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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Nanophotonic waveguide chip-to-world beam scanning

A seamless chip-to-world photonic interface enables broad advancements in optical ranging, display, communication, computation and quantum information science. The ideal solution enables two-dimensional scanning of a diffraction-limited beam from anywhere on a photonic integrated circuit to a large number of resolvable spots. Current beam-scanning technologies are limited by a fundamental trade-off: photonic-integrated-circuits with diffractive optics offer scalability but have poor mode quality, whereas inertially limited micromechanical scanners provide high-quality beams but lack scalable integration. Here we report a photonic ski-jump—a nanoscale waveguide monolithically integrated on a piezoelectric cantilever—to overcome these limitations. It passively curls ~90° out-of-plane within a less-than-0.1 mm 2 footprint, emits a submicrometre, broadband diffraction-limited beam, and exhibits kilohertz-rate mechanical resonances with quality factors of over 10,000. Fabricated in a volume complementary metal–oxide–semiconductor (CMOS) foundry, our device enables scalable two-dimensional beam scanning. Driven on-resonance at CMOS-level voltages, it achieves a footprint-adjusted spot rate of 68.6 mega spots s –1 mm–², exceeding state-of-the-art micro-electro-mechanical systems mirrors by more than 50-fold, which is sufficient for one million pixels at 100 Hz from an approximately 1.5 mm diameter footprint. We demonstrate full-colour image and video projection, and single-photon initialization and readout from silicon vacancy centres in diamond. Finally, by demonstrating uniformity across a 64 ski-jump array, we establish a pathway to achieving greater than one gigaspot resolution at kilohertz rates within a sub-5-cm-diameter footprint, creating a seamless optical pipeline between integrated photonic processors and the free-space world.

Displays↗
DOE OSTI2020

Real-time observation of dynamic structure of liquid-vapor interface at nanometer resolution in electron irradiated sodium chloride crystals

The dynamics and structure of the liquid and vapor interface has remained elusive for decades due to the lack of an effective tool for directly visualization beyond micrometer resolution. Here, we designed a simple liquid-cell for encapsulating the liquid state of sodium for transmission electron microscopic (TEM) observation. The real-time dynamic structure of the liquid-vapor interface was imaged and videoed by TEM on the sample of electron irradiated sodium chloride (NaCl) crystals, a well-studied sample with low melting temperature and quantum super-shells of clusters. The nanometer resolution images exhibit the fine structures of the capillary waves, composed of first-time observed three zones of structures and features, i.e. flexible nanoscale fibers, nanoparticles/clusters, and a low-pressure area that sucks the nanoparticles from the liquid to the interface. Although the phenomenons were observed based on irradiated NaCl crystals, the similarities of the phenomenons to predictions suggest our real-time ovserved dynamic structure might be useful in validating long-debated theoretical models of the liquid-vapor interface, and enhancing our knowledge in understanding the non-equilibrium thermodynamics of the liquid-vapor interface to benefit future engineering designs in microfluidics.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Nanoscale defect evaluation framework combining real-time transmission electron microscopy and integrated machine learning-particle filter estimation

Observation of dynamic processes by transmission electron microscopy (TEM) is an attractive technique to experimentally analyze materials’ nanoscale phenomena and understand the microstructure-properties relationships in nanoscale. Even if spatial and temporal resolutions of real-time TEM increase significantly, it is still difficult to say that the researchers quantitatively evaluate the dynamic behavior of defects. Images in TEM video are a two-dimensional projection of three-dimensional space phenomena, thus missing information must be existed that makes image’s uniquely accurate interpretation challenging. Therefore, even though they are still a clustering high-dimensional data and can be compressed to two-dimensional, conventional statistical methods for analyzing images may not be powerful enough to track nanoscale behavior by removing various artifacts associated with experiment; and automated and unbiased processing tools for such big-data are becoming mission-critical to discover knowledge about unforeseen behavior. We have developed a method to quantitative image analysis framework to resolve these problems, in which machine learning and particle filter estimation are uniquely combined. The quantitative and automated measurement of the dislocation velocity in an Fe-31Mn-3Al-3Si autunitic steel subjected to the tensile deformation was performed to validate the framework, and an intermittent motion of the dislocations was quantitatively analyzed. The framework is successfully classifying, identifying and tracking nanoscale objects; these are not able to be accurately implemented by the conventional mean-path based analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Deep learning-based noise filtering toward millisecond order imaging by using scanning transmission electron microscopy

Application of scanning transmission electron microscopy (STEM) to in situ observation will be essential in the current and emerging data-driven materials science by taking STEM’s high affinity with various analytical options into account. As is well known, STEM’s image acquisition time needs to be further shortened to capture a targeted phenomenon in real-time as STEM’s current temporal resolution is far below the conventional TEM’s. However, rapid image acquisition in the millisecond per frame or faster generally causes image distortion, poor electron signals, and unidirectional blurring, which are obstacles for realizing video-rate STEM observation. Here we show an image correction framework integrating deep learning (DL)-based denoising and image distortion correction schemes optimized for STEM rapid image acquisition. By comparing a series of distortion corrected rapid scan images with corresponding regular scan speed images, the trained DL network is shown to remove not only the statistical noise but also the unidirectional blurring. This result demonstrates that rapid as well as high-quality image acquisition by STEM without hardware modification can be established by the DL. The DL-based noise filter could be applied to in-situ observation, such as dislocation activities under external stimuli, with high spatio-temporal resolution.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Tracking blobs in the turbulent edge plasma of a tokamak fusion device

Abstract The analysis of turbulence in plasmas is fundamental in fusion research. Despite extensive progress in theoretical modeling in the past 15 years, we still lack a complete and consistent understanding of turbulence in magnetic confinement devices, such as tokamaks. Experimental studies are challenging due to the diverse processes that drive the high-speed dynamics of turbulent phenomena. This work presents a novel application of motion tracking to identify and track turbulent filaments in fusion plasmas, called blobs, in a high-frequency video obtained from Gas Puff Imaging diagnostics. We compare four baseline methods (RAFT, Mask R-CNN, GMA, and Flow Walk) trained on synthetic data and then test on synthetic and real-world data obtained from plasmas in the Tokamak à Configuration Variable (TCV). The blob regime identified from an analysis of blob trajectories agrees with state-of-the-art conditional averaging methods for each of the baseline methods employed, giving confidence in the accuracy of these techniques. By making a dataset and benchmark publicly available, we aim to lower the entry barrier to tokamak plasma research, thereby greatly broadening the community of scientists and engineers who might apply their talents to this endeavor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Predicting wind-driven spatial deposition through simulated color images using deep autoencoders

Abstract For centuries, scientists have observed nature to understand the laws that govern the physical world. The traditional process of turning observations into physical understanding is slow. Imperfect models are constructed and tested to explain relationships in data. Powerful new algorithms can enable computers to learn physics by observing images and videos. Inspired by this idea, instead of training machine learning models using physical quantities, we used images, that is, pixel information. For this work, and as a proof of concept, the physics of interest are wind-driven spatial patterns. These phenomena include features in Aeolian dunes and volcanic ash deposition, wildfire smoke, and air pollution plumes. We use computer model simulations of spatial deposition patterns to approximate images from a hypothetical imaging device whose outputs are red, green, and blue (RGB) color images with channel values ranging from 0 to 255. In this paper, we explore deep convolutional neural network-based autoencoders to exploit relationships in wind-driven spatial patterns, which commonly occur in geosciences, and reduce their dimensionality. Reducing the data dimension size with an encoder enables training deep, fully connected neural network models linking geographic and meteorological scalar input quantities to the encoded space. Once this is achieved, full spatial patterns are reconstructed using the decoder. We demonstrate this approach on images of spatial deposition from a pollution source, where the encoder compresses the dimensionality to 0.02% of the original size, and the full predictive model performance on test data achieves a normalized root mean squared error of 8%, a figure of merit in space of 94% and a precision-recall area under the curve of 0.93.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Assessment of ITER radiation environment during the remote-handling operation of In-Vessel components with D1SUNED

During ITER operational life, a remote-handled cask will be used to transfer In-Vessel components to the Hot Cell for maintenance, storage and decommissioning purposes. Due to the distribution of penetrations for system allocation in the facility, the radiation field of each transfer operation presents a high spatial variability; all operations must be studied independently for workers and electronics protection. In this paper, we present a fully representative approach to describe the radiation environment during the complete remote-handling scenario of In-Vessel components in the ITER facility. The impact of all relevant radiation sources during different stages of the operation is addressed. As-built structures and 2020 baseline designs are considered to produce the most detailed neutronics model of the Tokamak Complex, the 400,000-tonne civil structure hosting the tokamak, up to date. Novel capabilities of the D1SUNED code have allowed to compute the integral dose, the dose rate and the photon-induced neutron flux of both moving and static radiation sources. Time bins are included in the simulations to compute the dose rate caused by In-Vessel components at all positions along the transfer. The time evolution of the dose rate is built in video format with a 1-m resolution, especially valuable for hot-spots identification.

42 ENGINEERING↗
DOE OSTI2020

Quantifying patterns in optical micrographs of one- and two-dimensional ellipsoidal particle assemblies

Current developments in colloidal science include the assembly of anisotropic colloids with broad geometric diversity. As the complexity of particle assemblies increases, the need for ubiquitous algorithms that quantitatively analyze images of the assemblies to deliver key information such as quantification of crystal structures becomes more urgent. This contribution describes algorithms capable of image analysis for classifying colloidal structures based on abstracted interparticle relationship information and quantitatively analyzing the abundance of each structure in mixed pattern assemblies. The algorithm parameters can be adjusted, allowing for the algorithms to be adapted for different image analyses. Three different ellipsoidal particle assembly images are presented to demonstrate the effectiveness of the algorithms: a one-dimensional (1D) particle chain assembly and two two-dimensional (2D) polymorphic crystals each consisting of assemblies of two distinct plane symmetry groups. Angle relationships between neighbouring particles are calculated and neighbour counts of each particle are determined. Combining these two parameters as rules for classification criteria allows for the labeling and quantification of each particle into a defined symmetry class within an assembly. The algorithms provide a labelled image comprising classification results and particle counts of each defined class. For multiple images or individual frames from a video, the script can be looped to achieve automatic processing. The yielded classification data allow for more in-depth image analysis of mixed pattern particle assemblies. Finally, we envision that these algorithms will have utility in quantitative analysis of images comprising ellipsoidal colloidal materials, nanoparticles, or biological matter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

MultiTaskDeltaNet: change detection-based image segmentation for operando ETEM with application to carbon gasification kinetics

Transforming in situ transmission electron microscopy (TEM) imaging into a tool for spatially-resolved operando characterization of solid-state reactions requires automated, high-precision semantic segmentation of dynamically evolving features. However, traditional deep learning methods for semantic segmentation often face limitations due to the scarcity of labeled data, visually ambiguous features of interest, and scenarios involving small objects. To tackle these challenges, we introduce MultiTaskDeltaNet (MTDN), a novel deep learning architecture that creatively reconceptualizes the segmentation task as a change detection problem. By implementing a unique Siamese network with a U-Net backbone and using paired images to capture feature changes, MTDN effectively leverages minimal data to produce high-quality segmentations. Furthermore, MTDN utilizes a multi-task learning strategy to exploit correlations between physical features of interest. In an evaluation using data from in situ environmental TEM (ETEM) videos of filamentous carbon gasification, MTDN demonstrated a significant advantage over conventional segmentation models, particularly in accurately delineating fine structural features. Notably, MTDN achieved a 10.22% performance improvement over conventional segmentation models in predicting small and visually ambiguous physical features. This work bridges key gaps between deep learning and practical TEM image analysis, advancing automated characterization of nanomaterials in complex experimental settings.

08 HYDROGEN↗
DOE OSTI2020

Shock initiation and hot spots in plastic-bonded 1,3,5-triamino-2,4,6-trinitrobenzene (TATB)

TATB (1,3,5-triamino-2,4,6-trinitrobenzene) is a powerful explosive whose dynamical behavior is difficult to study because TATB is so insensitive to initiation by shock waves. We used a tabletop microscope equipped with 0–4.5 km/s laser-launched flyer plates to study shock initiation of TATB, which was fabricated in the form of an array of hundreds of plastic-bonded explosive minicharges (X-TATB = 80% TATB + 20% Sylgard 182 polymer). The 4 ns shocks from the flyer plates were not effective in initiating TATB, but we also developed a two-layer array where flyers first initiated a plastic-bonded PETN (pentaerythritol tetranitrate) charge (X-PETN = 80% PETN + 20% Sylgard), which drove an initiating 25 ns shock into the X-TATB. Thermal emission from shocked X-TATB was used to measure time-dependent temperature profiles with a resolution of 2 ns and to produce high-speed (5 ns) videos. In X-TATB, flyer plates produced 2500–3500 K hot spots and combustion at 2500 K. With X-PETN initiators, X-TATB had 3500–4000 K hot spots and a powerful volume explosion lasting a few nanoseconds. Prospects for producing TATB detonations on a tabletop are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Further developments on observations of the Taylor instability in a dusty plasma

We previously reported the observation of a hydrodynamic-type interchange instability occurring sporadically at the curved interface between two dust clouds of different densities, in a three-dimensional dusty plasma [Pacha et al., Phys. Plasmas 19, 014501 (2012)]. The mechanism for the instability was not conclusively identified. Further analysis of the video images has been performed, showing that the instability is associated with the appearance of large amplitude dust acoustic waves or shocks. Evidence of a dust acoustic shock at the boundary, which could drive a Richtmyer–Meshkov-type instability, will be presented. We also discuss the possibility, suggested by Avinash and Sen [Phys. Plasmas 22, 083707 (2015)], that the observed instability is due to a Rayleigh–Taylor instability driven by a component of the gravitational acceleration, which is perpendicular to the curved boundary.

Pacha, K. A.↗
DOE OSTI2020

Standoff detection of chemical plumes from high explosive open detonations using a swept-wavelength external cavity quantum cascade laser

A swept-wavelength external cavity quantum cascade laser (ECQCL) is used to perform standoff detection of combustion gases in a plume generated from an outdoor high-explosive (HE) open detonation. The swept-ECQCL system was located at a standoff distance of 830 m from a 41kg charge of LX-14(polymer-bonded high explosive) and was used to measure the infrared transmission/absorption through the post-detonation plume as it propagated through the beam path. The swept-ECQCL was operated continuously to record broadband absorption spectra at 200hz rate over a spectral range from 2050 to 2230 cm -1 (4.48 - 4.88 μm). Fitting of measured spectra was used to determine time-resolved column densities of CO, CO 2 , H 2 O, and N 2 O. Analysis of visible video imagery was used to provide timing correlations and to estimate plume dimensions, from which gas mixing ratios were estimated. Measured emission factors and modified combustion efficiency show good agreement with previously reported values.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

A combined numerical and experimental study to elucidate primary breakup dynamics in liquid metal droplet-on-demand printing

Droplet-on-demand liquid metal jetting is emerging as a powerful technology for the additive manufacturing of metallic parts. The success of this method hinges on overcoming several technological challenges. Additionally, the principal one among these challenges is the controlled repeatable ejection of single uniform droplets. Due to the high density and surface tension of liquid metals, the droplet ejection process occurs near the minimal extremes of the printability phase diagram, defined by acceptable ranges for the Weber (We) and Ohnesorge (Oh) numbers. In this work, we experimentally demonstrate the satellite-free ejection of pneumatically actuated molten tin droplets in this extreme corner of printability and use a combination of high-speed video analysis and volume-of-fluid modeling to elucidate the droplet dynamics. While the simulations at low Oh and We can correctly describe several aspects of the breakup process, such as an increasing tail and pinch-point near the nozzle, no single parameter set can completely capture the droplet shape at breakup. Instead, the experimental droplet dynamics appear to include features from both high and low Oh breakup. This disagreement is ascribed to the incomplete description of the droplet ejection process including wetting and exit effects near the nozzle opening and surface effects such as transient cooling and oxide formation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Imaging pyrometry for most color cameras using a triple pass filter

A simple combination of the Planck blackbody emission law, optical filters, and digital image processing is demonstrated to enable most commercial color cameras (still and video) to be used as an imaging pyrometer for flames and explosions. The hardware and data processing described take advantage of the color filter array (CFA) that is deposited on the surface of the light sensor array present in most digital color cameras. In this work, a triple-pass optical filter incorporated into the camera lens allows light in three 10-nm wide bandpass regions to reach the CFA/light sensor array. These bandpass regions are centered over the maxima in the blue, green, and red transmission regions of the CFA, minimizing the spectral overlap of these regions normally present. A computer algorithm is used to retrieve the blue, green, and red image matrices from camera memory and correct for remaining spectral overlap. A second algorithm calibrates the corrected intensities to a gray body emitter of known temperature, producing a color intensity correction factor for the camera/filter system. The Wien approximation to the Planck blackbody emission law is used to construct temperature images from the three color (blue, green, red) matrices. A short pass filter set eliminates light of wavelengths longer than 750 nm, providing reasonable accuracy (±10%) for temperatures between 1200 and 6000 K. The effectiveness of this system is demonstrated by measuring the temperature of several systems for which the temperature is known.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

A liquid metal dropper for experiments on the wettability of liquid metals on plasma facing components

A liquid metal dropper has been developed as a part of the Ion-Gas-Neutral Interactions with Surfaces 2 (IGNIS-2) facility at The Pennsylvania State University. The dropper has the capability of directly applying drops to candidate plasma facing materials for nuclear fusion reactors to enable measurements of their liquid metal wetting properties. The results presented here are specific to the use of lithium in the dropper. This paper discusses the design choices of the liquid metal dropper and its chamber, including the heating and temperature control and the dropper’s motorized operation. Lithium drops of masses ranging from 0.05 g up to 0.13 g, equivalent to drop diameters between 5.6 mm to 1 cm, have been consistently dispensed by the dropper. A new algorithm is developed and used to automate the analysis of the contact angle between the liquid drops and substrate material for efficient analysis of video data recorded to study the wetting properties of candidate plasma-facing components.

Instruments & Instrumentation↗
DOE OSTI2024

Shock tube experiments on the three-layer Richtmyer–Meshkov instability

Here, a vertical shock tube is used for experiments on the three-layer Richtmyer–Meshkov instability. Two closely spaced membrane-less interfaces are formed by the flow of two different sects of three gases: one with air above CO 2 above SF 6 and the other with helium above air above SF 6 . The lightest of the three gases enters the shock tube at the top of the driven section and flows downward. Conversely, the heaviest gas enters at the bottom of the shock tube and flows upward while the intermediate density gas enters at the middle through porous plates. All three gases are allowed to escape through holes at the layer location, leaving an approximately 30-mm layer of intermediate-density gas suspended between the lightest gas from above and the heaviest gas from below. A single-mode, two-dimensional initial perturbation is then imposed on the lower interface by oscillating the shock tube in the horizontal direction. The flow is visualized by seeding the intermediate gas with particles and illuminating it with a pulsed laser. Image sequences are then captured using high-speed video cameras. Perturbation amplitude measurements are made from the three-layer system and compared with measurements from 2, two-layer systems. It is observed that the presence of the upper, initially flat interface produces a decrease in growth of instability amplitude in the nonlinear phase over an equivalent single-interface configuration.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Producing two-dimensional dust clouds and clusters using a movable electrode for complex plasma and fundamental physics experiments

We report a Bidirectional Electrode Control Arm Assembly (BECAA) for precisely manipulating dust clouds levitated above the powered electrode in RF plasmas. The reported techniques allow the creation of perfectly 2D dust layers by eliminating off-plane particles by moving the electrode from outside the plasma chamber without altering the plasma conditions. Here, the tilting and moving of electrodes using BECAA also allows the precise and repeatable elimination of dust particles one by one to achieve any desired number of grains N without trial and error. Simultaneously acquired top and side view images of dust clusters show that they are perfectly planar or 2D. A demonstration of clusters with N = 1–28 without changing the plasma conditions is presented to show the utility of BECAA for complex plasma and statistical physics experimental design. Demonstration videos and 3D printable part files are available for easy reproduction and adaptation of this new method to repeatably produce 2D clusters in existing RF plasma chambers.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗