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Multilayer film coating for laser ion source target for increase of low charge state production
The use of Laser Ion Source for accelerator facilities has the advantage to tune the characteristic of the produced beams by changing the laser parameters using the same primary target. The advantageous and innovative opportunity to manipulate the characteristic of charge state distributions by the use of composed target, may open new possibilities for the ion sources. In this experiment we characterize and study the plasma produced by the laser ablation of coated targets at constant laser parameters. The performed investigation has the double purpose to have a better understanding of penetration depth of laser in composed materials and understand how to tune the charge states by adding coating films. Finally, the obtained results showed that for particular thickness of coating, the low charge states were produced with higher yield than in the case of pure material.
Identification of uranium oxidation states using oxygen K-edge scanning transmission X-ray microscopy
The field of nuclear forensics is growing in importance, and the increasing capabilities at synchrotron radiation light sources enable non-destructive characterization of oxide particles with better spatial, compositional, and oxidation state speciation resolution than ever before. Here, uranium oxide particles derived from multiple wet chemical processing methods were examined using a scanning transmission X-ray microscope (STXM), and a weakly-supervised method was developed to automatically analyze the collected data. Multiple uranium oxidation states were observed and quantified within and between samples, yielding information about differences between particles produced via the various processing routes.
Secondary organic aerosol (SOA) yields from NO 3 radical + isoprene based on nighttime aircraft power plant plume transects
Nighttime reaction of nitrate radicals ( NO 3 ) with biogenic volatile organic compounds (BVOC) has been proposed as a potentially important but also highly uncertain source of secondary organic aerosol (SOA). The southeastern United States has both high BVOC and nitrogen oxide ( NO x ) emissions, resulting in a large model-predicted NO 3 -BVOC source of SOA. Coal-fired power plants in this region constitute substantial NO x emissions point sources into a nighttime atmosphere characterized by high regionally widespread concentrations of isoprene. In this paper, we exploit nighttime aircraft observations of these power plant plumes, in which NO 3 radicals rapidly remove isoprene, to obtain field-based estimates of the secondary organic aerosol yield from NO 3 + isoprene. Observed in-plume increases in nitrate aerosol are consistent with organic nitrate aerosol production from NO 3 + isoprene, and these are used to determine molar SOA yields, for which the average over nine plumes is 9 % ( ±5 %). Corresponding mass yields depend on the assumed molecular formula for isoprene- NO 3 -SOA, but the average over nine plumes is 27 %( ±14 %), on average larger than those previously measured in chamber studies (12 %–14 % mass yield as Δ OA / Δ VOC after oxidation of both double bonds). Yields are larger for longer plume ages.This suggests that ambient aging processes lead more effectively to condensable material than typical chamber conditions allow. We discuss potential mechanistic explanations for this difference, including longer ambient peroxy radical lifetimes and heterogeneous reactions of NO 3 -isoprene gas phase products. As a result more in-depth studies are needed to better understand the aerosol yield and oxidation mechanism of NO 3 radical + isoprene, a coupled anthropogenic–biogenic source of SOA that may be regionally significant.
Exploring New Applications of Municipal Solid Waste
This study aimed to (i) characterize municipal solid waste (MSW) sourced from Utah and Michigan transfer stations and (ii) upcycle, produce, and evaluate composites derived from this MSW. Composition analysis showed that the MSW was composed of a variety of commodity plastics, paper/cardboard, and inorganic materials. Detailed chemical analysis for lignin, cellulose, hemicellulose, and lipids was performed. The plastics identified were mainly polyethylene, polypropylene, polystyrene, and poly (ethylene terephthalate). The compoundability of the MSW was assessed by torque rheometry. Composites were prepared by compounding the MSW in an extruder. A composite flexural strength of 29 MPa and a modulus of 1.0 GPa was achieved. The thermal properties of the composites were also determined. The melt flow behavior of the MSW composites at 190 °C was comparable to wood plastic composite formulations.
Development of a Superconducting Adaptive Gap Undulator Prototype for NSLS-II
The photon flux and brightness of synchrotron radiation, crucial parameters for any light source, vary significantly depending on the type of source employed. Among the 23 Insertion Device (ID) sources at the National Synchrotron Light Source II (NSLS-II) at Brookhaven National Lab (BNL), the 12-year-old 3m-long In-Vacuum Undulator (IVU20) stands out for its superior performance, although it no longer represents the cutting edge of technology. Recently, there has been a shift in focus towards developing next-generation sources, particularly Superconducting Undulators (SCUs), characterized by smaller gaps, shorter periods, and maximum lengths. However, despite ongoing research and development efforts, SCUs have yet to surpass their predecessors, the Cryogenic Permanent Magnet Undulators (CPMUs), in terms of performance. This is largely attributed to the limitations posed by traditional superconducting wire, as well as challenges in the design of the magnetic structure and vacuum chamber. In this paper, we aim to overcome such limitations through the development of a unique prototype Superconducting Adaptive Gap Undulator (SC-AGU) magnet core and vacuum chamber design. This paper will outline a novel technical approach aimed at constructing a compact prototype magnet array utilizing state-of-the-art superconducting wire technology. This approach provides a more efficient magnetic structure, allowing for enhanced magnetic field strength and stability.
Monitoring CO2 sources and sinks from space : the Orbiting Carbon Observatory (OCO) Mission
NASA's Orbiting Carbon Observatory (OCO) will make the first space-based measurements of atmospheric carbon dioxide (CO2) with the precision, resolution, and coverage needed to characterize the geographic distribution of CO2 sources and sinks and quantify their variability over the seasonal cycle. OCO is currently scheduled for launch in 2008. The observatory will carry a single instrument that incorporates three high-resolution grating spectrometers designed to measure the near-infrared absorption by CO2 and molecular oxygen (O2) in reflected sunlight. OCO will fly 12 minutes ahead of the EOS Aqua platform in the Earth Observing System (EOS) Afternoon Constellation (A-Train). The in-strument will collect 12 to 24 soundings per second as the Observatory moves along its orbit track on the day side of the Earth. A small sampling footprint (<3 km2 at nadir) was adopted to reduce biases in each sounding associated with clouds and aerosols and spatial variations in surface topography. A comprehensive ground-based validation program will be used to assess random errors and biases in the XCO2 product on regional to continental scales. Measurements collected by OCO will be assimilated with other environmental measurements to retrieve surface sources and sinks of CO2. This information could play an important role in monitoring the integrity of large scale CO2 sequestration projects.
Requirements for an in-house synchrotron radiation source at LANL
Synchrotron measurements for diffraction characterization and high resolution tomography require: (1) unable monochromatic X-ray incident energy from 65keV to 100keV. 65keV need is defined by Ta and W absorption edges at 67keV, 100keV need is defined by need to penetrate U/Pu sample thickness of 0.5 mm (2) focused flux density of the monochromatic beam on a beam spot of ~100 µm 2 greater than 10 10 photons per second to allow some slower kinetics experiments such as heating, cooling for CTE measurements (but not quenching, solidification etc. which require <0.1 s resolution) (3) Δλ/λ resolution of 0.3% or better across the energy spectrum. This can be achieved by monochromator as long as flux needs are met in the monochromatic beam.
Mechanism of Catalytic O2 Reduction by Iron Tetraphenylporphyrin
The catalytic reduction of O2 to H2O is important for energy transduction in both synthetic and natural systems. Herein, we report a kinetic study of O2 reduction catalyzed by iron tetraphenylporphyrin in N,N-dimethylformamide using decamethylferrocene as a soluble reductant and para-toluenesulfonic acid (pTsOH) as the proton source. Reduction of the ferric porphyrin, [FeIII(TPP)]+ , forms the ferrous porphyrin, FeII(TPP), which binds O2 reversibly to form the ferric-superoxide porphyrin complex, FeIII(TPP)(O2 •?). The temperature dependence of both the electron transfer and O2 binding equilibrium constants have been determined. Kinetic studies over a range of concentrations and temperatures show that the catalyst resting state changes during the course of each catalytic run, necessitating the use of global kinetic modeling to extract rate constants and kinetic barriers. The rate-determining step in oxygen reduction is protonation of FeIII(TPP)(O2•?) by pTsOH, which proceeds with a substantial kinetic barrier. Computational studies indicate that this barrier for proton transfer arises from an unfavorable pre-association of the proton donor with the superoxide adduct and a transition state that requires significant desolvation of the proton donor. Together, these results are the first example of oxygen reduction by iron tetraphenylporphyrin where the pre-equilibria between ferric, ferrous, and ferric-superoxide intermediates have been quantified under catalytic conditions. This work gives a generalizable model for the mechanism of iron porphyrin-catalyzed ORR and provides an unusually complete mechanistic study of an ORR reaction. More broadly, this study also highlights the kinetic challenges for proton transfer to catalytic intermediates in organic media.
Initial Characterization and Optimization of the Liquid Sampling-Atmospheric Pressure Glow Discharge Ionization Source Coupled to an Orbitrap Mass Spectrometer for the Determination of Plutonium
Plutonium measurements are essential to the nuclear forensics and safeguards community. The liquid sampling-atmospheric pressure glow discharge (LS-APGD) microplasma ionization source coupled with an Orbitrap mass spectrometer is a proven platform for uranium isotope ratio determinations. Here, this work expands the LS-APGD-Orbitrap platform capabilities by reporting the first-ever analysis of plutonium with the LS-APGD and the first-ever measurement of elemental plutonium with an Orbitrap mass spectrometer. This coupling has the potential to dramatically reduce the complex sample manipulations required for traditional analysis techniques employed for actinide isotope ratio determinations. As a first step toward the goal of simultaneous uranium and plutonium isotope ratio determinations, the initial characterization and optimization of the platform for the detection of plutonium are reported. Collision-induced dissociation modality settings were optimized to reduce water-related and other molecular clusters containing plutonium, maximizing 242 Pu 16 O 2 + responses. A design of experiments study was conducted to optimize the discharge conditions of the dual-electrode LS-APGD toward the responsivity of 242 Pu 16 O 2 +. The measurement sensitivity was determined from a Pu response curve, yielding a limit of detection of 10 fg (absolute) of total analyte when data was collected and processed with a Spectroswiss FTMS Booster X2 data acquisition system. Additionally, plutonium and uranium were measured in a simultaneous acquisition, and each analyte remained unaffected by the other. It is believed that the LS-APGD-Orbitrap platform could be a valuable addition to the nuclear forensics’ toolbox and, indeed, other scientific disciplines and regulatory communities in which rapid, high-resolution plutonium determinations are paramount.
Reductive amination cascades in cell‐free and resting whole cell formats for valorization of lignin deconstruction products
Abstract The selective introduction of amine groups within deconstruction products of lignin could provide an avenue for valorizing waste biomass while achieving a green synthesis of industrially relevant building blocks from sustainable sources. Here, we built and characterized enzyme cascades that create aldehydes and subsequently primary amines from diverse lignin‐derived carboxylic acids using a carboxylic acid reductase (CAR) and an ω‐transaminase (TA). Unlike previous studies that have paired CAR and TA enzymes, here we examine multiple homologs of each of these enzymes and a broader set of candidate substrates. In addition, we compare the performance of these systems in cell‐free and resting whole‐cell biocatalysis formats using the conversion of vanillate to vanillyl amine as model chemistry. We also demonstrate that resting whole cells can be recycled for multiple batch reactions. We used the knowledge gained from this study to produce several amines from carboxylic acid precursors using one‐pot biocatalytic reactions, several of which we report for the first time. These results expand our knowledge of these industrially relevant enzyme families to new substrates and contexts for environmentally friendly and potentially low‐cost synthesis of diverse aryl aldehydes and amines.
Structural properties of optically clear bacterial cellulose produced by Komagataeibacter hansenii using arabitol
Here, bacterial cellulose (BC) exhibits beneficial properties for use in biomedical applications but is limited by its lack of tunable transparency capabilities. To overcome this deficiency, a novel method to synthesize transparent BC materials using an alternative carbon source, namely arabitol, was developed. Characterization of the BC pellicles was performed for yield, transparency, surface morphology, and molecular assembly. Transparent BC was produced using mixtures of glucose and arabitol. Zero percent arabitol pellicles exhibited 25% light transmittance, which increased with increasing arabitol concentration through to 75% light transmittance. While transparency increased, overall BC yield was maintained indicating that the altered transparency may be induced on a micro-scale rather than a macro-scale. Significant differences in fiber diameter and the presence of aromatic signatures were observed. Overall, this research outlines methods for producing BC with tunable optical transparency, while also bringing new insight to insoluble components of exopolymers produced by Komagataeibacter hansenii.
Optically induced quantum transitions in direct probed mesoscopic NbSe 2 for prototypical bolometers
Superconducting transition-edge sensors (TES) have emerged as fascinating devices to detect broadband electromagnetic radiation with low thermal noise. The advent of metallic transition metal dichalcogenides, such as NbSe 2 , has also created an impetus to understand their low-temperature properties, including superconductivity. Interestingly, NbSe 2 -based sensor within the TES framework remains unexplored. In this work, direct-probed superconducting NbSe 2 absorbers led to a proof-of-concept demonstration for the transduction of incoming light to heat, where a thermodynamic superconducting phase transition in NbSe 2 was evident to switch it to the normal-state, when biased below its superconducting transition temperature. A wavelength-dependent response of its optical absorption properties was observed, based on the incident optical excitation source used. Furthermore, extensive optical characterization studies were conducted using Raman spectroscopy, where the in-plane and out-of-plane thermal conductivity was empirically determined. Our results open new possibilities for the use of NbSe 2 in superconducting radiation detectors, including in a TES framework
The battery failure databank: Insights from an open-access database of thermal runaway behaviors of Li-ion cells and a resource for benchmarking risks
The thermal response of Li-ion cells can greatly vary for identical cell designs tested under identical conditions, the distribution of which is costly to fully characterize experimentally. The open-source Battery Failure Databank presented here contains robust, high-quality data from hundreds of abuse tests spanning numerous commercial cell designs and testing conditions. Data was gathered using a fractional thermal runaway calorimeter and contains the fractional breakdown of heat and mass that was ejected, as well as high-speed synchrotron radiography of the internal dynamic response of cells during thermal runaway. The distribution of thermal output, mass ejection, and internal response of commercial cells are compared for different abuse-test conditions, which when normalized on a per amp-hour basis show a strong positive correlation between heat output from cells, the fraction of mass ejected from the cells, their energy- and power-density. Ejected mass was shown to contain 10x more heat per gram than non-ejected mass. The causes of 'outlier' thermal and ejection responses i.e., extreme cases, are elucidated by high-speed radiography which showed how occurrences such as vent clogging can create more hazardous conditions. High-speed radiography also demonstrated how the time-resolved interplay of thermal runaway propagation and mass ejection influences the total heat generated.
A variance deconvolution estimator for efficient uncertainty quantification in Monte Carlo radiation transport applications
Monte Carlo simulations are at the heart of many high-fidelity simulations and analyses for radiation transport systems. As is the case with any complex computational model, it is important to propagate sources of input uncertainty and characterize how they affect model output. Unfortunately, uncertainty quantification (UQ) is made difficult by the stochastic variability that Monte Carlo transport solvers introduce. The standard method to avoid corrupting the UQ statistics with the transport solver noise is to increase the number of particle histories, resulting in very high computational costs. In this contribution, we propose and analyze a sampling estimator based on the law of total variance to compute UQ variance even in the presence of residual noise from Monte Carlo transport calculations. Here, we rigorously derive the statistical properties of the new variance estimator, compare its performance to that of the standard method, and demonstrate its use on neutral particle transport model problems involving both attenuation and scattering physics. We illustrate, both analytically and numerically, the estimator’s statistical performance as a function of available computational budget and the distribution of that budget between UQ samples and particle histories. We show analytically and corroborate numerically that the new estimator is unbiased, unlike the standard approach, and is more accurate and precise than the standard estimator for the same computational budget.
Identifying human failure events (HFEs) for external hazard probabilistic risk assessment
In recent years, several advancements in nuclear power plant (NPP) probabilistic risk assessment (PRA) have been driven by increased understanding of external hazards, plant response, and uncertainties. However, major sources of uncertainty associated with external hazard PRA remain. One important source is how risk-significant human actions that are carried out to enable plant response and recovery from natural hazards cause the close coupling of physical impacts on plants and overall plant risk during these hazard events. This makes human reliability and human-plant interactions important elements to consider in resolving PRA gaps in external hazards. One of the challenges in considering human response in external hazard probabilistic risk assessment (XHPRA) is that most existing human reliability analysis (HRA) models were not developed for assessing actions outside the control room (termed ex-control room actions) and hazard response. To support this new scope, HRA models will need to be developed or modified to support identification of human activities, causal factors, and uncertainties inherent in external hazard response, thereby providing insights regarding event timing and physical event conditions as they relate to human performance. In this study, there are two main objectives: (1) evaluate the applicability of an existing cognitive-based HRA method, Phoenix, to ex-control room actions, and (2) identify sources of uncertainty to be characterized or reduced in order to make this method suitable for XHPRA. The first step of such work is performed by assessing the suitability of existing HRA methods to support identifying human failure events (HFEs) for human response to flooding hazards. These HFEs are human actions or inactions that are involved in human responses to flooding hazards and could contribute to the loss of a critical function for the plant in the scenario being examined. Here, in this work, decomposition analyses using the cognitive-based Phoenix HRA model are used to identify HFEs. The Phoenix method was found to be suitable for analyzing ex-control room actions as well as identifying specific HFEs and underlying crew failure modes (CFMs). However, the method's suitability for use in ex-control room actions would benefit from expanding the available CFMs to accommodate a larger variety of physical and communication tasks.
Uncertain quantum computing futures and potential energy and physical resource impacts at scale
Considerable attention has recently focused on the vast energy and water demands of supercomputing, namely large-scale data centers that underpin artificial intelligence (AI), one of the great disruptors of contemporary society. Looking ahead some years from now, quantum computing is poised to disrupt established computing paradigms once again. Scientists and engineers are now working intensely to bring this century-old dream of physicists to fruition. Yet, as quantum computers begin to be integrated with classical supercomputing architectures, the implications for energy and physical resource use also need to be understood, especially how they compare to today’s AI data centers. These impacts have not yet been quantified by the research community – a notable gap in the literature, even if commercial-scale deployment of Quantum-Accelerated Computing Infrastructure (QuACI) is not expected for a few more years. This study is the first to conduct such an assessment. Using publicly available information from academic sources and private industry, we characterize multiple configurations of superconducting qubit-based, fault-tolerant quantum computers (FTQC) that could plausibly be deployed at scale in the 2030s and into the 2040s. By parameterizing these FTQC systems at a process level, we conduct a prospective scenario analysis to quantify their energy and physical resource needs. While these estimates are uncertain, given the current state of quantum technologies and their unknown future trajectories, important insights can already be drawn. One key finding is that while the electricity needs for a fleet of FTQCs are within the bounds of previous modeling studies that have explored high electricity demand futures, the needs for certain physical resources, namely water and helium-3, could pose bottlenecks to QuACI scale-up.
Time domain probabilistic seismic risk analysis using ground motion prediction equations of Fourier amplitude spectra
Modeling of Fourier amplitude spectra (FAS) of seismic motions has gained much attention in engineering seismology. In the past few years, several ground motion prediction equations (GMPEs) and inter-frequency correlation structure of FAS have been established. Due to many preferable characteristics of FAS, probabilistic seismic hazard/risk analysis is rapidly changing from ergodic, spectrum acceleration Sa(T 0 )-based approach to non-ergodic, site-specific, FAS-based approach. This paper presents time domain intrusive framework for probabilistic seismic risk analysis using GMPE of FAS. Herein, methodology for time domain stochastic ground motion modeling based on GMPEs of FAS is presented in some detail. The simulated uncertain motions are modeled as a random process and represented by polynomial chaos Karhunen-Loève expansion. The random process excitations are further propagated into the uncertain structural system using Galerkin stochastic finite element method (SFEM). Probabilistic evolution of structural response is solved, and such solution is used to develop seismic risk for any damage state. The presented framework is illustrated through seismic risk analysis of a four-story building subjected to possible earthquakes from two strike slip faults. The influences of the epistemic uncertainties in source stress drop Δσ and site attenuation κ0 on seismic risk are investigated. The need for non-ergodic seismic risk analysis with source-specific and site specific characterizations is emphasized.