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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Legacy surface change analyses of the 1993 Rock Valley earthquake sequence for direct comparison to planned NA-22 underground conventional high-explosive experiments (Source Physics Experiment 3 (SPE3) - RV/DC Task 1.3 FY22 Final Report)

Recent work under two previous phases of the NNSA NA-22 Source Physics Experiment (SPE) have shown that underground chemical high-explosive experiments can produce detectable surface changes that differ in spatial extent and vertical magnitude depending on the geologic media at the site (Schultz-Fellenz et al., 2018; 2020; Crawford et al., 2021). Neither of these two prior phases of SPE identified natural earthquake-related surface effects in the same region that occurred at a similar depth as the explosive experiments for direct comparison. While earthquakes can also produce surface changes that are detectable using remote sensing data analyses, it is expected that the pattern and spatial extent of surface changes would vary between earthquakes and explosions. However, no direct-observed surface-change signature comparison between earthquakes and explosions has ever been performed. The SPE Phase 3 Rock Valley/Direct Comparison (RV/DC) program presents a unique opportunity to investigate and characterize co-occurrence of both earthquakes and explosions. In this project, we worked to address five tasks in a workflow, as follows: 1. Identify and obtain existing high-resolution legacy satellite and aerial imagery as close in time before and after the 1993 Rock Valley earthquake sequence to temporally constrain the analyses. 2. Transform these pre-earthquake and post-earthquake datasets into digital elevation models (DEMs) using geospatial analysis software packages (e.g., ArcGIS, Agisoft Metashape, and Google Earth Engine). 3. Perform DEM differencing analyses to assess and quantify earthquake-related changes from the 1993 sequence, and develop map products that visualize these analyses. 4. Use the analyses from (3) to: (a) assess spatial distribution and magnitude of surface changes due to the 1993 Rock Valley earthquake sequence, and (b) determine parameters of forthcoming, planned explosion-related surface change data collection from sensors mounted on unmanned aerial vehicles (UAVs) (e.g., spatial extent of collection, design and density of survey control, sensors to deploy, forward speed and line spacing of UAV flight lines, flight altitude). 5. Develop a summary report on the analyses, including how the analyses define parameters and identify focus areas for any future surface change analytical field campaigns related to the explosive experiment. Analyzing these legacy data and identifying whether they can detect any surface changes related to the earthquake sequence facilitates opportunities for direct signature comparison of surface change from explosions at one location, which has never previously been performed. Comparing the surface change signatures from a co-located and depth-equivalent earthquake and an explosion could help to advance remote sensing event discrimination techniques. This report summarizes the work completed toward this ambitious goal.

42 ENGINEERING↗
DOE OSTI2024

Spin Textures at Conformal Surfaces and Interfaces: CRADA Final Report

The scientific and technological exploration of artificially designed three-dimensional magnetic nanostructures opens the path to exciting novel physical phenomena, originating from the increased complexity in spin textures, topology, and frustration in three dimensions. Theory predicts that the equilibrium magnetic ground state of two-dimensional systems which reflects the competition between symmetric (Heisenberg) and antisymmetric (Dzyaloshinskii-Moriya interaction (DMI)) exchange interaction is significantly modified on curved surfaces when the radius of local curvature becomes comparable to fundamental magnetic length scales. In this CRADA we performed collaboratively an experimental study of the spin texture in an 8 nm thin magnetic multilayer with growth-induced in-plane anisotropy and DMI deposited onto the curved surface of a 1.8µm long non-magnetic carbon nanowire with a 67 nm radius. The sample was fabricated in Juelich and with collaborators at BESSY in Berlin. Using magnetic soft x-ray tomography at the ALBA synchrotron in Spain, the three-dimensional spin configuration in this nanotube was retrieved with about 30nm spatial resolution. The transition between two vortex configurations on the two ends of the nanotube with opposite circulation occurs through a domain wall that is aligned at an inclined angle relative to the wire axis. Three-dimensional micromagnetic simulations support the experimental observations and represent a visualization of the curvature-mediated DMI. They also allow a quantitative estimate of the DMI value for the magnetic multilayered nanotube.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

Cold Spray NDE for Porosity and Other Process Anomalies

This paper describes a technology review of non-destructive examination (NDE) methods that can be applied to cold spray coatings. Cold spray is a process for depositing metal powder at high velocity so that it bonds to the substrate metal without significant heating that would be likely to cause additional residual tensile stresses. Coatings in the range from millimeters to centimeters are possible at relatively high deposition rates. Cold spray coatings that may be used for hydroelectric components that are subject to erosion, corrosion, wear, and cavitation damage are of interest. The topic of cold spray NDE is treated generally however and may be considered applicable to virtually any cold spray application except where there are constraints of the hydroelectric component application that bear special consideration. Hydroelectric turbine components are primarily made from low carbon and austenitic stainless steels. They are typically very large components that are partially assembled on-site. Transport of these components within the hydroelectric facility and away from the hydroelectric facility is challenging due to the component’s size and weight, high cost of disassembly, and the confined space of the dam. One method for prolonging component life is application of cold spray and thermal powder metal coatings to the components most susceptible to erosion, corrosion, cracking, and mechanical wear. Process controls and visual inspections have historically been applied to cold spray application; however, quantitative NDE could detect anomalies not readily apparent from such a visual examination. Optical profilometry, Eddy current, ultrasound, and hardness tests are shown for one set of good, fair, and poor Nickle-Chrome (NiCr) on 304 stainless steel (304SS) cold spray samples to demonstrate inspection possibilities. The primary indicator of cold spray quality is the cold spray porosity that is most directly measured with witness-sample destructive examinations (DE) – mostly photo-micrographs. These DE generated porosity values are correlated with optical profilometry, eddy current, ultrasound, and hardness test NDE methods to infer the porosity and other Information of interest. These parameters of interest primarily include: • Porosity primarily caused by improper process conditions (temperature, gas velocity, spray standoff, spray angle, powder size, condition, surface cleanliness, surface oxide, etc.). • Presence/absence of the cold spray coating including possible over-sprayed voids • Coating thickness Optical profilometry measurements of surface roughness trended with porosity plus if compared with a reference measurement or reference drawing would provide information on the coating thickness. Ultrasound could provide similar surface profile information plus attenuation measurements trended with porosity. The ultrasound measurements however may be limited to geometries where the substrate back-wall is normal to the cold spray surface and not too thick. Eddy current showed a strong correlation with porosity. Eddy currents can also be sensitive to cracks and do not need fluid coupling to make measurements. Eddy currents however are not sensitive to coating thicknesses in most cases. Vickers hardness measurements also tracked well with porosity. These types of hardness measurements however are also not sensitive to coating thickness. An NDE program may include multiple measurements. Acknowledgement: This work is sponsored by Bonneville Power Administration (BPA) under their technology innovation project program. Such support does not constitute BPA endorsement of views expressed in this work.

Glass, Samuel W.↗
DOE OSTI2015

Toward 2D and 3D imaging of magnetic nanoparticles using EPR measurements

Purpose: Magnetic nanoparticles (MNPs) are an important asset in many biomedical applications. An effective working of these applications requires an accurate knowledge of the spatial MNP distribution. A promising, noninvasive, and sensitive technique to visualize MNP distributions in vivo is electron paramagnetic resonance (EPR). Currently only 1D MNP distributions can be reconstructed. In this paper, the authors propose extending 1D EPR toward 2D and 3D using computer simulations to allow accurate imaging of MNP distributions. Methods: To find the MNP distribution belonging to EPR measurements, an inverse problem needs to be solved. The solution of this inverse problem highly depends on the stability of the inverse problem. The authors adapt 1D EPR imaging to realize the imaging of multidimensional MNP distributions. Furthermore, the authors introduce partial volume excitation in which only parts of the volume are imaged to increase stability of the inverse solution and to speed up the measurements. The authors simulate EPR measurements of different 2D and 3D MNP distributions and solve the inverse problem. The stability is evaluated by calculating the condition measure and by comparing the actual MNP distribution to the reconstructed MNP distribution. Based on these simulations, the authors define requirements for the EPR system to cope with the added dimensions. Moreover, the authors investigate how EPR measurements should be conducted to improve the stability of the associated inverse problem and to increase reconstruction quality. Results: The approach used in 1D EPR can only be employed for the reconstruction of small volumes in 2D and 3D EPRs due to numerical instability of the inverse solution. The authors performed EPR measurements of increasing cylindrical volumes and evaluated the condition measure. This showed that a reduction of the inherent symmetry in the EPR methodology is necessary. By reducing the symmetry of the EPR setup, quantitative images of larger volumes can be obtained. The authors found that, by selectively exciting parts of the volume, the authors could increase the reconstruction quality even further while reducing the amount of measurements. Additionally, the inverse solution of this activation method degrades slower for increasing volumes. Finally, the methodology was applied to noisy EPR measurements: using the reduced EPR setup’s symmetry and the partial activation method, an increase in reconstruction quality of ≈80% can be seen with a speedup of the measurements with 10%. Conclusions: Applying the aforementioned requirements to the EPR setup and stabilizing the EPR measurements showed a tremendous increase in noise robustness, thereby making EPR a valuable method for quantitative imaging of multidimensional MNP distributions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-R-42: Association of Radiomic and Metabolic Tumor Volumes in Radiation Treatment of Glioblastoma Multiforme

Purpose: High-throughput extraction of imaging and metabolomic quantitative features from MRI and MR Spectroscopy Imaging (MRSI) of Glioblastoma Multiforme (GBM) results in tens of variables per patient. In radiotherapy (RT) of GBM, the relevant metabolic tumor volumes (MTVs) are related to aberrant levels of N-acetyl Aspartate (NAA) and Choline (Cho). Corresponding Clinical Target Volumes (CTVs) for RT planning are based on Contrast Enhancing T1-weighted MRI (CE-T1w) and T2-weighted/Fluid Attenuated Inversion Recovery (FLAIR) MRI. The objective is to build a framework for investigation of associations between imaging, CTV, and MTV features better understanding of the underlying information in the CTVs and dependencies between these volumes. Methods: Necrotic portions, enhancing lesion and edema were manually contoured on T1w/T2w images for 17 GBM patients. CTVs and MTVs for NAA (MTV{sub NAA}) and Cho (MTV{sub Cho}) were constructed. Tumors were scored categorically for ten semantic imaging traits by neuroradiologist. All features were investigated for redundancy. Two-way correlations between imaging and RT/MTV features were visualized as heat maps. Associations between MTV{sub NAA}, MTV{sub Cho} and imaging features were studied using Spearman correlation. Results: 39 imaging features were computed per patient. Half of the imaging traits were replaced with automatically extracted continuous variables. 21 features were extracted from MTVs/CTVs. There were a high number (43) of significant correlations of imaging with CTVs/MTV{sub NAA} while very few (10) significant correlations were with CTVs/MTV{sub Cho}. MTV{sub NAA} was found to be closely associated with MRI volumes, MTV{sub Cho} remains elusive for characterization with imaging. Conclusion: A framework for investigation of co-dependency between MRI and RT/metabolic features is established. A series of semantic imaging traits were replaced with automatically extracted continuous variables. The approach will allow for exploration of relationships between sizes and intersection of imaging features of tumors, RT volumes, metabolite concentrations and comparing those to therapy outcome, quality of life evaluation and overall survival rate. This publication was supported by Grant 10BN03 from Bankhead Coley Cancer Research Program, R01EB000822, R01EB016064, and R01CA172210 from the National Institutes of Health, and Indo-US Science & Technology Forum award #20-2009. Bhaswati Roy received financial assistance from University Grant Commission, New Delhi, India.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

FIRM image analysis: A machine learning workflow for quantifying extracellular matrix components from electron microscopy images

The extracellular matrix (ECM) is a complex network of biomolecules that plays an integral role in the structure, processes, and signaling mechanisms of cells and tissues. Identifying and quantifying changes in these matrix components provides insight into the mechanisms behind specific tissue remodeling processes; however, quantifying these changes is challenging due to difficult imaging conditions, complexity of the ECM, and the subtlety of these changes. Current imaging techniques allow us to visualize these critical remodeling events and developments in image analysis have employed a combination of analysis software and machine learning techniques to improve the efficiency and accuracy with which features are measured. Although image analysis has seen much improvement in recent years, there has been no technique developed to address ambiguity in feature edges in electron microscopy images. Presented here is a new machine learning-based workflow for the analysis of microscopy images named FIRM (Feature Identification from Raw Microscopy) that uses a random forest classifier to identify ECM features of interest and generate binary segmentation masks for quantification with ImageJ-FIJI. FIRM performed with an F1 score of 0.794 and greater than 80% accuracy for number and size of features detected. FIRM had similar deviation from the ground truth in the number of identified fibrils, fibril size, and size distributions when compared to human analyses. The results suggest that FIRM performs as well as manual analysis and requires a fraction of the time. This analysis technique is more efficient, eliminates user bias, and can be easily optimized to identify a variety of features, making it useful for any discipline requiring image analysis.

Science & Technology - Other Topics↗
DOE OSTI2023

Analysis of Tank 38h (HTF-38-23-19, -20) and Tank 43H (HTF-43-23-21, -22) Samples for Support of the Enrichment Control and Corrosion Control Programs

SRNL analyzed samples from Tank 38H and Tank 43H to support ECP and CCP. The results indicate the concentrations of most soluble species in the Tank 38H surface sample decreased significantly from the previous surface sample. The Tank 38H sub-surface sample shows changes in concentration for soluble species in the solution with some increasing and some decreasing. The current Thank 38H sub-surface sample contains visible sludge solids similar to the previous sample, i.e., less than 1%, based on visual appearance. The significant differences in the concentrations of major components between the Tank 38H surface and sub-surface samples indicate significant stratification of solution species between these two locations within the tank. Savannah River Mission Completion personnel indicate that ~ 150,000 gallons of Tank 22 supernate were received in Tank 38H since its last analysis during which time the 2H evaporator was not operated, so the observed stratification is expected. The Tank 43H surface and sub-surface samples are similar in composition to the previous samples. The similar solution compositions measured in the Tank 43H surface and sub-surface samples indicate a minimal stratification within the tank. The total uranium and plutonium in the current Tank 38H surface sample remains similar to the previous analysis. The Tank 38H sub-surface sample shows an increase in uranium and plutonium concentrations compared to the previous sample likely because of an increase in sludge solids in the current sample. The total uranium concentration in the Tank 43H surface sample is similar to the previous sample results while the plutonium in the Tank 43H sub-surface sample increased relative to the previous analysis. The sum of the major cations versus the sum of the major anions shows a difference of <10% for both samples from Tank 38H sub-surface sample (174 mg/L) increased compared with the previous sample. The Tank 38H surface sample silicon concentrations (27.5 mg/L) is one-half of the previous sample results. The Tank 43H surface sample silicon concentrations compared to the previous sample results indicate Si in the concentration range of 60 to 83 mg/L. Thus, these current samples analyzed from Tanks 38H and 43H show overall silicon concentrations ranging from 27.5 to 174 mg/L.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Properties of polycyclic aromatic hydrocarbons in the northwest photon dominated region of NGC 7023. II. Traditional PAH analysis using k-means as a visualization tool

Polycyclic aromatic hydrocarbon (PAH) emission in the Spitzer-IRS spectral map of the northwest photon dominated region (PDR) in NGC 7023 is analyzed using the 'traditional' approach in which the PAH bands and plateaus between 5.2-19.5 μm are isolated by subtracting the underlying continuum and removing H{sub 2} emission lines. The spectra are organized into seven spectroscopic bins by using k-means clustering. Each cluster corresponds to, and reveals, a morphological zone within NGC 7023. The zones self-organize parallel to the well-defined PDR front that coincides with an increase in intensity of the H{sub 2} emission lines. PAH band profiles and integrated strengths are measured, classified, and mapped. The morphological zones revealed by the k-means clustering provides deeper insight into the conditions that drive variations in band strength ratios and evolution of the PAH population that otherwise would be lost. For example, certain band-band relations are bifurcated, revealing two limiting cases; one associated with the PDR, the other with the diffuse medium. Traditionally, PAH band strength ratios are used to gain insight into the properties of the emitting PAH population, i.e., charge, size, structure, and composition. Insights inferred from this work are compared and contrasted to those from Boersma et al. (first paper in this series), where the PAH emission in NGC 7023 is decomposed exclusively using the PAH spectra and tools made available through the NASA Ames PAH IR Spectroscopic Database.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Achieving Stable Molybdenum Oxide Cathodes for Aqueous Zinc‐Ion Batteries in Water‐in‐Salt Electrolyte

Abstract Layered MoO 3 represents a promising cathode for aqueous rechargeable Zn‐ion batteries, but the implementation of this material is limited due to the low conductivity and poor structural stability. A 30 m ZnCl 2 water‐in‐salt electrolyte (WISE) is introduced to a MoO 3 nanobelt cathode for the first time, significantly increasing the stability of MoO 3 cathodes compared to those in 3 m ZnSO 4 and 3 m ZnCl 2 . The Zn/MoO 3 cell in WISE unambiguously demonstrate significantly improved rate performance delivering 349, 253, and 222 mAh g −1 at 100, 500, and 1000 mA g −1 , denoting a 12× capacity increase of those achieved in 3 m electrolytes at 1000 mA g −1 . A capacity retention rate of 73% is achieved after (dis)charging at 100 mA g −1 for 100 cycles, and no obvious capacity fading is observed at higher current densities of 500 mA g −1 and 2 A g −1 . Specifically, the data suggest that the drastic fading in 3 m electrolytes can be attributed to the parasitic surface deposits on Zn originated from Mo dissolution and H 2 formation due to Zn corrosion and hydrogen evolution reaction, which are significantly suppressed in the WISE. The direct visualization of these side reactions is achieved for the first time in the Zn‐MoO 3 system, using an in situ optoelectrochemical measurement.

Wang, Lei↗
DOE OSTI2013

A low dose simulation tool for CT systems with energy integrating detectors

Purpose: This paper introduces a new strategy for simulating low-dose computed tomography (CT) scans using real scans of a higher dose as an input. The tool is verified against simulations and real scans and compared to other approaches found in the literature. Methods: The conditional variance identity is used to properly account for the variance of the input high-dose data, and a formula is derived for generating a new Poisson noise realization which has the same mean and variance as the true low-dose data. The authors also derive a formula for the inclusion of real samples of detector noise, properly scaled according to the level of the simulated x-ray signals. Results: The proposed method is shown to match real scans in number of experiments. Noise standard deviation measurements in simulated low-dose reconstructions of a 35 cm water phantom match real scans in a range from 500 to 10 mA with less than 5% error. Mean and variance of individual detector channels are shown to match closely across the detector array. Finally, the visual appearance of noise and streak artifacts is shown to match in real scans even under conditions of photon-starvation (with tube currents as low as 10 and 80 mA). Additionally, the proposed method is shown to be more accurate than previous approaches (1) in achieving the correct mean and variance in reconstructed images from pure-Poisson noise simulations (with no detector noise) under photon-starvation conditions, and (2) in simulating the correct noise level and detector noise artifacts in real low-dose scans. Conclusions: The proposed method can accurately simulate low-dose CT data starting from high-dose data, including effects from photon starvation and detector noise. This is potentially a very useful tool in helping to determine minimum dose requirements for a wide range of clinical protocols and advanced reconstruction algorithms.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Shallow cumuli cover and its uncertainties from ground-based lidar–radar data and sky images

Cloud cover estimates of single-layer shallow cumuli obtained from narrow field-of-view (FOV) lidar–radar and wide-FOV total sky imager (TSI) data are compared over an extended period (2000–2017 summers) at the established United States Atmospheric Radiation Measurement mid-continental Southern Great Plains site. We quantify the impacts of two factors on hourly and sub-hourly cloud cover estimates: (1) instrument-dependent cloud detection and data merging criteria and (2) FOV configuration. Enhanced observations at this site combine the advantages of the ceilometer, micropulse lidar (MPL) and cloud radar in merged data products. Data collected by these three instruments are used to calculate narrow-FOV cloud fraction (CF) as a temporal fraction of cloudy returns within a given period. Sky images provided by TSI are used to calculate the wide-FOV fractional sky cover (FSC) as a fraction of cloudy pixels within a given image. To assess the impact of the first factor on CF obtained from the merged data products, we consider two additional subperiods (2000–2010 and 2011–2017 summers) that mark significant instrumentation and algorithmic advances in the cloud detection and data merging. We demonstrate that CF obtained from ceilometer data alone and FSC obtained from sky images provide the most similar and consistent cloud cover estimates; hourly bias and root-mean-square difference (RMSD) are within 0.04 and 0.12, respectively. However, CF from merged MPL–ceilometer data provides the largest estimates of the multiyear mean cloud cover, about 0.12 (35 %) and 0.08 (24 %) greater than FSC for the first and second subperiods, respectively. CF from merged ceilometer–MPL–radar data has the strongest subperiod dependence with a bias of 0.08 (24 %) compared to FSC for the first subperiod and shows no bias for the second subperiod. The strong period dependence of CF obtained from the combined ceilometer–MPL–radar data is likely results from a change in what sensors are relied on to detect clouds below 3 km. After 2011, the MPL stopped being used for cloud top height detection below 3 km, leaving the radar as the only sensor used in cloud top height retrievals. To quantify the FOV impact, a narrow-FOV FSC is derived from the TSI images. We demonstrate that FOV configuration does not modify the bias but impacts the RMSD (0.1 hourly, 0.15 sub-hourly). In particular, the FOV impact is significant for sub-hourly observations, where 41 % of narrow- and wide-FOV FSC differ by more than 0.1. A new “quick-look” tool is introduced to visualize impacts of these two factors through integration of CF and FSC data with novel TSI-based images of the spatial variability in cloud cover. The influence of cloud field organization, such cloud streets parallel to the wind direction, on narrow- and wide-FOV cloud cover estimates can be visually assessed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Two-Dimensional Siloxene Nanosheets: Impact of Morphology and Purity on Electrochemistry

Two-dimensional (2D) siloxene (Si 6 O 3 H 6 ) has shown promise as a negative electrode material for Li-ion batteries due to its high gravimetric capacity and superior mechanical properties under (de)lithiation compared to bulk Si. Here, in this work, we prepare purified siloxene nanosheets through the removal of bulk Si contaminants, use ultrasonication to control the lateral size and thickness of the nanosheets, and probe the effects of the resulting morphology and purity on the electrochemistry. The thin siloxene nanosheets formed after 4 h of ultrasonication deliver an average capacity of 810 mA h/g under a 1000 mA/g rate over 200 cycles with a capacity retention of 76%. Interestingly, the purified siloxene shows lower initial capacity but superior capacity retention over extended cycling. The 2D morphology benefit is illustrated where the parent siloxene nanosheet morphology and structure were largely maintained based on operando optoelectrochemistry, in situ Raman, ex situ scanning electron microscopy, and ex situ transmission electron microscopy. Furthermore, the purified siloxene-based electrode free from crystalline Si impurity experiences the least expansion upon (de)lithiation as visualized by cross-section electron microscopy of samples recovered post-cycling.

25 ENERGY STORAGE↗
DOE OSTI2013

PRECIOUS METALS IN SDSS QUASAR SPECTRA. I. TRACKING THE EVOLUTION OF STRONG, 1.5 < z < 4.5 C IV ABSORBERS WITH THOUSANDS OF SYSTEMS

We have vastly increased the C IV statistics at intermediate redshift by surveying the thousands of quasars in the Sloan Digital Sky Survey (SDSS) Data-Release 7. We visually verified over 16,000 C IV systems with 1.46 < z < 4.55-a sample size that renders Poisson error negligible. Detailed Monte Carlo simulations show that we are approximately 50% complete down to rest equivalent widths W {sub r} Almost-Equal-To 0.6 A. We analyzed the sample as a whole and in 10 small redshift bins with approximately 1500 doublets each. The equivalent width frequency distributions f(W {sub r}) were well modeled by an exponential, with little evolution in shape. In contrast with previous studies that modeled the frequency distribution as a single power law, the fitted exponential gives a finite mass density for the C IV ions. The comoving line density dN{sub CIV}/dX evolved smoothly with redshift, increasing by a factor of 2.37 {+-} 0.09 from z = 4.55-1.96, then plateauing at dN{sub CIV}/dX{approx}0.34 for z = 1.96-1.46. Comparing our SDSS sample with z < 1 (ultraviolet) and z > 5 (infrared) surveys, we see an approximately 10-fold increase in dN{sub CIV}/dX over z Almost-Equal-To 6 {yields} 0, for W {sub r} {>=} 0.6 A. This suggests a monotonic and significant increase in the enrichment of gas outside galaxies over the 12 Gyr lifetime of the universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Charge Localization after Ultrafast Photoexcitation of a Rigid Perylene Perylenediimide Dyad Visualized by Transient Stark Effect

The intramolecular charge transfer (CT) dynamics of a rigid and strongly conjugated perylenediimide-bridge-perylene dyad (PDIPe) has been explored in dichloromethane using ultrafast transient electronic absorption spectroscopy and quantum chemical calculations. The strong electronic coupling between the dyad units gives rise to a CT band. Its photoexcitation forms a delocalized CT state with well-preserved ion bands despite the strong coupling. In the dyad, the electronic transition dipole moment of the electron donor perylene is aligned along the axis of the electric field vector with respect to the CT species. This alignment makes the donor sensitive to the Stark effect and thus charge density fluctuations in the CT state. Charge localization on the picosecond time scale manifests as a time-dependent Stark shift in the visible region. Quantum chemical calculations reveal a twist around the acetylene bridging unit to be the responsible mechanism generating a partial to an almost complete CT state. An estimate of the electric field strength in the CT state yields approximately 25 MV/cm, which increases to around 31 MV/cm during charge localization. Additionally, the calculations illustrate the complexity of electronic structure in this strongly delocalized superchromophore and reflect the complications in the interpretation of transient absorption results when compared to steady-state approaches such as spectroelectrochemistry and model chromophore experiments such as photoinduced bimolecular charge transfer.

14 SOLAR ENERGY↗
DOE OSTI2023

Star cluster classification using deep transfer learning with PHANGS- HST

Currently available star cluster catalogues from the Hubble Space Telescope (HST) imaging of nearby galaxies heavily rely on visual inspection and classification of candidate clusters. Here, the time-consuming nature of this process has limited the production of reliable catalogues and thus also post-observation analysis. To address this problem, deep transfer learning has recently been used to create neural network models that accurately classify star cluster morphologies at production scale for nearby spiral galaxies (D ≲ 20 Mpc). Here, we use HST ultraviolet (UV)–optical imaging of over 20 000 sources in 23 galaxies from the Physics at High Angular resolution in Nearby GalaxieS (PHANGS) survey to train and evaluate two new sets of models: (i) distance-dependent models, based on cluster candidates binned by galaxy distance (9–12, 14–18, and 18–24 Mpc), and (ii) distance-independent models, based on the combined sample of candidates from all galaxies. We find that the overall accuracy of both sets of models is comparable to previous automated star cluster classification studies (~60–80 per cent) and shows improvement by a factor of 2 in classifying asymmetric and multipeaked clusters from PHANGS-HST. Somewhat surprisingly, while we observe a weak negative correlation between model accuracy and galactic distance, we find that training separate models for the three distance bins does not significantly improve classification accuracy. We also evaluate model accuracy as a function of cluster properties such as brightness, colour, and spectral energy distribution (SED)-fit age. Based on the success of these experiments, our models will provide classifications for the full set of PHANGS-HST candidate clusters (N ~ 200 000) for public release.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Blockchain based Communication Architectures with Applications to Private Security Networks

Existing communication protocols in high consequence security networks are highly centralized. While this naively makes the controls easier to physically secure, external actors require fewer resources to disrupt the system because there are fewer points in the system can be destroyed or interrupted without the entire system failing. We present a solution to this problem using a proof-of-work-based blockchain implementation built on MultiChain. We construct a test-bed network containing two types of data input: visual imagers and microwave sensor information. These data types are ubiquitous in perimeter intrusion detection security systems and allow a realistic representation of a real-world network architecture. The cameras in this system use an object detection algorithm to nd important targets in the scene. The raw data from the camera and the outputs from the detection algorithm are then placed in a transaction on the distributed ledger. Similarly, microwave data is used to detect relevant events and are placed in a transaction. These transactions are then bundled into blocks and broadcast to the rest of the network using the Bitcoin-based MultiChain protocol. We develop five tests to examine the security metrics of our network. We performed the five security metric test using different sized networks from 7 to 39 nodes to determine how the metrics scale with respect to size. We nd that when compared to a centralized architecture our implementation provides a resiliency increase that is expected from a blockchain-based protocol without slowing the system so much that a human operator would notice. Furthermore, our approach is able to detect tampering in real time. Based on these results, we theorize that security networks in general could use a blockchain-based approach in a meaningful way.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

High-Precision Characterization of Seismicity from the 2022 Hunga Tonga-Hunga Ha'apai Volcanic Eruption

The earthquake swarm accompanying the January 2022 Hunga Tonga-Hunga Ha'apai (HTHH) volcanic eruption includes a large number of posteruptive moderate-magnitude seismic events and presents a unique opportunity to use remote monitoring methods to characterize and compare seismic activity with other historical caldera-forming eruptions. We compute improved epicentroid locations, magnitudes, and regional moment tensors of seismic events from this earthquake swarm using regional to teleseismic surface-wave cross correlation and waveform modeling. Precise relative locations of 91 seismic events derived from 59,047 intermediate-period Rayleigh- and Love-wave cross-correlation measurements collapse into a small area surrounding the volcano and exhibit a southeastern time-dependent migration. Regional moment tensors and observed waveforms indicate that these events have a similar mechanism and exhibit a strong positive compensated linear vector dipole component. Precise relative magnitudes agree with regional moment tensor moment magnitude ($M_w$) estimates while also showing that event sizes and frequency increase during the days after the eruption followed by a period of several weeks of less frequent seismicity of a similar size. The combined information from visual observation and early geologic models indicate that the observed seismicity may be the result of a complex series of events that occurred after the explosive eruption on 15 January, possibly involving rapid resupply of the magma chamber shortly after the eruption and additional faulting and instability in the following weeks. In addition, we identify and characterize an $M_w$ 4.5 event five days before the paroxysmal explosion on 15 January, indicating that additional seismic events preceding the main eruption could have been identified with improved local monitoring. As a result, our analysis of the HTHH eruption sequence demonstrates the value of potentially utilizing teleseismic surface-wave cross correlation and waveform modeling methods to assist in the detailed analysis of remote volcanic eruption sequences.

58 GEOSCIENCES↗
DOE OSTI2023

Multi-Task Learning of Scanning Electron Microscopy and Synthetic Thermal Tomography Images for Detection of Defects in Additively Manufactured Metals

One of the key challenges in laser powder bed fusion (LPBF) additive manufacturing of metals is the appearance of microscopic pores in 3D-printed metallic structures. Quality control in LPBF can be accomplished with non-destructive imaging of the actual 3D-printed structures. Thermal tomography (TT) is a promising non-contact, non-destructive imaging method, which allows for the visualization of subsurface defects in arbitrary-sized metallic structures. However, because imaging is based on heat diffusion, TT images suffer from blurring, which increases with depth. We have been investigating the enhancement of TT imaging capability using machine learning. In this work, we introduce a novel multi-task learning (MTL) approach, which simultaneously performs the classification of synthetic TT images, and segmentation of experimental scanning electron microscopy (SEM) images. Synthetic TT images are obtained from computer simulations of metallic structures with subsurface elliptical-shaped defects, while experimental SEM images are obtained from imaging of LPBF-printed stainless-steel coupons. MTL network is implemented as a shared U-net encoder between the classification and the segmentation tasks. Results of this study show that the MTL network performs better in both the classification of synthetic TT images and the segmentation of SEM images tasks, as compared to the conventional approach when the individual tasks are performed independently of each other.

36 MATERIALS SCIENCE↗