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All sources NASA NTRS DOE OSTI

DOE OSTI2023

Scalable Detector Design for a High-Resolution Fast-Neutron Radiography Panel

Development of a scalable flat-panel neutron radiography device is needed to meet the nondestructive testing needs of a growing industrial market. Flood field images from a Cs-137 gamma source and a Cf-252 fission neutron source were generated using a detector composed of a 3-mm-thick sheet of EJ-200, and 3-mm-thick sheet of acrylic light spreader, an 8 $\times$ 8 array of SensL MICROFJ-60035-TSV SiPMs, and an IDEAS ROSSPAD readout module. The readout module can be tiled together with similar systems to create a panel of any size, and is only limited by the number of available Ethernet ports in a switching system. A collimated gamma line image demonstrated a 90% spatial resolution of approximately 0.47 line pairs per centimeter and a 10% spatial resolution of approximately 2.32 line pairs per centimeter. A neutron edge image demonstrated a 90% spatial resolution of approximately 0.70 line pairs per centimeter and a 10% spatial resolution of approximately 3.35 line pairs per centimeter. Both of these images show the ability to generate radiographs with sub-SiPM spatial resolution. Using these readout modules, a large-scale radiographic panel can be developed by tiling ROSSPAD modules together.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Quantifying deformation during Zry-4 burst testing: a comparison of BISON and a combined in-situ digital image correlation and infrared thermography method

The development and verification of nuclear fuel-cladding performance codes require extensive testing to establish empirical correlations, necessitating more accelerated testing methods that can replace large validation studies. Here, in the present work, a technique was developed and implemented to experimentally quantify the relationship between temperature, cladding internal pressure, and strain in-situ during a burst test, with the specific aim of generating data for code validation and model refinement. Digital image correlation was used to measure hoop, axial, and radial strain, and infrared thermography to quantify axial temperature gradients. Several key experimental modifications to traditional LOCA burst testing were necessary, but are shown to effectively have little impact on burst temperatures. The time/temperature dependent pressure and time/spatially dependent thermal gradient data were used with BISON to simulate cladding burst and strain rates. Although the measured DIC strains reach appreciable amounts at slightly lower temperatures than BISON simulated strains, there is good agreement between the measured and simulated strains in terms of magnitude and rates leading up to burst. However, in the few seconds prior to and during burst, the BISON simulated strains are significantly lower than the measured strains, indicating the potential for model improvement. The combined experiment and simulation technique may be applied to any new cladding concept to accelerate fuel qualification.

36 MATERIALS SCIENCE↗

DOE OSTI2021

A Method of Ground-Based Cloud Motion Predict: CCLSTM + SR-Net

Ground-based cloud images can provide information on weather and cloud conditions, which play an important role in cloud cover monitoring and photovoltaic power generation forecasting. However, the cloud motion prediction of ground-based cloud images still lacks advanced and complete methods, and traditional technologies based on image processing and motion vector calculation are difficult to predict cloud morphological changes. In this paper, we propose a cloud motion prediction method based on Cascade Causal Long Short-Term Memory (CCLSTM) and Super-Resolution Network (SR-Net). Firstly, CCLSTM is used to estimate the shape and speed of cloud motion. Secondly, the Super-Resolution Network is built based on perceptual losses to reconstruct the result of CCLSTM and, finally, make it clearer. We tested our method on Atmospheric Radiation Measurement (ARM) Climate Research Facility TSI (total sky imager) images. The experiments showed that the method is able to predict the sky cloud changes in the next few steps.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Enabling robust, stable, and accurate nonlinear optical measurements from squeezed light generated in hot rubidium vapor

The feasibility of nonlinear optical (NLO) imaging and spectroscopy using low intensity quantum states of light including entangled photon and squeezed light sources, such as those driven by two-photon absorption (TPA), has been a topic of ongoing debate. An unambiguous identification of the appreciable quantum advantage in such quantum light applications could enable NLO imaging of biological samples without photodegradation and phototoxicity. Recently, we have constructed a two-mode squeezed light source based on four-wave mixing in 85Rb vapor, which is capable of 7.9 dB of intensity-difference squeezing (IDS), corresponding to 8.7 dB upon electronic noise correction. In this talk, we discuss the stability of our system, including implementation details on achieving and maintaining 8.7 dB of IDS for several hours, and ensuring the two spatially multimode beams are properly overlapped in a sample with minimal optical loss.

Allen, Harry [ORNL] (ORCID:0000000190253914)↗

DOE OSTI2023

Chemically sensitive fluorescence imaging of colliding microdroplets

Here, we present a simple optical capability for generating spatially resolved chemical concentration maps of mixing fluids using a chemically sensitive dye, 1-hydroxy-3,6,8-pyrenetrisulfonic acid, detected by planar laser induced fluorescence. To demonstrate an application of this capability, we investigate the collision and mixing of a pair of microdroplets in air. The two microdroplets are composed of different fluids, methanol and water, with the dye initially in the methanol droplet. When the droplets collide and mixing process develops, the fluorescence of the dye shifts from blue to green as the solvent environment changes. A series of spectral-temporal images of the collision and subsequent mixing are recorded, from which we extract the distribution of the two intermixing droplet species reflected in the spatially resolved dye spectra. Images reveal material transfer between droplets in both coalescing and non-coalescing droplet collisions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Using pyrometry to identify porosity in additively manufactured structures

A method and apparatus for identifying porosity in a structure made by an additive manufacturing process in which a laser is scanned across layers of material to form the structure. Pyrometry data comprising images of the layers acquired during additive manufacturing of the structure is received. The pyrometry data is used to generate temperature data comprising estimated temperatures of points in the layers in the images of the layers. The temperature data is used to identify shapes fit to high temperature areas in the images of the layers. Conditions of the shapes fit to the high temperature areas in the images of the layers are identified. Outlier shapes are identified in the shapes fit to the high temperature areas in the images of the layers using the conditions of the shapes.

Mitchell, John A.↗

DOE OSTI2021

“Seeing Is Believing”—In-Depth Analysis by Co-Imaging of Periodically-Poled X-Cut Lithium Niobate Thin Films

Nonlinear and quantum optical devices based on periodically-poled thin film lithium niobate (PP-TFLN) have gained considerable interest lately, due to their significantly improved performance as compared to their bulk counterparts. Nevertheless, performance parameters such as conversion efficiency, minimum pump power, and spectral bandwidth strongly depend on the quality of the domain structure in these PP-TFLN samples, e.g., their homogeneity and duty cycle, as well as on the overlap and penetration depth of domains with the waveguide mode. Hence, in order to propose improved fabrication protocols, a profound quality control of domain structures is needed that allows quantifying and thoroughly analyzing these parameters. In this paper, we propose to combine a set of nanometer-to-micrometer-scale imaging techniques, i.e., piezoresponse force microscopy (PFM), second-harmonic generation (SHG), and Raman spectroscopy (RS), to access the relevant and crucial sample properties through cross-correlating these methods. Based on our findings, we designate SHG to be the best-suited standard imaging technique for this purpose, in particular when investigating the domain poling process in x-cut TFLNs. While PFM is excellently recommended for near-surface high-resolution imaging, RS provides thorough insights into stress and/or defect distributions, as associated with these domain structures. In this context, our work here indicates unexpectedly large signs for internal fields occurring in x-cut PP-TFLNs that are substantially larger as compared to previous observations in bulk LN.

Reitzig, Sven (ORCID:0000000286970379)↗

DOE OSTI2020

Evaluation of Techniques for Vegetation Removal from UAV-Based Photogrammetric DSM near WIPP Land Withdrawal Act Boundary, NM

The Waste Isolation Pilot Plant is located within New Mexico's karst landscape and is the United States' only deep geologic radioactive waste repository which isolates transuranic waste from defense activities underground in a bedded salt formation. Characteristic karst topography in this region is made up of material (such as limestone) that can be dissolved by water over a long period of time, and includes features such as springs, surface streams, sinking streams, caves, and sinkholes. Karst features can potentially impact the integrity of the waste repository in the future and compromise WIPP's performance, particularly when coupled with incompatible land-use activities within the Land Withdrawal Act (LWA) boundary as well as increased water withdrawals outside the LWA. In order to better capture the ground surface topography to support hydrology modeling efforts, the U.S. DOE has enlisted FIU to develop a high-resolution digital elevation model (DEM). In a previous field study, a high-resolution digital surface model (DSM) of an adjacent representative site, Basin 6, was developed by photogrammetry using aerial images captured with unmanned aerial vehicles. The DSM generated was based on point clouds representing the entire landscapes, including points of terrain, vegetation and infrastructure. These above-ground features need to be removed to create a DSM/DEM with good representation of the bare ground. In recent years, many techniques including both pre- and post-processing of DSMs, were developed for vegetation removal with varied success. This research focuses on applying and comparing various vegetation removal methods using point clouds generated of the Basin 6 pilot study area. The 3D RGB-based point cloud classification using Python scripts was a modification of the procedure by Themistocleous (2019). The method using Liblas classifies the point cloud three-dimensionally, whereas the method by Themistocleous (2019) is two-dimensional. The preliminary result of the method using Liblas, however, still had a large amount of vegetation remaining compared to the Pix4D Machine Learning method. The vegetation layer remains highly visible in the DEMs processed using the vegetation indices as opposed to the Pix4D Machine Learning method, which produces a DEM where mostly bare ground is seen. Further modifications to the input parameters are required to improve the vegetation vs. bare ground classification using this approach. The next step will be to improve the method using Liblas and to also test other vegetation removal methods found in the literature review to compare them against the two described here.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2026

Hyperdimensional computing for image classification (HDC) v1.0

This is an implementation of the hyperdimensional computing technique to classify images. It consists of a python script that trains the system for a set of images from a set of images (dataset) specified by the user. This training produces hardware configuration parameters and description vectors that are then loaded into the hardware description part of the project. The hardware description consists of hardware described in Verilog (a well known language for this purpose) that is synthesizable and can be implemented in a real chip. This hardware received the training information generated by python, and then is able to accept images to produce answers for each image on which category (class) from the pre-=trained ones the image belongs to. The hardware and python training scripts are configurable and documented. The advantage of hyperdimensional computing is its robustness to errors and the easy capability for online learning (refining the training during inference slowly over time), which this implementation supports.

Michelogiannakis, Georgios [Lawrence Berkeley Nati↗

DOE OSTI2022

Numerical Investigation of the Spark Discharge Process in a Crossflow

The present study numerically investigates the spark discharge process under crossflow conditions using a thermal equilibrium plasma solver that fully couples the electromagnetic physics and fluid dynamics in a computational framework. Numerical results are validated by the comparison with experimental data. Here, the spark discharge experiment is performed in a constant volume vessel using an inductive coil ignition system for automotive applications, and the evolution of the spark channel is measured using high-speed imaging. The crossflow in the gap between the spark-plug electrodes is generated by a rotating fan with two different fan speeds, and the flow velocity across the gap is characterized by particle image velocimetry (PIV) measurement. A computational fluid dynamics (CFD) solver is employed to simulate the crossflow and provide the flow field variables (velocity, pressure, temperature) to the plasma solver. The crossflow velocity predicted in the flow simulation agrees well with the PIV data in that the non-uniform velocity profiles at monitoring points are reproduced by the CFD code. With the crossflow initialization in the plasma solver, the simulated spark discharge process from the breakdown to spark discharge matches the experimental data, including the voltage and circuit waveforms and the high-speed images of the spark channel evolution. The stretch of spark channel captured by plasma simulations agrees with the measured data. The plasma simulation reveals that the mean temperature of the spark channel is maintained at 5000 K during the discharge phase, and the temperature varies along the spark channel so that the highest value is obtained at the spark root on the center electrode. Overall, the results presented in this paper are meant to provide valuable information about the properties of the plasma generated by the spark discharge.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Phase imaging of irradiated foils at the OMEGA EP facility using phase-stepping X-ray Talbot–Lau deflectometry

Abstract Diagnosing the evolution of laser-generated high energy density (HED) systems is fundamental to develop a correct understanding of the behavior of matter under extreme conditions. Talbot–Lau interferometry constitutes a promising tool, since it permits simultaneous single-shot X-ray radiography and phase-contrast imaging of dense plasmas. We present the results of an experiment at OMEGA EP that aims to probe the ablation front of a laser-irradiated foil using a Talbot–Lau X-ray interferometer. A polystyrene (CH) foil was irradiated by a laser of 133 J, 1 ns and probed with 8 keV laser-produced backlighter radiation from Cu foils driven by a short-pulse laser (153 J, 11 ps). The ablation front interferograms were processed in combination with a set of reference images obtained ex situ using phase-stepping. We managed to obtain attenuation and phase-shift images of a laser-irradiated foil for electron densities above ${10}^{22}\;{\mathrm{cm}}^{-3}$ . These results showcase the capabilities of Talbot–Lau X-ray diagnostic methods to diagnose HED laser-generated plasmas through high-resolution imaging.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Unmanned aircraft system (UAS) detection and assessment via temporal intensity aliasing

A method and system for temporal frequency analysis for identification of unmanned aircraft systems. The method includes obtaining a sequence of video image frames and providing a pixel from an output frame of the video; generating a fluctuating pixel value vector; examining the fluctuating pixel value vector over a period of time; obtaining the frequency information present in the pixel fluctuations; summing the frequency coefficients for the vectorized pixel values from the fluctuating pixel value vector; obtaining an image representing a two dimensional space based on the summed center frequency coefficients; generating a series of still frames equal to a summation of the center frequency coefficients for pixel variations; and combining the temporal information into spatial locations in a matrix to provide a single image containing the spatial and temporal information present in the sequence of video image frame.

Woo, Bryana Lynn↗

DOE OSTI2023

Unmanned aircraft system (UAS) detection and assessment via temporal intensity aliasing

Woo, Bryana Lynn↗

DOE OSTI2023

X-ray self-emission imaging with spherically bent Bragg crystals on the Z-machine

Here, an x-ray imaging scheme using spherically bent crystals was implemented on the Z-machine to image x rays emitted by the hot, dense plasma generated by a Magnetized Liner Inertial Fusion (MagLIF) target. This diagnostic relies on a spherically bent crystal to capture x-ray emission over a narrow spectral range (<15 eV), which is established by a limiting aperture placed on the Rowland circle. The spherical crystal optic provides the necessary high-throughput and large field-of-view required to produce a bright image over the entire, one-cm length of the emitting column of a plasma. The average spatial resolution was measured and determined to be 18 µm for the highest resolution configuration. With this resolution, the radial size of the stagnation column can be accurately determined and radial structures, such as bifurcations in the column, are clearly resolved. The success of the spherical-crystal imager has motivated the implementation of a new, two-crystal configuration for identifying sources of spectral line emission using a differential imaging technique.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Deblurring galaxy images with Tikhonov regularization on magnitude domain

Abstract We propose a regularization-based deblurring method that works efficiently for galaxy images. The spatial resolution of a ground-based telescope is generally limited by seeing conditions and is much worse than space-based telescopes. This circumstance has generated considerable research interest in the restoration of spatial resolution. Since image deblurring is a typical inverse problem and often ill-posed, solutions tend to be unstable. To obtain a stable solution, much research has adopted regularization-based methods for image deblurring, but the regularization term is not necessarily appropriate for galaxy images. Although galaxies have an exponential or Sérsic profile, the conventional regularization assumes the image profiles to behave linearly in space. The significant deviation between the assumption and real situations leads to blurring of the images and smoothing out the detailed structures. Clearly, regularization on logarithmic domain, i.e., magnitude domain, should provide a more appropriate assumption, which we explore in this study. We formulate a problem of deblurring galaxy images by an objective function with a Tikhonov regularization term on a magnitude domain. We introduce an iterative algorithm minimizing the objective function with a primal–dual splitting method. We investigate the feasibility of the proposed method using simulation and observation images. In the simulation, we blur galaxy images with a realistic point spread function and add both Gaussian and Poisson noise. For the evaluation with the observed images, we use galaxy images taken by the Subaru HSC-SSP. Both of these evaluations show that our method successfully recovers the spatial resolution of the deblurred images and significantly outperforms the conventional methods. The code is publicly available from the GitHub 〈https://github.com/kzmurata-astro/PSFdeconv_amag〉.

Murata, Kazumi↗

DOE OSTI2021

ChemPix: automated recognition of hand-drawn hydrocarbon structures using deep learning

Inputting molecules into chemistry software, such as quantum chemistry packages, currently requires domain expertise, expensive software and/or cumbersome procedures. Leveraging recent breakthroughs in machine learning, we develop ChemPix: an offline, hand-drawn hydrocarbon structure recognition tool designed to remove these barriers. A neural image captioning approach consisting of a convolutional neural network (CNN) encoder and a long short-term memory (LSTM) decoder learned a mapping from photographs of hand-drawn hydrocarbon structures to machine-readable SMILES representations. We generated a large auxiliary training dataset, based on RDKit molecular images, by combining image augmentation, image degradation and background addition. Additionally, a small dataset of ~600 hand-drawn hydrocarbon chemical structures was crowd-sourced using a phone web application. These datasets were used to train the image-to-SMILES neural network with the goal of maximizing the hand-drawn hydrocarbon recognition accuracy. By forming a committee of the trained neural networks where each network casts one vote for the predicted molecule, we achieved a nearly 10 percentage point improvement of the molecule recognition accuracy and were able to assign a confidence value for the prediction based on the number of agreeing votes. The ensemble model achieved an accuracy of 76% on hand-drawn hydrocarbons, increasing to 86% if the top 3 predictions were considered.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Transport of intensity equation: a tutorial

When it comes to “phase measurement” or “quantitative phase imaging”, many people will automatically connect them with “laser” and “interferometry”. Indeed, conventional quantitative phase imaging and phase measurement techniques generally rely on the superposition of two beams with a high degree of coherence: complex interferometric configurations, stringent requirements on the environmental stabilities, and associated laser speckle noise severely limit their applications in optical imaging and microscopy. On a different note, as one of the most well-known phase retrieval approaches, the transport of intensity equation (TIE) provides a new non-interferometric way to access quantitative phase information through intensity only measurement. Despite the insufficiency for interferometry, TIE is applicable under partially coherent illuminations (like the Köhler’s illumination in a conventional microscope), permitting optimum spatial resolution, higher signal-to-noise ratio, and better image quality. In this tutorial, we give an overview of the basic principle, research fields, and representative applications of TIE, focus particularly on optical imaging, metrology, and microscopy. The purpose of this tutorial is twofold. It should serve as a self-contained introduction to TIE for readers with little or no knowledge of TIE. On the other hand, it attempts to give an overview of recent developments in this field. These results highlight a new era in which strict coherence and interferometry are no longer prerequisites for quantitative phase imaging and diffraction tomography, paving the way toward new generation label-free three-dimensional microscopy, with applications in all branches of biomedicine.

42 ENGINEERING↗

DOE OSTI2020

Toward nanoscale molecular mass spectrometry imaging via physically constrained machine learning on co-registered multimodal data

Mass spectrometry imaging (MSI) plays a pivotal role in investigating the chemical nature of complex systems that underly our understanding in biology and medicine. Multiple fields of life science such as proteomics, lipidomics and metabolomics benefit from the ability to simultaneously identify molecules and pinpoint their distribution across a sample. However, achieving the necessary submicron spatial resolution to distinguish chemical differences between individual cells and generating intact molecular spectra is still a challenge with any single imaging approach. Here, we developed an approach that combines two MSI techniques, matrix-assisted laser desorption/ionization (MALDI) and time-of-flight secondary ion mass spectrometry (ToF-SIMS), one with low spatial resolution but intact molecular spectra and the other with nanometer spatial resolution but fragmented molecular signatures, to predict molecular MSI spectra with submicron spatial resolution. The known relationships between the two MSI channels of information are enforced via a physically constrained machine-learning approach and directly incorporated in the data processing. We demonstrate the robustness of this method by generating intact molecular MALDI-type spectra and chemical maps at ToF-SIMS resolution when imaging mouse brain thin tissue sections. This approach can be readily adopted for other types of bioimaging where physical relationships between methods have to be considered to boost the confidence in the reconstruction product.

97 MATHEMATICS AND COMPUTING↗