were imaged through TXD for the first-time using laser-cut X-pinch backlighting. Experimental images were compared with simulations from the x-ray wave-front propagation code, demonstrating that TXD can be a powerful x-ray refraction-based diagnostic for dense Z-pinch loads. Future plans for Talbot–Lau interferometry diagnostics in the pulsed-power environment are described.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Understanding palladium–tellurium cluster formation on WTe2: From a kinetically hindered distribution to thermodynamically controlled monodispersity
Abstract A fundamental understanding of the transition metal dichalcogenide (TMDC)–metal interface is critical for their utilization in a broad range of applications. We investigate how the deposition of palladium (Pd), as a model metal, on WTe2(001), leads to the assembly of Pd into clusters and nanoparticles. Using X-ray photoemission spectroscopy, scanning tunneling microscopy imaging, and ab initio simulations, we find that Pd nucleation is driven by the interaction with and the availability of mobile excess tellurium (Te) leading to the formation of Pd-Te clusters at room temperature. Surprisingly, the nucleation of Pd-Te clusters is not affected by intrinsic surface defects, even at elevated temperatures. Upon annealing, the Pd-Te nanoclusters adopt an identical nanostructure and are stable up to ∼523 K. Density functional theory calculations provide a foundation for our understanding of the mobility of Pd and Te atoms, preferential nucleation of Pd-Te clusters, and the origin of their annealing-induced monodispersity. These results highlight the role the excess chalcogenide atoms may play in the metal deposition process. More broadly, the discoveries of synthetic pathways yielding thermally robust monodispersed nanostructures on TMDCs are critical to the manufacturing of novel quantum and microelectronics devices and catalytically active nano-alloy centers.
36 MATERIALS SCIENCE↗
Vorticity-induced flow-focusing leads to bubble entrainment in an inkjet printhead: Synchrotron x-ray and volume-of-fluid visualizations
The oscillatory flows present in an inkjet printhead can lead to strong deformations of the air-liquid interface at the nozzle exit. Such deformations may lead to an inward directed air jet with bubble pinch-off and the subsequent entrainment of an air bubble, which is highly detrimental to the stability of inkjet printing. Understanding the mechanisms of bubble entrainment is therefore crucial to improving print stability. Here, in the present work, we use ultrafast x-ray phase-contrast imaging and direct numerical simulations based on the volume-of-fluid method to study the mechanisms underlying the bubble entrainment in a piezoacoustic printhead. We first demonstrate good agreement between experiments and numerics. We then show the different classes of bubble pinch-off obtained in experiments, and that those were also captured numerically. The numerical results are then used to show that the baroclinic torque, which is generated at the gas-liquid interface due to the misalignment of density and pressure gradients, results in a flow-focusing effect that drives the formation of the air jet from which a bubble can pinch off.
42 ENGINEERING↗
Near, far, wherever you are: simulations on the dose efficiency of holographic and ptychographic coherent imaging
Different studies in X-ray microscopy have arrived at conflicting conclusions about the dose efficiency of imaging modes involving the recording of intensity distributions in the near (Fresnel regime) or far (Fraunhofer regime) field downstream of a specimen. A numerical study is presented on the dose efficiency of near-field holography, near-field ptychography and far-field ptychography, where ptychography involves multiple overlapping finite-sized illumination positions. Unlike what has been reported for coherent diffraction imaging, which involves recording a single far-field diffraction pattern, it is found that all three methods offer similar image quality when using the same fluence on the specimen, with far-field ptychography offering slightly better spatial resolution and a lower mean error. These results support the concept that (if the experiment and image reconstruction are done properly) the sample can be near or far; wherever you are, photon fluence on the specimen sets one limit to spatial resolution.
42 ENGINEERING↗
Synthesizing pseudo-Kossel lines from neutron transmission data. I. An analytical approach for recovering single-crystal orientation
The energy-dispersive neutron spectra transmitted through single crystals are characterized by sharp Bragg dips at specific wavelengths, where Bragg's law is being fulfilled for certain crystallographic planes. This phenomenon allows for developing methods for crystal-orientation determination techniques similar to electron backscatter diffraction and X-ray diffraction microscopy. This work presents a new procedure to recover the orientation matrix for single crystals using transmission spectra recorded during rotation of a crystal about an axis perpendicular to a polychromatic neutron beam. The proposed method consists of an initial transformation of the as-collected wavelength–rotation maps to a wavevector $\textit{K}$ space, resulting in linear pseudo-Kossel lines that are suitable for analysis and indexing using image-processing procedures. Further, simulated neutron transmission spectra through a copper crystal with known orientations were used to set and prove the numerical approach. This technique may be expanded for cases where the neutron beam intersects multiple single-crystal grains with different orientations.
36 MATERIALS SCIENCE↗
Towards Interactive, Reproducible Analytics at Scale on HPC Systems
The growth in scientific data volumes has resulted in a need to scale up processing and analysis pipelines using High Performance Computing (HPC) systems. These workflows need interactive, reproducible analytics at scale. The Jupyter platform provides core capabilities for interactivity but was not designed for HPC systems. In this paper, we outline our efforts that bring together core technologies based on the Jupyter Platform to create interactive, reproducible analytics at scale on HPC systems. Our work is grounded in a real world science use case-applying geophysical simulations and inversions for imaging the subsurface. Our core platform addresses three key areas of the scientific analysis workflow-reproducibility, scalability, and interactivity. We describe our implemention of a system, using Binder, Science Capsule, and Dask software. We demonstrate the use of this software to run our use case and interactively visualize real-Time streams of HDF5 data.
containers↗
Simulation Based Inference with Domain Adaptation for Strong Gravitational Lensing
Simulation based inference leverages machine learning to carry out Bayesian inference for systems with intractable likelihoods. However, transitioning a network trained on simulated data to real data runs the risk of encountering domain shift, leading to performance losses. We attempt to implement domain adaptation into the sbi neural posterior estimation framework using the Maximum Mean Discrepancy as an additional network loss. We test two network architectures and use masked autoregressive flow for density estimation. We test the network on a set of 400,000 simulated strong gravitational lensing images generated using deeplenstronomy. The source domain is defined as low noise whereas the target domain has a noise profile sampled from experimentally derived DES survey conditions. We find that, while DA does lead to performance improvements, they are marginal at ~6% less inference error. We also find a similar marginal improvement in uncertainty calibration at around 8%.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Toward Complete Merger Identification at Cosmic Noon with Deep Learning
As we enter the era of large imaging surveys such as Roman, Rubin, and Euclid, a deeper understanding of potential biases and selection effects in optical astronomical catalogs created with the use of ML-based methods is paramount. This work focuses on a deeper understanding of the performance and limitations of deep learning-based classifiers as tools for galaxy merger identification. We train a ConvNeXT-Pico model on mock HST CANDELS images from the IllustrisTNG50 simulation. Our focus is on a more challenging classification of galaxy mergers and non-mergers at higher redshifts 1 < z < 1.5, including minor mergers and lower mass galaxies down to the stellar mass of 108M⊙. We demonstrate, for the first time, that a deep learning model, such as the one developed in this work, can successfully identify even minor and low mass mergers even at these redshifts. Our model achieves overall accuracy, purity, and completeness of over 73%. We show that some galaxy mergers can only be identified from certain observation angles, leading to a potential upper limit in overall accuracy. Using Grad-CAMs and UMAPs, we more deeply examine the performance and observe a visible gradient in the latent space with stellar mass and specific star formation rate, but no visible gradient with merger mass ratio or merger stage.
Schechter, Aimee L. [U. Colorado, Boulder]↗
Bridging Time-series Image Phenotyping and Functional–Structural Plant Modeling to Predict Adventitious Root System Architecture
Root system architecture (RSA) is an important measure of how plants navigate and interact with the soil environment. However, current methods in studying RSA must make tradeoffs between precision of data and proximity to natural conditions, with root growth in germination papers providing accessibility and high data resolution. Functional–structural plant models (FSPMs) can overcome this tradeoff, though parameterization and evaluation of FSPMs are traditionally based in manual measurements and visual comparison. Here, we applied a germination paper system to study the adventitious RSA and root phenology of Populus trichocarpa stem cuttings using time-series image-based phenotyping augmented by FSPM. We found a significant correlation between timing of root initiation and thermal time at cutting collection (P value = 0.0061, R 2 = 0.875), but little correlation with RSA. We also present a use of RhizoVision [1] for automatically extracting FSPM parameters from time series images and evaluating FSPM simulations. A high accuracy of the parameterization was achieved in predicting 2D growth with a sensitivity rate of 83.5%. This accuracy was lost when predicting 3D growth with sensitivity rates of 38.5% to 48.7%, while overall accuracy varied with phenotyping methods. Despite this loss in accuracy, the new method is amenable to high throughput FSPM parameterization and bridges the gap between advances in time-series phenotyping and FSPMs.
60 APPLIED LIFE SCIENCES↗
Acoustic and Thermoacoustic Jet Propulsion
This manuscript bridges the fields of jet propulsion, synthetic jets and thermoacoustic engines. We introduce the case that synthetic jets in air can be considered a consistent approach for propulsion systems. To date, studies on synthetic jet propulsion have been scattered and rather subsidiary. Furthermore, investigating the perspective of propulsion can provide new insights into the field of synthetic jets and the physics of propulsion. In this work, synthetic jet propulsion in air is demonstrated and studied for acoustic and thermoacoustic cases. We developed synthetic jet systems and characterized the resulting propulsion regarding several relevant parameters such as geometric factors and the frequency and power of acoustic jets electromechanically and thermally produced. We demonstrated the 10.4-mN and 2.7-mN thrust in the acoustic and thermoacoustic modes, respectively, using compact tabletop assemblies. The physical mechanism of the jets has been modeled, simulated, verified with Schlieren imaging and laid in the perspective of adherent literature. Similarities and differences regarding traditional jet propulsion systems are discussed. Synthetic jet propulsion in air using a thermal cycle is experimentally demonstrated for the first time.
33 ADVANCED PROPULSION SYSTEMS↗
Detecting Low Surface Brightness Galaxies with Mask R-CNN
Low surface brightness galaxies (LSBGs), galaxies that are fainter than the dark night sky, are famously difficult to detect. However, studies of these galaxies are essential to improve our understanding of the formation and evolution of low-mass galaxies. In this work, we train a deep learning model using the Mask R-CNN framework on a set of simulated LSBGs inserted into images from the Dark Energy Survey (DES) Data Release 2 (DR2). This deep learning model is combined with several conventional image pre-processing steps to develop a pipeline for the detection of LSBGs. We apply this pipeline to the full DES DR2 coadd image dataset, and preliminary results show the detection of 22 large, high-quality LSBG candidates that went undetected by conventional algorithms. Furthermore, we find that Galactic cirrus represents the largest contaminant in our resulting candidate list.
Levy, Caleb↗
Simulation based inference with domain adaptation for strong gravitational lensing
Simulation based inference leverages machine learning to carry out Bayesian inference in systems with intractable likelihoods. However, transitioning a network trained on simulated data to real data runs the risk of encountering domain shift, leading to performance losses. We attempt to implement domain adaptation into the sbi neural posterior estimation framework using the Maximum Mean Discrepancy as an additional network loss, using masked autoregressive fow (MAF) as our density estimator. We test the network on a set of 400,000 simulated strong gravitational lensing images generated using deeplenstronomy. The source domain is defined as low noise whereas the target domain has a noise profile sampled from experimentally derived DES survey conditions. We find that SBI appears robust against small changes in the data with similar performance on source and target. Moreover, while DA does lead to performance improvements, they are marginal at 6% less inference error.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Discrete-Element and Material-Point Method (DEM and MPM) Based Solvers for Sustainable Technologies
We present the use of discrete element method (DEM) and material point method (MPM) in three relevant green technology applications that include biomass feedstock handling, lithium-ion battery manufacturing, and high-pressure reverse osmosis. Our open-source DEM and MPM solvers are developed using performance portable grid and particle management library, AMReX, thus enabling superior performance on NVIDIA and AMD GPUs with > 100 million particles. Our DEM solver resolves the motion of individual particles in a granular system and includes a bonded sphere method for modeling non-spherical particles along with Hertzian and liquid bridge-based contact models. We simulate highly variable biomass feedstock flows in large-scale hoppers for biofuel production and electrode calendering in battery manufacturing using DEM. Our simulations predict flow blockage in large scale biomass hoppers and electrode microstructure variations, thus providing valuable information for biofuel and battery manufacturers, respectively. The second half of the talk will be on MPM and its application towards pore resolved simulations of reverse osmosis membranes under compressive loads. We present a validation study of our MPM simulations with membrane microscopy imaging thus providing useful insights on membrane stability under high pressure conditions. We also present a spectral stability analysis of using linear hat, quadratic and cubic spline basis in MPM indicating regions of numerical stability.
BIOMASS FUELS,MATHEMATICS AND COMPUTING↗