ImagingSIMS/ImagingSIMS
ImagingSIMS is an open-source project for loading, analyzing, and visualizing secondary ion mass spectrometry (SIMS) data.
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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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ImagingSIMS is an open-source project for loading, analyzing, and visualizing secondary ion mass spectrometry (SIMS) data.
DM-Sim: Quantum Simulator on GPU Cluster using Density Matrix: a new simulation approach that significantly reduces communication overhead.
Spectral emissivity control is paramount for designing a high-efficiency selective emitter surface required for thermophotovoltaic (TPV) applications. Owing to the temperature dependency of materials optical constants, the spectral properties of a selective emitter surface changes with the emitter temperature. This paper presents the fabrication of a multilayer metal-dielectric ( ${\rm Si}_{3}{\rm N}_{4}/\rm W/Si_{3}{\rm N_{4}}$ ) coated tungsten selective emitter aimed for GaSb-based TPV systems and studies the dependence of its surface spectral emissivity, $\varepsilon (\lambda)$ , upon a temperature ranging from 300 K to 1500 K. Both the simulation and experimental methods were used to characterize $\varepsilon (\lambda)$ as a function of temperature. For wavelengths less than 1.4 µm, $\varepsilon (\lambda)$ was found to have a minimal dependence on temperature. Beyond 1.4 µm, $\varepsilon (\lambda)$ increases with the temperature. At 1.55 µm, the simulation and experimental data estimated a ${\sim}{{4}}\%$ greater emissivity at 1500 K than at room temperature. At 1500 K, the increased $\varepsilon (\lambda)$ at longer wavelengths lowered the spectral conversion efficiency of the selective emitter from 58% to 47%. The output power density, sub-bandgap loss, and TPV conversion efficiency ( ${\eta _{\rm TPV}}$ ) for a GaSb cell illuminated by the selective thermal emitter at 1500 K were estimated. ${\eta _{\rm TPV}}$ drops from 13.7% to 11% due to the increased sub-bandgap emission at 1500 K. Essential approaches for mitigating the sub-bandgap losses to further improve ${\eta _{\rm TPV}}$ are also discussed.
Interfaces play a critical role in the properties and lifetime of current generation and advanced batteries. However, detailed characterization of the critical interfaces during battery operation which can enable performance improvements and improved design has been a significant challenge requiring innovative technique development and creative experiments. This paper describes ways that information from a range of microscopy, spectroscopy, and spectrometry tools can be used to address important challenges associated with energy storage science and technology, in particular the development of advanced batteries for consumer use, transportation, , and renewable storage. Expanding the types of measurements that can be made on operational model batteries has significantly expanded the type and quality of information that can be obtained. This paper first shows examples of approaches being used to collect in situ transmission electron microscopy (TEM), secondary ion mass spectrometry (SIMS) and x-ray photoelectron spectroscopy data. The final section of the paper briefly shows two examples: the use of in situ XPS to examine SEI layers and a variety of methods including scanning TEM, atom probe tomography, scanning transmission x-ray microscopy (STXM), and x-ray adsorption near edge spectroscopy to understanding improve the performance of layered lithium transition metal oxide (LTMO) cathodes .
Abstract We propose an on-chip gyroscope based on nonlinear multiresonant optics in a thin film χ (2) resonator that combines high sensitivity, compact form factor, and low power consumption simultaneously. We theoretically analyze a novel holistic metric – Fisher Information capacity of a multiresonant nonlinear photonic cavity – to fully characterize the sensitivity of our gyroscope under fundamental quantum noise conditions. Leveraging Bayesian optimization techniques, we directly maximize the nonlinear multiresonant Fisher Information. Our holistic optimization approach orchestrates a harmonious convergence of multiple physical phenomena – including noise squeezing, nonlinear wave mixing, nonlinear critical coupling, and noninertial signals – all encapsulated within a single sensor-resonator, thereby significantly augmenting sensitivity. We show that ∼ 470 × $\sim 470{\times}$ improvement is possible over the shot-noise limited linear gyroscope with the same footprint, intrinsic quality factors, and power budget.
Surrogate nuclear explosion debris (SNED) has emerged as a critical platform for advancing post-detonation nuclear forensic analysis in the absence of readily accessible historic materials. SNED enables controlled investigation and validation of analytical methodologies used to interrogate the chemical, isotopic, radiological, and microstructural signatures preserved in nuclear explosion debris. This review presents an integrated assessment of destructive and non-destructive analytical techniques commonly employed within decision-driven nuclear forensic workflows. Each technique is discussed individually while highlighting how it contributes to different stages of post-detonation analysis. Core methods – including gamma and alpha spectrometry, ICP-MS, TIMS, SIMS, SEM-EDS, XRF, LIBS, vibrational spectroscopy, and X-ray absorption spectroscopy – are critically evaluated with respect to forensic maturity, information content, and matrix limitations. Emphasis is placed on the role of SNED in benchmarking multi-modal workflows and identifying gaps in reproducing heterogeneity, fractionation, and radiation-driven evolution relevant to forensic attribution.
Arsenic and other heavy metal contaminants in water are a significant global health threat. In this study, low-cost, sulfur-free, sustainable, water-insoluble materials with heavy metal remediation properties were produced from renewable resources such as starch, xylan, citric acid, and chitosan. Synthesized starch citrate-chitosan (SCC) foam and xylan citrate-chitosan (XCC) foam were flexible, porous, and elastic. The foams’ arsenic uptake in water was significantly greater than five different commercial metal remediating agents. The mercury and lead uptakes with the synthesized foams were similar to the performance of a commercial sulfur-based product, SorbaTech 450 (ST450). However, the cadmium and selenium uptakes were comparatively lower. The complexation of arsenic with oxygen and nitrogen of the SCC foam was shown with time-of-flight secondary ion mass spectrometry (TOF-SIMS). The XCC foam was also shown to adsorb potassium iodide (KI) at a similar rate to sodium chloride. This may be used to remediate water contaminated with radioactive materials, such as iodine 131.
In order to generate a public data set that can be used to validate Wave Energy Converter (WEC) numerical codes, such as WEC-Sim, Sandia National Laboratories led an experimental testing campaign of a 1:33 scale Floating Oscillating Surge Wave Energy Converter (FOSWEC) in the Directional Wave Basin at Oregon State University's Hinsdale Wave Research Laboratory. Testing was performed in two phases; Phase 1 testing was completed in November - December 2015, and Phase 2 testing was completed in May - June 2016. This experimental testing report details the selection and design of a FOSWEC, experimental setup and tests, and overview of the resulting dataset from Phase 1 and Phase 2 testing.
'Additional Degree of Freedom for WEC' - WEC-Sim numerical model from RFTS 1 TEAMER project. An increase in wave energy converter (WEC) efficiency requires not only consideration of the nonlinear effects in the WEC dynamics and the power take-off (PTO) mechanisms, but also more integrated treatment of the whole system, i.e., the buoy dynamics, the PTO system, and the control strategy. It results in an optimization formulation that has a nonquadratic and nonstandard cost functional. This model presents the application of real-time nonlinear model predictive controller (NMPC) to two degrees of freedom point absorber type WEC with highly nonlinear PTO characteristics. The nonlinear effects, such as the fluid viscous drag, are also included in the plant dynamics. The controller may be implemented on a real-time target machine, and the WEC device is emulated in real-time using the WECSIM toolbox. Please see the ‘ReadMe’ within the root directory for an explanation of how to set-up and run the model. An article covering the development of this model is attached as "Real-Time Nonlinear Model Predictive Controller for Multiple Degrees of Freedom Wave Energy Converters with Non-Ideal Power Take-Off"
Boundary element method (BEM) and WEC-Sim analysis of UMass Dartmouth's maximal asymmetric drag wave energy converter (MADWEC), including its tethered ballast system and PTO (power take-off).
Critical military training and testing on lands along the nation’s coastal and estuarine shorelines are increasingly placed at risk because of encroachment pressures in surrounding areas, impairments due to other anthropogenic disturbances, and changes in climate and sea level. The U.S. Department of Defense (DoD) intends to enhance and sustain its training and testing assets and also optimize its stewardship of natural resources through the development and application of an ecosystem-based management approach on DoD installations. To accomplish this goal, particularly for installations in estuarine/coastal environments, the Strategic Environmental Research and Development Program (SERDP) launched the Defense Coastal/Estuarine Research Program (DCERP) as a 10-year effort at Marine Corps Base Camp Lejeune (MCBCL) in North Carolina. The results of the second 5 years of the program (DCERP2) are presented in the DCERP2 Final Report.There were four overarching objectives of DCERP2. The first objective was to understand the effects of climate change impacts, including warming temperatures, variability in the hydrological cycle, storm events, and sea level rise on the coastal ecosystems at MCBCL from observations and measurements made over the 10-year program. The second objective was to understand the carbon cycle of the coastal and terrestrial ecosystems at MCBCL through a highly integrated sampling program. The third objective was to develop models, tools, and indicators to evaluate current and projected future ecosystem state changes and translate scientific findings into actionable information for installation managers. The last objective was to recommend adaptive management strategies to sustain ecosystem natural resources within the context of an active military installation.This data package contains the files needed to run MCBCL simulations using the state-and-transition simulation model (ST-Sim) software to simulate longleaf pine landscape.
The radiation-induced volumetric expansion (RIVE) of aggregate-forming minerals causes damage in concrete exposed to high levels of fast neutrons fluence ( \(>\,\sim \,10^{19}\, \hbox {n}\,\hbox {cm}^{-2}\) at kinetics energy above 0.1 MeV). Historical post-irradiation RIVE and Young’s modulus data obtained in test reactors were revisited using a polycrystalline homogenization model (self-consistent scheme) accounting for the aggregates’ minerals content and the formation of voids/cracks during irradiation. It was found that the formation of extra voids/cracks can contribute to the aggregate expansion more substantially than the cumulated expansions of aggregate-forming minerals. Furthermore, the rate of void creation appears to be inversely correlated to the silica content, although aggregates of higher silicate contents exhibit higher RIVEs. The loss of Young’s modulus decreases exponentially with the aggregates’ expansion. At a comparable RIVE level, the relative loss of modulus is more significant in aggregates of higher silica content.
The paper presents results from the Collaborative Computational Project in Wave Structure Interaction (CCP-WSI) Blind Test Series 2. Without prior access to the physical data, participants, with numerical methods ranging from low-fidelity linear models to fully non-linear Navier-Stokes (NS) solvers, simulate the interaction between focused wave events and two separate, taut-moored, floating structures: a hemispherical-bottomed cylinder and a cylinder with a moonpool. The ‘blind’ numerical predictions for heave, surge, pitch and mooring load, are compared against physical measurements. Dynamic time warping is used to quantify the predictive capability of participating methods. In general, NS solvers and hybrid methods give more accurate predictions; however, heave amplitude is predicted reasonably well by all methods; and a WEC-Sim implementation, with CFD-informed viscous terms, demonstrates comparable predictive capability to even the stronger NS solvers. Large variations in the solutions are observed (even among similar methods), highlighting a need for standardisation in the numerical modelling of WSI problems.
Cumulative Spatial Impact Layers™ (CSIL) is a GIS-based tool that summarizes spatio-temporal datasets based on overlapping features and attributes. Applying a recursive quadtree method and multiple additive frameworks, the CSIL tool allows users to analyze raster and vector datasets simultaneously by calculating data, record, or attribute density. The CSIL tool was designed based on the original approach (Bauer et al. 2015) and more information on the tool overall along with applications can be found in Romeo et al. 2019). Providing an efficient summary of disparate geospatial data, CSIL bridges the gap between understanding data and analysis. Bauer, J. R., Nelson, J., Romeo, L., Eynard, J., Sim, L., Halama, J., Rose, K., & Graham, J. (2015). A spatio-temporal approach to analyze broad risks and potential impacts associated with uncontrolled hydrocarbon release events in the offshore Gulf of Mexico (NETL-TRS-2-2015 EPAct Technical Report Series). U.S. Department of Energy, National Energy Technology Laboratory: Morgantown, WV; p 60. Romeo, L., Nelson, J., Wingo, P., Bauer, J., Justman, D., & Rose, K. (2019). Cumulative spatial impact layers: A novel multivariate spatio-temporal analytical summarization tool. Transactions in GIS.
Recent developments of the ERL-based design of future high-luminosity electron-hadron collider eRHIC focused on balancing technological risks present in the design versus the design cost. As a result a lower risk design has been adopted at moderate cost increase. The modifications include a change of the main linac RF frequency, reduced number of SRF cavity types and modified electron spin transport using a spin rotator. A luminosity-staged approach is being explored with a Nominal design ($L \sim 10^{33} {\rm cm}^2 {\rm s}^{-1}$) that employs reduced electron current and could possibly be based on classical electron cooling, and then with the Ultimate design ($L \gt 10^{34} {\rm cm}^{-2} {\rm s}^{-1}$) that uses higher electron current and an innovative cooling technique (CeC). The paper describes the recent design modifications, and presents the full status of the eRHIC ERL-based design.
Nb3Sn is a potential candidate for surface material of SRF cavities since it can enable the cavity to operate at higher temperatures with high quality factor and at an increased accelerating gradient. Nb-Sn films were deposited using magnetron sputtering of individual Nb and Sn targets onto Nb and sapphire substrates. The as-deposited films were annealed at 1200 °C for 3 hours. The films were characterized for their structure by X-ray Diffraction (XRD), morphology by Field Emission Scanning Electron Microscopy (FESEM), and composition by Energy Dispersive X-ray Spectroscopy (EDS) and Time of Flight Secondary Ion Mass Spectrometry (ToF-SIMS). The surface resistivity was measured down to cryogenic temperature to determine the superconducting transition temperature and its width. The composition of the multilayered films was controlled by varying the thickness of the Nb and Sn layers. The films showed crystalline Nb3Sn phases with Tc up to 17.6 K.
In this study we present new insight on low temperature nitrogen infusion on bulk niobium superconducting radio-frequency (SRF) cavities. Nitrogen infusion is a thermal treatment recently discovered at Fermilab that allows to reach high accelerating gradients, of the order of 45MV/m, with high Q-factors, of the order of 2 · 10¹⁰. Detailed depth dependent RF studies (by means of subsequent HF rinses) and comparisonwith SIMS results pinpointed interstitial nitrogen as the responsible for the improved performance and uncovered the extension of its profile inside the material.
Over the last several years, alloying of the surface layer of niobium SRF cavities has been demonstrated to beneficially lower the superconducting RF surface resistance. Nitrogen, titanium, and oxygen have all been demonstrated as effective alloying agents, occupying interstitial sites in the niobium lattice within the RF penetration depth and even deeper, when allowed to thermally diffuse into the surface at appropriate temperatures. The use of nitrogen for this function has been often termed ’nitrogen doping’ and is being applied in the LCLS-II and LCLS-II HE projects. We report characterization studies of the distribution of nitrogen into the exposed niobium surface and how such distribution is affected by the quality of the vacuum furnace environment in which the doping takes place, and the complexity of nitride crystal growth on different grain orientations of surface niobium. Using state-of-the-art quantification methods by dynamic secondary ion mass spectrometry (SIMS) depth profiling in niobium, we identify several phenomena involving furnace-sourced contamination. We also highlight a potential issue with N₂ flow constraints from the flange ’caps’ used during heat treatments.