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At least 145 records · Page 8

Evaluation of Polyethylene and Blank Pulsed Sphere Experiments Using Deuteron Transport Feature in COG

From the late 1960s to about 1985, LLNL undertook a series of ‘pulsed sphere’ experiments for 31 materials involving 148 different experiments using 75 different spheres. The purpose was to measure the neutron leakage spectra for different materials from 14-MeV neutrons generated by 3 H(d,n) 4 He reactions induced by an incident D+ beam from the Insulated Core Transfer (ICT) accelerator at LLNL. This deuteron beam was focused to impinge upon tritium loaded onto a titanium substrate within a low mass target assembly placed within the center of a spherical shell constructed from the material of interest. COG is a three-dimensional, continuous energy, Monte Carlo code, developed by Lawrence Livermore National Laboratory (LLNL). Recent additions to COG include alpha and deuteron particle transport in order to directly calculate (α,n) and 3 H(d,n) 4 He reactions, and resulting neutron emission spectra. Results of the direct deuteron transport calculation for the 0.8 MFP (mean free path) polyethylene sphere with PILOT B detector was previously published. The purpose of this paper is to present expanded COG results showing the neutron peak from deuterium buildup ( 2 H(d,n) 3 He) due to tritium decay in the target. Cross section data libraries used are ENDF/B-VIII.0 for neutrons and ENDF/B-VII.1 for deuterons, respectively.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Nonlinear post-compression in multi-pass cells in the mid-IR region using bulk materials

We numerically investigate the regime of nonlinear pulse compression at mid-IR wavelengths in a multi-pass cell (MPC) containing a dielectric plate. This post-compression setup allows for ionization-free spectral broadening and self-compression while mitigating self-focusing effects. We find that self-compression occurs for a wide range of MPC and pulse parameters and derive scaling rules that enable its optimization. We also reveal the solitonic dynamics of the pulse propagation in the MPC and its limitations and show that spatiotemporal/spectral couplings can be mitigated for appropriately chosen parameters. In addition, we reveal the formation of spectral features akin to quasi-phase matched degenerate four-wave mixing. Finally, we present two case studies of self-compression at 3-μm and 6-μm wavelengths using pulse parameters compatible with driving high-field physics experiments. The simulations presented in this paper set a framework for future experimental work using few-cycle pulses at mid-IR wavelengths.

Carlson, D. (ORCID:0000000346836463)↗

CO 2 to Bioplastics: Beneficial Re-use of Carbon Emissions from Coal-fired Power Plants using Microalgae

This project sought to address the technical and economic barriers to carbon dioxide (CO 2 ) capture and utilization using microalgae. Specifically, a dual photobioreactor (PBR)/open raceway pond (ORP) cultivation system was evaluated with respect to capital and operational costs, productivity, and culture health, and compared to an ORP-only cultivation system. In the dual (or “hybrid”) system, a cyclic flow PBR was used to provide inoculum for two open raceway ponds after each harvest, with the hypothesis that this PBR + pond system should result in improved performance compared to traditional raceway ponds. Two other raceway ponds were operated conventionally as a control, the experiments being performed at Duke Energy’s East Bend Station in northern KY using coal-derived flue gas as the CO 2 source. Although algae productivity achieved was mediocre due to the fact that the experiments had to be performed late in the growing season when climatic conditions were not optimal for high growth, the hybrid cultivation system showed a higher level of algae productivity (statistically significant) compared to the traditional ponds. In order to realize the maximum value of the algal biomass produced, fractionation of the biomass was examined. Bioplastic compounding and material characterization was subsequently performed using three feed stocks: whole biomass, lipid-extracted biomass and the proteinaceous residue from full fractionation. In general, the whole and lipid-extracted biomass gave similar results in terms of the properties of the resulting bioplastics, while the proteinaceous residue showed promise for the production of a polybutylene adipate terephthalate (PBAT) blend. Finally, sustainability assessment of a putative biorefinery system was conducted, including techno-economic and life cycle impact assessment. Nine different production scenarios were considered, comprising combinations of the three different biomass growth architectures (ORP, PBR and dual PBR-ORP systems) coupled with three different algae biomass processing pathways (drying only, lipid extraction and fractionation). Results show that the minimum selling price of the bioplastic feed stock (BPFS) is within the realm of economic competition with prices as low as $970 USD tonne -1 . Additionally, life cycle impact assessment results indicate drastic improvements in performance of the produced BPFS, with reductions in greenhouse gas emissions ranging between 67 and 116% compared to a petroleum based plastic feedstock.

01 COAL, LIGNITE, AND PEAT↗

Using diglycolamides to improve rare-earth element separation

The family of 17 elements known as the “rare earth elements” are difficult to produce economically. Despite this, they are described as “critical raw materials” because of their unique properties and their various technological applications. This means their use is accelerating globally. Separation of these elements is a fundamental challenge, but this does not daunt Dr Santa Jansone-Popova and her team at Oak Ridge National Laboratory. In recovering praseodymium from neodymium using a variety of ligands known as diglycolamides, she has been demonstrating potentially game-changing advances in liquid-liquid separations that could realise more of these in-demand materials.

Jansone-Popova, Santa↗

n–Doping of a Low–Electron–Affinity Polymer Used as an Electron–Transport Layer in Organic Light–Emitting Diodes

n-Doping electron-transport layers (ETLs) increases their conductivity and improves electron injection into organic light-emitting diodes (OLEDs). Because of the low electron affinity and large bandgaps of ETLs used in green and blue OLEDs, n-doping has been notoriously more difficult for these materials. In this work, n-doping of the polymer poly[(9,9-dioctylfluorene-2,7-diyl)-alt-(benzo[2,1,3]thiadiazol-4,7-diyl)] (F8BT) is demonstrated via solution processing, using the air-stable n-dopant (pentamethylcyclopentadienyl)(1,3,5-trimethylbenzene)ruthenium dimer [RuCp*Mes] 2 . Undoped and doped F8BT films are characterized using ultraviolet and inverse photoelectron spectroscopy. The ionization energy and electron affinity of the undoped F8BT are found to be 5.8 and 2.8 eV, respectively. Upon doping F8BT with [RuCp*Mes] 2 , the Fermi level shifts to within 0.25 eV of the F8BT lowest unoccupied molecular orbital, which is indicative of n-doping. Conductivity measurements reveal a four orders of magnitude increase in the conductivity upon doping and irradiation with ultraviolet light. Here, the [RuCp*Mes] 2 -doped F8BT films are incorporated as an ETL into phosphorescent green OLEDs, and the luminance is improved by three orders of magnitude when compared to identical devices with an undoped F8BT ETL.

36 MATERIALS SCIENCE↗

Learning compact physics‐aware delayed photocurrent models using dynamic mode decomposition

Abstract Radiation‐induced photocurrent in semiconductor devices can be simulated using complex physics‐based models, which are accurate, but computationally expensive. This presents a challenge for implementing device characteristics in high‐level circuit simulations where it is computationally infeasible to evaluate detailed models for multiple individual circuit elements. In this work we demonstrate a procedure for learning compact delayed photocurrent models that are efficient enough to implement in large‐scale circuit simulations, but remain faithful to the underlying physics. Our approach utilizes dynamic mode decomposition (DMD), a system identification technique for learning reduced‐order discrete‐time dynamical systems from time series data based on singular value decomposition. To obtain physics‐aware device models, we simulate the excess carrier density induced by radiation pulses by solving numerically the ambipolar diffusion equation, then use the simulated internal state as training data for the DMD algorithm. Our results show that the significantly reduced‐order delayed photocurrent models obtained via this method accurately approximate the dynamics of the internal excess carrier density—which can be used to calculate the induced current at the device boundaries—while remaining compact enough to incorporate into larger circuit simulations.

Hanson, Joshua↗

Virtual diffraction simulations using the quasi-coarse-grained dynamics method to understand and interpret plasticity contributions during in situ shock experiments

The dynamic deformation response of metallic materials has contributions from dislocations, deformation twinning, and plastic deformation. The current state-of-art techniques can detail the complex mechanistic history of deformation modes under shock loading in real-time using in situ X-ray diffraction (XRD). However, the capability of these experiments to unravel plasticity contributions is challenging due to limitations in interpreting results and the lack of validation from atomistic simulations. Molecular dynamics (MD) simulations can successfully capture various deformation modes in metals and complement experiments using simulated diffractograms at various stages of evolution. However, the difference in length and time scales of MD simulations and experiments is a substantial obstacle in completing and interpreting in situ diffractograms. Therefore, the existing modeling methods require various approximations to model defect evolution and interaction at the mesoscales. However, while using approximations to correlate the peak broadening behavior to the density of dislocations or the shifts/splitting due to the presence of twins, the interpretations of the plasticity contributions from diffractograms are non-trivial, especially when multiple modes of deformation may be operating. This viewpoint discusses combining a mesoscale modeling method called quasi-coarse-grained dynamics and virtual XRD to characterize the plasticity contributions in BCC metals from slip, twinning, and phase transformation behavior. Furthermore, the combined approach shows promise in bridging the mesoscale gap between the capabilities of atomic-scale simulations and in situ experiments to characterize the dynamic deformation of materials.

36 MATERIALS SCIENCE↗

Plasma-Assisted Epitaxy of Piezoelectric Sc x Al 1-x N Films on Sapphire for Use in Harsh-Environment Microwave Acoustic Sensors

The Sc x Al 1-x N wurtzite structure has been shown theoretically and experimentally to exhibit significantly higher piezoelectric coupling compared to pure AlN. In this work, a plasma-assisted epitaxial growth method has been used to synthesize epitaxial (0002) Sc x Al 1-x N films on c-sapphire substrates from x = 0.07 to 0.30 by co-evaporating high-purity Sc and Al sources in the presence of a nitrogen plasma generated by an RF plasma source. Epitaxial Sc x Al 1-x N films with highly oriented (0002) grains and in-plane registry were produced on c-sapphire substrates that were pre-exposed to the nitrogen plasma to form an oxynitride seed layer. Growth of Sc x Al 1-x N films was carried out at 930°C under both metal-rich and N-rich conditions using precisely controlled Sc, Al, and N-plasma fluxes. Metal-rich depositions yielded non-(0002)-oriented Sc x Al 1-x N grains and intermetallic ScAl grains. Nitrogen-rich growth with a Sc/Al flux ratio of 1/3 produced the best (0002) epitaxy as determined by x-ray diffraction analysis. Surface acoustic wave resonator (SAWR) devices were fabricated from 500-nm-thick Sc x Al 1-x N and AlN films to extract their electromechanical coupling coefficients, k 2 . As the Sc concentration in the films increases, the degree of (0002) epitaxy is reduced, yet the value of k 2 increases becasue there is more Sc in the wurzite lattice despite the decreased level of (0002) grain alignment. As a result, the use of a 10-nm-thick Si x N y capping layer on top of the Sc x Al 1-x N films aids in preventing etching during SAWR device photolithography and also helps hinder film oxidation up to 800°C.

36 MATERIALS SCIENCE↗

Tree growth, transpiration, and water-use efficiency between shoreline and upland red maple (Acer rubrum) trees in a coastal forest

Coastal shoreline forests are vulnerable to seawater exposure, the impacts of which will increase due to sea-level rise, but the longterm adaption strategies and vulnerability of coastal forests are not well understood. We used whole-tree transpiration, leaf water potential, tree-ring width, and tree-ring d13C (a proxy for intrinsic water use efficiency, iWUE) to examine the long-term adaption strategies of red maple (Acer rubrum) trees at the coastal interface (i.e., shoreline) and nearby upland in Maryland, USA. Red maple trees that grew along the shoreline and were exposed to slightly saline water (up to two PSU) had higher transpiration rates than those growing in the nearby upland forest during a wet year, but these differences disappeared during a normal precipitation year. Shoreline trees grew more slowly than upland trees over the last four decades, but these growth differences have disappeared in the last six years. Shoreline and upland trees had similar variation in iWUE, indicating that higher transpiration rates of the seawater exposed trees did not translate into differences in water use efficiency. There were no differences in predawn and midday water potential between upland and shoreline trees, suggesting no water stress occurs in shoreline trees. These findings indicate that urrent soil salinity is below the threshold to constrain coastal red maple physiological activities.

Wang, Wenzhi↗

Optimizing Phase Change Composite Thermal Energy Storage Using the Thermal Ragone Framework

The thermal Ragone framework can be applied to the design of thermal energy storage heat exchangers to identifying relationships between their power requirements and energy capabilities. This presentation focuses on the design of planar thermal energy storage heat exchangers with phase change materials and thermal conductivity additives. Finite-difference models were used to optimize thermal storage heat exchanger designs focusing on key design parameters of conductivity additive volume fraction, spacing between tubes, and the phase transition temperatures. Design trends were developed for optimal designs based on varying thermal power requirements. To aid in future device design, models of reduced complexity were developed with the ability to predict optimal designs with computational speeds up to 5,000 times faster than finite-difference models.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION,↗

Cold Spray Deposition of 304L Stainless Steel to Mitigate Chloride-Induced Stress Corrosion Cracking in Canisters for Used Nuclear Fuel Storage

A feasibility study of the cold spray deposition process of 304L stainless steel on 304L stainless steel substrates as a mitigation method for chloride-induced stress corrosion cracking (CISCC) has been investigated under various substrate conditions. The study is aimed at the application of this technology to mitigate CISCC that may potentially occur in or nearthe fusion welded regions of stainless steel canisters in Dry Cask Storage System (DCSS) for used nuclear fuels. Spherical gas-atomized 304L stainless steel powder, in the size range of 25 µm to 44 µm, was used as a feedstock powder for the cold spray process. The powder was deposited on four types of 304L substrates with various surface conditions: as-polished, oxidized, cold-rolled, plates with prototypical CISCC. The effects of cold spray parameters on quality of cold spray coatings were investigated. Thickness, porosity, and phases in the as-deposited materials were evaluated using scanning electron microscopy (SEM) and X-ray diffraction (XRD), and correlated with microhardness and adhesion strength measured via micro-indentation and ASTM C633 pulling test, respectively. XRD analysis of the coatings was also conducted to examine the effects of cold spray condition on residual stress state in the coating. Detailed cross-sectional examination of coating/substrate interfaces was performed with transmission electron microscopy (TEM) equipped with energy dispersive spectroscopy (EDS). Dense and continuous coatings with good adhesion strength and hardness were produced for the various substrate conditions by adjusting cold spray parameters. The results demonstrate that cold spray stainless steel coating is a viable option to provide a physical barrier against CISCC in fusion weld regions of stainless steel in corrosive chloride salt-bearing environments.

Dry Cask Storage Systems, cold spray, 304L stainle↗

Micrometer-sized Magnetite Synthesis using Fe(OH)2(s) as a Precursor for Technetium Sequestration from Liquid Nuclear Waste Streams

Systematic batch experiments under variable adjusted physicochemical conditions were conducted to explore optimization of micrometer-sized magnetite synthesis for Tc sequestration from radionuclide waste streams using Fe(OH)2(s) as the precursor. Extensive solid characterization using x-ray diffraction and spectroscopic methods was performed to assess changes in particle morphology and size distribution, as well as Tc speciation and incorporation, in the produced mineral phases. The results show that the solution pH, temperature, and oxidation kinetics play key roles in the final mineral products. Micrometer-sized magnetite crystals (0.62-0.96 µm on average) with well-defined dodecahedral or octahedral structures were synthesized under near neutral (~pH 8) or alkaline (~pH13) conditions at 75 °C, respectively; whereas goethite dominated the end products at room temperature. An increase in pH at 75 °C improved Tc removal from 27% (near neutral pH) to 42% (alkaline pH), but the removal process remained inhibited by redox competitive Cr(VI) present in the waste streams. By adding additional Fe(II) to the system, Tc sequestration was dramatically improved to up to 87% without observable changes in the solid product. The sequestrated Tc existed as TcO2·2H2O and/or Tc(IV) incorporated into magnetite, where extended X-ray absorption fine structure (EXAFS) spectroscopy showed that more Tc was incorporated into magnetite at elevated temperatures and pH conditions, with complete Tc(IV) incorporation into magnetite occurring under 75 °C-pH 13 conditions. Our results indicate that optimal micrometer-sized magnetite can be produced for Tc sequestration by reacting Fe(OH)2(s) with a waste stream simulant under elevated pH (~13) and temperature (75 °C) conditions. The incorporation of reduced Tc(IV) into stable micrometer-sized magnetite provides a viable supplemental immobilizing technology that may be used to improve nuclear waste treatment and disposal needs.

Wang, Guohui↗

Using machine learning to predict the correlation of spectra using SDSS magnitudes as an improvement to the Locus Algorithm

The Locus Algorithm is a new technique to improve the quality of differential photometry by optimising the choices of reference stars. At the heart of this algorithm is a routine to assess how good each potential reference star is by comparing its SDSS magnitude values to those of the target star. In this way, the difference in wavelength-dependent effects of the Earth’s atmospheric scattering between target and reference can be minimised. This paper sets out a new way to estimate the quality of each reference star using machine learning. A random subset of stars from SDSS with spectra was chosen. For each one, a suitable reference star, also with a spectrum, was chosen. The correlation between the two spectra in the SDSS r band (between 550 nm and 700 nm) was taken to be the gold-standard measure of how well they match up for differential photometry. The five SDSS magnitude values for each of these stars were used as predictors. A number of supervised machine learning models were constructed on a training set of the stars and were each evaluated on a testing set. The model using Support Vector Regression had the best performance of these models. It was then tested on a final, hold-out, validation set of stars to get an unbiased measure of its performance. With an R 2 of 0.62, the SVR model presents enhanced performance for the Locus Algorithm technique.

79 ASTRONOMY AND ASTROPHYSICS↗