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DOE OSTI2017

Toward Scintillator High‐Gain Avalanche Rushing Photoconductor Active Matrix Flat Panel Imager ( SHARP ‐ AMFPI ): Initial fabrication and characterization

Purpose We present the first prototype Scintillator High‐Gain Avalanche Rushing Photoconductor Active Matrix Flat Panel Imager ( SHARP ‐ AMFPI ). This detector includes a layer of avalanche amorphous Selenium (a‐Se) ( HARP ) as the photoconductor in an indirect detector to amplify the signal and reduce the effects of electronic noise to obtain quantum noise‐limited images for low‐dose applications. It is the first time avalanche a‐Se has been used in a solid‐state imaging device and poses as a possible solution to eliminate the effects of electronic noise, which is crucial for low‐dose imaging performance of AMFPI . Methods We successfully deposited a solid‐state HARP structure onto a 24 × 30 cm 2 array of thin‐film transistors ( TFT array) with a pixel pitch of 85 μm. The HARP layer consists of 16 μm of a‐Se with a hole‐blocking and electron‐blocking layer to prevent charge injection from the high‐voltage bias and pixel electrodes, respectively. An electric field ( E S e ) up to 105 V μm −1 was applied across the a‐Se layer without breakdown. A 150 μm thick‐structured CsI:Tl scintillator was used to form SHARP ‐ AMFPI . The x‐ray imaging performance is characterized using a 30 kV p Mo/Mo beam. We evaluate the spatial resolution, noise power, and detective quantum efficiency at zero frequency of the system with and without avalanche gain. The results are analyzed using cascaded linear system model ( CLSM ). Results An avalanche gain of 76 ± 5 was measured at E S e = 105 V μm −1 . We demonstrate that avalanche gain can amplify the signal to overcome electronic noise. As avalanche gain is increased, image quality improves for a constant (0.76 mR ) exposure until electronic noise is overcome. Our system is currently limited by poor optical transparency of our high‐voltage electrode and long integrating time which results in dark current noise. These two effects cause high‐spatial frequency noise to dominate imaging performance. Conclusions We demonstrate the feasibility of a solid‐state HARP x‐ray imager and have fabricated the largest active area HARP sensor to date. Procedures to reduce secondary quantum and dark noise are outlined. Future work will improve optical coupling and charge transport which will allow for frequency DQE and temporal metrics to be obtained.

Scheuermann, James R.↗

DOE OSTI2018

A novel crystallization kinetics model of transcrystalline used for crystallization behavior simulation of short carbon fiber‐reinforced polymer composites

A combined model is presented to simulate the crystallization behavior of short carbon fiber‐reinforced polymer (SCFRP) composites in this work. The combined model accounts for two morphologies in SCFRP: transcrystalline and spherulite. Transcrystalline is affected by complicated processing conditions and fibers and significantly affects the performance of composites. The quantitative modeling of crystallization kinetics of transcrystalline is thus important in predicting the mechanical properties of the composites. Therefore, this work proposes a novel analytical crystallization kinetics model of transcrystalline for SCFRP. In the combined model, the crystallization kinetics of spherulites is calculated using a classic Kolmogorov model. The combined model for SCFRP is first validated using a pixel coloring method in a two‐dimensional (2D) simulation experiment and is then compared with the results of a differential scanning calorimeter (DSC) experiment. The results of the model and experiments (using pixel coloring method and DSC) were found to be in agreement, which proves the rationality of the combined model. The modeling results also show that transcrystalline can accelerate the crystallization rate of composites, and the acceleration effect is more remarkable at high temperature. The proposed crystallization kinetics model has good potential for modelling the crystallization behavior of SCFRP under complex processing conditions. POLYM. ENG. SCI., 59:854–862, 2019. © 2018 Society of Plastics Engineers

Fang, Haidong↗

DOE OSTI2026

Image Distinguishability Analysis Testing Through Principal Components and Its Application to Hot Spot Scale Invariance

Hot spots are spatial regions of intense energy localization that govern initiation of secondary high explosives. Studies that characterize or compare simulated hot spots are frequently either qualitatively descriptive or resort to quantitative distribution functions that neglect stochastic variations and spatial correlations—effects that are also neglected in common comparison tests like the Kolmogorov–Smirnov test. To this end, we develop an image distinguishability analysis (IDA) test based on principal component (PC) analysis that makes pixel-by-pixel comparisons between small, for example, O(<10), image data sets. The IDA test makes comparisons through a generalized distance metric in the PC space and a test statistic that is derived to calculate mathematical equation-values. Here, we derive a statistical distribution and criticality criterion to determine whether images are distinguishable from established baselines. We apply the IDA test on images generated from molecular dynamics simulations of hot spots from pore collapse in TATB to assess scale invariance in the complex patterns of hot spots that form in a representative high explosive crystal. The IDA test shows that TATB hot spot spatial temperature fields and their derived temperature histograms exhibit scale-invariant features over specific intervals of shock orientation, strength, and initial pore diameter. However, the IDA test also shows that qualitatively different conclusions regarding invariance can be reached depending on whether the hot spot is treated as a spatially correlated field as opposed to a distribution function that lacks spatial information.

organic↗

DOE OSTI2018

Sulfur isotope analysis of microcrystalline iron sulfides using secondary ion mass spectrometry imaging: Extracting local paleo-environmental information from modern and ancient sediments

Rationale: Sulfur isotope ratio measurements of bulk sulfide from marine sediments have often been used to reconstruct environmental conditions associated with their formation. In situ microscale spot analyses by secondary ion mass spectrometry (SIMS) and laser ablation multiple-collector inductively coupled plasma mass spectrometry (LA-MC-ICP-MS) have been utilized for the same purpose. However, these techniques are often not suitable for studying small (≤10 μm) grains or for detecting intra-grain variability. Methods: In this work, we present a method for the physical extraction (using lithium polytungstate heavy liquid) and subsequent sulfur isotope analysis (using SIMS; CAMECA IMS 7f-GEO) of microcrystalline iron sulfides. SIMS sulfur isotope ratio measurements were made via Cs + bombardment of raster squares with sides of 20–130 μm, using an electron multiplier (EM) detector to collect counts of 32 S - and 34 S - for each pixel (128 × 128 pixel grids) for between 20 and 960 cycles. Results: The extraction procedure did not discernibly alter pyrite grain-size distributions. The apparent inter-grain variability in 34 S/ 32 S in 1–4 μm-sized pyrite and marcasite fragments from isotopically homogeneous hydrothermal crystals was ~ ±2‰ (1σ), comparable with the standard error of the mean for individual measurements (≤ ±2‰, 1σ). In contrast, grain-specific 34 S/ 32 S ratios in modern and ancient sedimentary pyrites and marcasites can have inter- and intra-grain variability >60‰. The distributions of intra-sample isotopic variability are consistent with bulk 34 S/ 32 S values. Conclusions: SIMS analyses of isolated iron sulfide grains yielded distributions that are isotopically representative of bulk 34 S/ 32 S values. Populations of iron sulfide grains from sedimentary samples record the evolution of the S-isotopic composition of pore water sulfide in their S-isotopic compositions. These data allow past local environmental conditions to be inferred.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Single-Filament Imaging Mass Spectrometry Lipidomics in Arthrospira platensis

Elucidating intra-organismal biochemical and lipid organization in photosynthetic biological cell factories of filamentous cyanobacteria, i.e., Arthrospira platensis (Spirulina), is important to track physiological response mechanisms during growth. Little is known about the filaments' biochemical organization and cellular structure and no label-free imaging techniques exist that provide molecular mapping. We applied ultra-high resolution mass spectrometry (7T FT-ICR-MS) matrix-assisted laser desorption ionization (MALDI) imaging to immobilized Spirulina filaments to investigate the localization of lipids across distinct physiological regions. We optimized matrix selection and deposition methods with the goal of facilitating high spatial, and intra-filament, resolution using untargeted multivariate statistical spectral deconvolution across MS pixels. Our results demonstrate an improved two step application with an optimized procedure for intra-organismal lipid profiling to improve analyte sensitivity and achieve higher spatial resolution, whereby we evaluate three conventional matrices 2,5-dihydroxybenzoic acid (DHB), a 9:1 ratio of DHB:superDHB (sDHB), 1,5- diaminonaphthalene (DAN) and a 50:50 mix of DHB:sDHB and compare delineation and pixel-based elucidation of intra-filament lipidomics. We identified a total of 1,626 features that could be putatively assigned a lipid-like formula based on database query and 46 unique features, with associated lipid assignments that were significantly distinct in their intra-filament location. MALDI- imaging MS with untargeted statistical spectral deconvolution was used to visualize intra-filament lipidomics organization in Spirulina filaments. Improvements in matrix deposition, including sequential sublimation and pneumatic spraying, increased signal abundance at high spatial resolution and allowed for identification of distinct lipid composition regions. Here in this work outlines a methodology that may be used for micro-ecological untargeted molecular phenotyping.

09 BIOMASS FUELS↗

DOE OSTI2018

Spatiotemporal video-domain high-fidelity simulation and realistic visualization of full-field dynamic responses of structures by a combination of high-spatial-resolution modal model and video motion manipulations

Structures with complex geometries, material properties, and boundary conditions exhibit spatially local dynamic behaviors. A high-spatial-resolution model of the structure is thus required for high-fidelity analysis, assessment, and prediction of the dynamic phenomena of the structure. The traditional approach is to build a highly refined finite element computer model for simulating and analyzing the structural dynamic phenomena based on detailed knowledge and explicit modeling of the structural physics such as geometries, materials properties, and boundary conditions. These physics information of the structure may not be available or accurately modeled in many cases, however. In addition, the simulation on the high-spatial-resolution structural model, with a massive number of degrees of freedom and system parameters, is computationally demanding. Here this study, on a proof-of-principle basis, proposes a novel alternative approach for spatiotemporal video-domain high-fidelity simulation and realistic visualization of full-field structural dynamics by an innovative combination of the fundamentals of structural dynamic modeling and the advanced video motion manipulation techniques. Specifically, a low-modal-dimensional yet high-spatial (pixel)-resolution (as many spatial points as the pixel number on the structure in the video frame) modal model is established in the spatiotemporal video domain with full-field modal parameters first estimated from line-of-sight video measurements of the operating structure. Then in order to simulate new dynamic response of the structure subject to a new force, the force is projected onto each modal domain, and the modal response is computed by solving each individual single-degree-of-freedom system in the modal domain. The simulated modal responses are then synthesized by the full-field mode shapes using modal superposition to obtain the simulated full-field structural dynamic response. Finally, the simulated structural dynamic response is embedded into the original video, replacing the original motion of the video, thus generating a new photo-realistic, physically accurate video that enables a realistic, high-fidelity visualization/animation of the simulated full-field vibration of the structure. Laboratory experiments are conducted to validate the proposed method, and the error sources and limitations in practical implementations are also discussed. Compared with high-fidelity finite element computer model simulations of structural dynamics, the video-based simulation method removes the need to explicitly model the structure's physics. In addition, the photo-realistic, physically accurate simulated video provides a realistic visualization/animation of the full-field structural dynamic response, which was not traditionally available. Lastly, these features of the proposed method should enable a new alternative to the traditional computer-aided finite element model simulation for high-fidelity simulating and realistically visualizing full-field structural dynamics in a relatively efficient and user-friendly manner.

42 ENGINEERING↗

DOE OSTI2014

Image Segmentation for Connectomics Using Machine Learning

Reconstruction of neural circuits at the microscopic scale of individual neurons and synapses, also known as connectomics, is an important challenge for neuroscience. While an important motivation of connectomics is providing anatomical ground truth for neural circuit models, the ability to decipher neural wiring maps at the individual cell level is also important in studies of many neurodegenerative diseases. Reconstruction of a neural circuit at the individual neuron level requires the use of electron microscopy images due to their extremely high resolution. Computational challenges include pixel-by-pixel annotation of these images into classes such as cell membrane, mitochondria and synaptic vesicles and the segmentation of individual neurons. State-of-the-art image analysis solutions are still far from the accuracy and robustness of human vision and biologists are still limited to studying small neural circuits using mostly manual analysis. In this chapter, we describe our image analysis pipeline that makes use of novel supervised machine learning techniques to tackle this problem.

connectomics↗

DOE OSTI2014

Studies of azimuthal dihadron correlations in ultra-central PbPb collisions at $\sqrt{s_{NN}} =$ 2.76 TeV

Azimuthal dihadron correlations of charged particles have been measured in PbPb collisions at $\sqrt{s_{NN}}$ = 2.76 TeV by the CMS collaboration, using data from the 2011 LHC heavy-ion run. The data set includes a sample of ultra-central (0-0.2% centrality) PbPb events collected using a trigger based on total transverse energy in the hadron forward calorimeters and the total multiplicity of pixel clusters in the silicon pixel tracker. A total of about 1.8 million ultra-central events were recorded, corresponding to an integrated luminosity of 120 inverse microbarns. The observed correlations in ultra-central PbPb events are expected to be particularly sensitive to initial-state fluctuations. The single-particle anisotropy Fourier harmonics, from $v_2$ to $v_6$, are extracted as a function of particle transverse momentum. At higher transverse momentum, the $v_2$ harmonic becomes significantly smaller than the higher-order $v_n$ (n greater than or equal to 3). The pt-averaged $v_2$ and $v_3$ are found to be equal within 2%, while higher-order $v_n$ decrease as n increases. The breakdown of factorization of dihadron correlations into single-particle azimuthal anisotropies is observed. This effect is found to be most prominent in the ultra-central PbPb collisions, where the initial-state fluctuations play a dominant role. As a result, a comparison of the factorization data to hydrodynamic predictions with event-by-event fluctuating initial conditions is also presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2017

Detecting Surface Changes from an Underground Explosion in Granite Using Unmanned Aerial System Photogrammetry

Efficient detection and high-fidelity quantification of surface changes resulting from underground activities are important national and global security efforts. In this investigation, a team performed field-based topographic characterization by gathering high-quality photographs at very low altitudes from an unmanned aerial system (UAS)-borne camera platform. The data collection occurred shortly before and after a controlled underground chemical explosion as part of the United States Department of Energy’s Source Physics Experiments (SPE-5) series. The high-resolution overlapping photographs were used to create 3D photogrammetric models of the site, which then served to map changes in the landscape down to 1-cm-scale. Separate models were created for two areas, herein referred to as the test table grid region and the nearfield grid region. The test table grid includes the region within ~40 m from surface ground zero, with photographs collected at a flight altitude of 8.5 m above ground level (AGL). The near-field grid area covered a broader area, 90–130 m from surface ground zero, and collected at a flight altitude of 22 m AGL. The photographs, processed using Agisoft Photoscan® in conjunction with 125 surveyed ground control point targets, yielded a 6-mm pixel-size digital elevation model (DEM) for the test table grid region. This provided the ≤3 cm resolution in the topographic data to map in fine detail a suite of features related to the underground explosion: uplift, subsidence, surface fractures, and morphological change detection. The near-field grid region data collection resulted in a 2-cm pixel-size DEM, enabling mapping of a broader range of features related to the explosion, including: uplift and subsidence, rock fall, and slope sloughing. This study represents one of the first works to constrain, both temporally and spatially, explosion-related surface damage using a UAS photogrammetric platform; these data will help to advance the science of underground explosion detection.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Root identification in minirhizotron imagery with multiple instance learning

In this study, multiple instance learning (MIL) algorithms to automatically perform root detection and segmentation in minirhizotron imagery using only image-level labels are proposed. Root and soil characteristics vary from location to location, and thus, supervised machine learning approaches that are trained with local data provide the best ability to identify and segment roots in minirhizotron imagery. However, labeling roots for training data (or otherwise) is an extremely tedious and time-consuming task. This paper aims to address this problem by labeling data at the image level (rather than the individual root or root pixel level) and train algorithms to perform individual root pixel level segmentation using MIL strategies. Three MIL methods (multiple instance adaptive cosine coherence estimator, multiple instance support vector machine, multiple instance learning with randomized trees) were applied to root detection and compared to non-MIL approaches. The results show that MIL methods improve root segmentation in challenging minirhizotron imagery and reduce the labeling burden. In our results, multiple instance support vector machine outperformed other methods. The multiple instance adaptive cosine coherence estimator algorithm was a close second with an added advantage that it learned an interpretable root signature which identified the traits used to distinguish roots from soil and did not require parameter selection.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Validation of a DIXON-based fat quantification technique for the measurement of visceral fat using a CT-based reference standard

Purpose: The purpose of the study is to determine whether a novel semi-automated DIXON-based fat quantification algorithm can reliably quantify visceral fat using a CT-based reference standard. Methods: This was an IRB-approved retrospective cohort study of 27 subjects who underwent abdominopelvic CT within 7 days of proton density fat fraction (PDFF) mapping on a 1.5T MRI. Cross-sectional visceral fat area per slice (cm{sup 2}) was measured in blinded fashion in each modality at intervertebral disc levels from T12 to L4. CT estimates were obtained using a previously published semi-automated computational image processing system that sums pixels with attenuation − 205 to − 51 HU. MR estimates were obtained using two novel semi-automated DIXON-based fat quantification algorithms that measure visceral fat area by spatially regularizing non-uniform fat-only signal intensity or de-speckling PDFF 2D images and summing pixels with PDFF ≥ 50%. Pearson’s correlations and Bland–Altman analyses were performed. Results: Visceral fat area per slice ranged from 9.2 to 429.8 cm{sup 2} for MR and from 1.6 to 405.5 cm{sup 2} for CT. There was a strong correlation between CT and MR methods in measured visceral fat area across all studied vertebral body levels (r = 0.97; n = 101 observations); the least (r = 0.93) correlation was at T12. Bland–Altman analysis revealed a bias of 31.7 cm{sup 2} (95% CI [− 27.1]–90.4 cm{sup 2}), indicating modestly higher visceral fat assessed by MR. Conclusion: MR- and CT-based visceral fat quantification are highly correlated and have good cross-modality reliability, indicating that visceral fat quantification by either method can yield a stable and reliable biomarker.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2018

Outer Wall Segmentation of Abdominal Aortic Aneurysm by Variable Neighborhood Search Through Intensity and Gradient Spaces

Aortic aneurysm segmentation remains a challenge. Manual segmentation is a time-consuming process which is not practical for routine use. To address this limitation, several automated segmentation techniques for aortic aneurysm have been developed, such as edge detection-based methods, partial differential equation methods, and graph partitioning methods. However, automatic segmentation of aortic aneurysm is difficult due to high pixel similarity to adjacent tissue and a lack of color information in the medical image, preventing previous work from being applicable to difficult cases. This paper uses uses a variable neighborhood search that alternates between intensity-based and gradient-based segmentation techniques. By alternating between intensity and gradient spaces, the search can escape from local optima of each space. The experimental results demonstrate that the proposed method outperforms the other existing segmentation methods in the literature, based on measurements of dice similarity coefficient and jaccard similarity coefficient at the pixel level. In addition, it is shown to perform well for cases that are difficult to segment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2018

Performance of an X-ray Microcalorimeter with a 240 μm Absorber and a 50 μm TES Bilayer

Superconducting transition-edge sensor (TES) microcalorimeters are being developed for a variety of potential astrophysics missions, including Athena. The X-ray integral field unit instrument on this mission requires close-packed pixels on a 0.25 mm pitch, and high quantum efficiency between 0.2 and 12 keV. In this work, we describe a new approach with 50 μm square TESs consisting of a Mo/Au bilayer, deposited on silicon nitride membranes to provide a weak thermal conductance to a ~ 50 mK heat bath. Larger TESs usually have additional normal metal stripes on top of the bilayer to reduce the noise. However, we have found that excellent spectral performance can be achieved without the need for any normal metal stripes on top of the TES. A spectral performance of 1.58 ± 0.12 eV at 5.9 keV has been achieved, the best resolution seen in any of our devices with this pixel size.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2018

Error-Correcting Codes for Code-Division Multiplexed TES Detectors

Transition edge sensors (TESs) have proven to be highly sensitive and versatile X-ray spectrometers. Upcoming missions, including Athena X-IFU, will rely on highly multiplexed focal planes where more than 32 TES pixels are read out using a single SQUID amplifier channel. We have implemented an error correction algorithm for code-division multiplexed TES signals that can compensate for potential failures of individual SQUID readout channels and that is both scalable and easily implemented in hardware. We present this algorithm for error correction and show results of laboratory tests to assess algorithm performance at recovering TES channels after a SQUID failure.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2018

Study of Surface Roughness Effect on Super–Normal Transition of Ti/Au Transition Edge Sensor Calorimeters

We are developing transition edge sensor (TES) X-ray microcalorimeters for the future Japanese mission DIOS. It adopts microstrip readout wiring for low pixel-to-pixel crosstalk. In past samples, TES films composed of Ti and Au have not shown proper super–normal transition when it is deposited on the wiring. Assuming that surface roughness of the substrate can influence the transition, we reduced the surface roughness of the underneath layer before deposition of the TES film by using chemical mechanical polishing. We then found that the substrate becomes much smoother with a roughness of <1 nm rms and the TES film shows a proper transition.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Study of Dissipative Losses in AC-Biased Mo/Au Bilayer Transition-Edge Sensors

We are developing kilo-pixel arrays of transition-edge sensors (TESs) for the X-ray Integral Field Unit on ESA’s Athena observatory. Previous measurements of AC-biased Mo/Au TESs have highlighted a frequency-dependent loss mechanism that results in broader transitions and worse spectral performance compared to the same devices measured under DC bias. In order to better understand the nature of this loss, we are now studying TES pixels in different geometric configurations. We present measurements on devices of different sizes and with different metal features used for noise mitigation and X-ray absorption. Our results show how the loss mechanism is strongly dependent upon the amount of metal in close proximity to the sensor and can be attributed to induced eddy current coupling to these features. We present a finite element model that successfully reproduces the magnitude and geometry dependence of the losses. Using this model, we present mitigation strategies that should reduce the losses to an acceptable level.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2018

Development of Multi-chroic MKIDs for Next-Generation CMB Polarization Studies

We report on the status of an ongoing effort to develop arrays of horn-coupled, polarization-sensitive microwave kinetic inductance detectors (MKIDs) that are each sensitive to two spectral bands between 125 and 280 GHz. These multi-chroic MKID arrays are tailored for next-generation, large-detector-count experiments that are being designed to simultaneously characterize the polarization properties of both the cosmic microwave background and Galactic dust emission. We present our device design and describe laboratory-based measurement results from two 23-element prototype arrays. From dark measurements of our first engineering array, we demonstrated a multiplexing factor of 92, showed the resonators respond to bath temperature changes as expected, and found that the fabrication yield was 100%. From our first optically loaded array, we found the MKIDs respond to millimeter-wave pulses; additional optical characterization measurements are ongoing. We end by discussing our plans for scaling up this technology to kilo-pixel arrays over the next 2 years.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2018

Design of Near Infrared and Visible Kinetic Inductance Detectors Using MIM Capacitors

We are developing superconducting Microwave Kinetic Inductance Detectors to operate at near infrared and optical wavelengths for astronomy. In order to efficiently meet with the requirements of astronomical applications, we propose to replace the interdigitated capacitor by a metal–insulator–metal capacitor which has the advantage of presenting a larger capacitance value within a much smaller space. The pixel will occupy a space of typically 100 × 85 µm which is nine times less than a typical pixel size using the interdigitated capacitor operating at the same frequency, below 2 GHz.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗