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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Automated CT registration, segmentation, and quantification (AutoCT) v1.1

Processing and analyzing brain imaging is crucial in both scientific development and clinical field. In this software package, we build a pipeline that integrates automatic registration, segmentation, and quantitative analysis for subjects' CT scans. Leveraging diffeomorphic transofrmations, we enable optimized forward and inverse mappings between an image and the reference. Furthermore, we extract localized features from deformation field based on an online template process, which advances statistical learning downstream. The created templates, atlas as well as our methods provide the brain imaging community tools for AI implementations

Bai, Zhe↗
DOE OSTI2021

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components. Third Annual Progress Report

Additive manufacturing (AM) of high-strength corrosion resistance alloys for nuclear energy applications, such as stainless steel and Inconel, is currently based on laser powder bed fusion (LPBF) process. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Probability of crack initiation at the pore depends on size, shape, and orientation of the defect. Pulsed Infrared Thermography Imaging (PIT) provides a capability for non-destructive evaluation (NDE) of sub-surface defects in arbitrary size structures. The PIT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PIT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PIT system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PIT capabilities in detecting microscopic subsurface defects in metals, and classifying shapes and orientation of pores in thermal images. For detection of microscopic defects in PIT imaging data, we have developed Spatial Temporal Denoised Thermal Source Separation (STDTSS) unsupervised machine learning (ML) image processing algorithm. We show that flat bottom hole (FBH) defects as small as 200µm in SS316 and IN718 specimens, can be detected with STDTSS algorithm. To the best of our knowledge, these are the smallest detected defects which are reported in literature. For classification of defects shapes, we have previously developed thermal tomography (TT) algorithm to obtain depth reconstructions of material defects from data cube of sequentially recorded surface temperatures. However, interpretation of TT images is non-trivial because of blurring with increasing depth. To address this challenge, we have developed a deep learning convolutional neural network (CNN) to classify size and orientation subsurface defects in simulated TT images.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Detecting optical transients using artificial neural networks and reference images from different surveys

ABSTRACT We present a technique to detect optical transients based on an artificial neural networks method. We describe the architecture of two networks capable of comparing images of the same part of the sky taken by different telescopes. One image corresponds to the epoch in which a potential transient could exist; the other is a reference image of an earlier epoch. We use data obtained by the Dr. Cristina V. Torres Memorial Astronomical Observatory and archival reference images from the Sloan Digital Sky Survey. We trained a convolutional neural network and a dense layer network on simulated source samples and then tested the trained networks on samples created from real image data. Autonomous detection methods replace the standard process of detecting transients, which is normally achieved by source extraction of a difference image followed by human inspection of the detected candidates. Replacing the human inspection component with an entirely autonomous method would allow for a rapid and automatic follow-up of interesting targets of opportunity. The toy-model pipeline that we present here is not yet able to replace human inspection, but it might provide useful hints to identify potential candidates. The method will be further expanded and tested on telescopes participating in the Transient Optical Robotic Observatory of the South Collaboration.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

An image-driven machine learning approach to kinetic modeling of a discontinuous precipitation reaction

Micrograph quantification is an essential component of several materials science studies. Machine learning methods, in particular convolutional neural networks, have previously demonstrated performance in image recognition tasks across several disciplines (e.g. materials science, medical imaging, facial recognition). Here, we apply these well-established methods to develop an approach to microstructure quantification for kinetic modeling of a discontinuous precipitation reaction in a case study on the uranium-molybdenum system. Prediction of material processing history based on image data (classification), calculation of area fraction of phases present in the micrographs (segmentation), and kinetic modeling from segmentation results were performed. Results indicate that convolutional neural networks represent microstructure image data well, and segmentation using the k-means clustering algorithm yields results that agree well with manually annotated images. Classification accuracies of original and segmented images are both 94% for a 5-class classification problem. Kinetic modeling results agree well with previously reported data using manual thresholding. The image quantification and kinetic modeling approach developed and presented here aims to reduce researcher bias introduced into the characterization process, and allows for leveraging information in limited image data sets.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Development of Thermal Tomography Imaging System for In-Service Nondestructive Evaluation of Additively Manufactured Components

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of nuclear reactor parts. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which can introduce internal material flaws, such as pores and anisotropy. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures due to exposure to high temperature, radiation and corrosive environment in a nuclear reactor. Thermal tomography (TT) provides a capability for non-destructive evaluation of sub-surface defects in arbitrary size structures. We investigate TT of AM stainless steel 316L specimen with imprinted internal porosity defects using relatively low-cost, small form factor infrared (IR) camera based on uncooled micro bolometer detector. Sparse coding related K-means singular value decomposition (SVD) machine learning, image processing algorithms are developed to improve quality of TT images through removal of Additive white Gaussian noise without blurring the images. Following initial qualification of an AM component for deployment in a nuclear reactor, a compact TT can also be used for in-service nondestructive evaluation (NDE). With capability to perform in-service NDE of the AM component lifecycle, TT data can be used for development of a component digital twin. MIT research reactor (MITR) has been identified as a representative environment to perform investigation of feasibility of in-service NDE during shutdown. Preliminary study of radiation level in the MITR viewport, with geometric parameters potentially compatible with compact TT system, has been conducted.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Altered white matter connectivity in patients with schizophrenia: An investigation using public neuroimaging data from SchizConnect

Several studies have produced extensive evidence on white matter abnormalities in schizophrenia (SZ). However, optimum consistency and reproducibility have not been achieved, and reported low white matter tract integrity in patients with SZ varies between studies. A whole-brain imaging study with a large sample size is needed. This study aimed to investigate white matter integrity in the corpus callosum and connections between regions of interests (ROIs) in the same hemisphere in 122 patients with SZ and 129 healthy controls with public neuroimaging data from SchizConnect. For each diffusion-weighted image (DWI), two-tensor full-brain tractography was performed; DWIs were parcellated by processing and registering T1 images with FreeSurfer and Advanced Normalization Tools. White matter query language was used to extract white matter fiber tracts. We evaluated group differences in means of diffusion measures between the patients and controls, and correlations of diffusion measures with the severity of clinical symptoms and cognitive impairment in the patients using the Positive and Negative Syndrome Scale (PANSS), a letter-number sequencing (LNS) test, vocabulary test, letter fluency test, category fluency test, and trail-making test, part A. To correct for multiple comparisons, a false discovery rate of q < 0.05 was applied. In patients with SZ, we observed significant radial diffusivity (RD) and trace (TR) increases in left thalamo-occipital tracts and the right uncinate fascicle, and a significant RD increase in the right middle longitudinal fascicle (MDLF) and the right superior longitudinal fascicle ii. Correlations were present between TR of left thalamo-occipital tracts, and the letter fluency test and the LNS test, and RD in the right MDLF and PANSS positive subscale score. However, these correlations were not significant after correction for multiple comparisons. These results indicated widespread white matter fiber tract abnormalities in patients with SZ, contributing to SZ pathophysiology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Dot tracking methodology for background-oriented schlieren (BOS)

We propose here a dot tracking methodology for processing background-oriented schlieren (BOS) images. The technique improves the accuracy, precision and spatial resolution compared to conventional cross-correlation algorithms. Our methodology utilizes the prior information about the dot pattern such as the location, size and number of dots to provide near 100% yield even for high dot densities (20 dots/32 × 32 pixels) and is robust to image noise. Furthermore, we propose an improvement to the displacement estimation step in the tracking process, especially for noisy images, using a “correlation correction”, whereby we combine the spatial resolution benefit of the tracking method and the smoothing property of the correlation method to increase the dynamic range of the overall measurement process. We evaluate the performance of the method with synthetic BOS images of buoyancy-driven turbulence rendered using ray-tracing simulations, and experimental images of flow in the exit plane of a converging–diverging nozzle. The results show that the improved spatial resolution results in a better accuracy of the tracking method compared to correlation-based methods in regions with sharp displacement gradients, and the correlation correction step reduces the noise floor of the measurement, resulting in a fourfold improvement in the dynamic range.

42 ENGINEERING↗
DOE OSTI2018

Wave Diagnostics and Forcing

Physical possibilities of remote diagnostics and manipulation with the state of the propagation medium by the methods of wave tomosynthesis are considered. This refers to the electromagnetic and acoustic waves as well as waves of other nature. Important are multi-position measurements with retention of phase information at each point of the medium that allows the technology of synthesizing a wide aperture with focusing to be implemented. Processing of wave projections of hidden objects makes it possible to restore their three-dimensional images. In this way, the effect of multiple wave re-reflections is reduced. In addition, the tomographic approach allows one to manipulate with the properties of the media being sounded. Thus, an increase in the radiation power at a chosen focusing point causes hyperthermia that can be used, for example, to treat oncological diseases. And creation of a minimum field and a preset phase distribution in certain regions of the medium opens the possibility of control over the motion of microparticles being trapped. The last circumstance is important, for example, for targeted delivery of medical preparations in medicine.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

First Global Images of Ion Energization in the Terrestrial Foreshock by the Interstellar Boundary Explorer

The Interstellar Boundary Explorer (IBEX) mission provides global energetic neutral atom (ENA) observations from the heliosphere and the Earth's magnetosphere, including spatial, temporal, and energy information. IBEX views the magnetosphere from the sides and almost always perpendicular to noon-midnight plane. We report the first ENA images of the energization process in the Earth's ion foreshock and magnetosheath regions. We show ENA flux and spectral images of the dayside magnetosphere with significant energization of ENA plasma sources (above ~2.7 keV) in the region magnetically connected to the Earth's bow shock (BS) in its quasi-parallel configuration of the interplanetary magnetic field (IMF). We also show that the ion energization increases gradually with decreasing IMF-BS angle, suggesting more efficient suprathermal ion acceleration deeper in the quasi-parallel foreshock.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Separating Bulk and Surface Contributions to Electronic Excited-State Processes in Hybrid Mixed Perovskite Thin Films via Multimodal All-Optical Imaging

A comprehensive understanding of electronic excited-state phenomena underlying the impressive performance of solution-processed hybrid halide perovskite solar cells requires access to both spatially resolved electronic processes and corresponding sample morphological characteristics. In this paper, we demonstrate an all-optical multimodal imaging approach that enables us to obtain both electronic excited-state and morphological information on a single optical microscope platform with simultaneous high temporal and spatial resolution. Specifically, images were acquired for the same region of interest in thin films of chloride containing mixed lead halide perovskites (CH 3 NH 3 PbI 3–x Cl x ) using femtosecond transient absorption, time-integrated photoluminescence, confocal reflectance, and transmission microscopies. Comprehensive image analysis revealed the presence of surface- and bulk-dominated contributions to the various images, which describe either spatially dependent electronic excited-state properties or morphological variations across the probed region of the thin films. Finally, these results show that PL probes effectively the species near or at the film surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Laser ultrasonic imaging of subsurface defects with the linear sampling method

Laser ultrasonics is a remote nondestructive evaluation technique suitable for real-time monitoring of fabrication processes in semiconductor metrology, advanced manufacturing, and other applications where non-contact, high fidelity measurements are required. Here we investigate laser ultrasonic data processing approaches to reconstruct images of subsurface side drilled holes in aluminum alloy specimens. We demonstrate through simulation that the model-based linear sampling method (LSM) can perform accurate shape reconstruction of single and multiple holes and produce images with well-defined boundaries. We experimentally confirm that LSM produces images that represent the internal geometric features of an object, some of which may be missed by conventional imaging.

42 ENGINEERING↗
DOE OSTI2020

Revealing transient powder-gas interaction in laser powder bed fusion process through multi-physics modeling and high-speed synchrotron x-ray imaging

Laser powder bed fusion (LPBF) is an emerging metal additive manufacturing process. The gas-driven powder motions in laser powder bed fusion have significant influence on the build quality. However, the transient powder-gas interaction has not been well understood due to the challenges in quantitative experiment measurements. In this work, the powder-gas interaction for a single pulse laser illuminating on the powder bed is studied. We establish a multi-physics model to simulate the complex liquid/gas flow as well as the gas-driven powder motions, which is substantiated by high-speed synchrotron x-ray imaging. We identify and quantify four characteristic modes of powder-gas interaction in LPBF. The motion of a powder is controlled by one or multiple interaction modes collectively. As revealed by simulations and confirmed by experiments, powders can merge into the molten pool from its rim, be ejected at different divergence angles (powder spattering), or dive into the molten pool to cause significant molten pool fluctuation. Overall, our results provide insights toward the driving forces controlling the dynamic powder behavior, which pave the way for reducing structure defects during the build process.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Features of Construction of the Fluorescent Microscope for the Study of Epithelial-Mesenchymal Transition of Cells in Vitro

An optical luminescent microscope has been developed to monitor the behavior of tumor cells that were modified by GFP and RFP fluorescent proteins and to monitor the formation of metastases in biochips. Images of cells in the light of GFP and RFP fluorescence proteins, as well as in the photography mode, are recorded in the microscope by an noncooled CMOS matrix at the excitation of luminescence by blue and green LEDs and illumination of cells with white LEDs, respectively. The obtained fluorescent images and photos in white light are recorded by the matrix in the same coordinate system and do not require additional processing for combination. The power of irradiation of cells with LEDs does not exceed 50 μW/mm{sup 2} at an exposure time of 1 s, which is an order of magnitude lower than the radiation power causing photodestruction and phototoxicity of cells during long-term studies. Relative parameters of the optical channel of the luminescent microscope have been introduced that allow comparing the sensitivity of the recording system and the minimum power level of the radiation that excites luminescence for optical elements with different spectral characteristics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

High-Resolution Field Emission Scanning Electron Microscopy (FESEM) Imaging of Cellulose Microfibril Organization in Plant Primary Cell Walls

Abstract We have used field emission scanning electron microscopy (FESEM) to study the high-resolution organization of cellulose microfibrils in onion epidermal cell walls. We frequently found that conventional “rule of thumb” conditions for imaging of biological samples did not yield high-resolution images of cellulose organization and often resulted in artifacts or distortions of cell wall structure. Here we detail our method of one-step fixation and dehydration with 100% ethanol, followed by critical point drying, ultrathin iridium (Ir) sputter coating (3 s), and FESEM imaging at a moderate accelerating voltage (10 kV) with an In-lens detector. We compare results obtained with our improved protocol with images obtained with samples processed by conventional aldehyde fixation, graded dehydration, sputter coating with Au, Au/Pd, or carbon, and low-voltage FESEM imaging. The results demonstrated that our protocol is simpler, causes little artifact, and is more suitable for high-resolution imaging of cell wall cellulose microfibrils whereas such imaging is very challenging by conventional methods.

biofuels (including algae and biomass), bio-inspir↗
DOE OSTI2018

In situ liquid cell crystallization and imaging of thiamethoxam by helium ion microscopy

Pest insect control is an essential component for crop protection and public health. Neonicotinoids are a relatively new class of insecticides developed in the last four decades. Thiamethoxam, a member of the neonicotinoid class, has shown outstanding potency for crop protection against a variety of piercing-sucking pests. However, its use in industrial-volume packing and transportation is complicated by crystallization dynamics. In this work, a helium ion microscope (HIM) with a Protochips liquid cell was utilized to crystallize and image thiamethoxam in situ . The results of the study illustrate the growth and morphology of the thiamethoxam crystals at different He + exposure doses, which is markedly different from what has been typically observed. Energy-dispersive x-ray spectroscopy results confirm the presence of the thiamethoxam on the liquid cell membrane. This imaging study illustrates the HIM ability to image and induce the crystallization in soft materials in liquid environments, and attempts to shed light onto the key processes involved in liquid imaging.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Quantitative assessment of particle dispersion in polymeric composites and its effect on mechanical properties

In this work, an automated image analysis tool is developed to establish quantitative correlations between the particle/cluster size distribution and the mechanical properties of particle reinforced polymer composites (PRPC).This automated image analysis tool is developed within python programming software to process and analyze the microstructural images of the polymerbased composite materials. The spent coffee bean powder (SCBP) reinforced poly-propylene carbonate (PPC) polymer composite with differing wt.% of the filler is selected for the analysis. Detailed statistical analysis of the microstructural images reveals that ‘clustering of clusters’ is also presented in addition to the most commonly reported ‘clustering of particles’, and the distribution of particle/clusters is bimodal. Based on these findings, an effective volume fraction for the filler material is proposed to mainly capture the agglomeration effect. With this effective volume fraction, the standard rule-of-mixture model correctly captures the experimentally measured tensile strength and modulus as a function of filler wt.%. Further, the applicability of this effective volume fraction for other theoretical models is also analyzed. The detailed statistical analysis of the microstructure and the proposed effective volume fraction helps to develop a deeper quantitative understanding of the PRPC than the conventional qualitative correlation of microstructural features with the properties and failure processes.

36 MATERIALS SCIENCE↗