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At least 361 records · Page 20

High-resolution analysis of clay minerals and amorphous materials in martian analog environments

Mudrocks and mud-sized sediments (i.e., silt to clay) dominate the surface of Earth and Mars. These fine-grained sediments preserve a rich history of sedimentary processes from source to sink and shed light on ancient climates. However, both the physical and chemical nature of these materials make them difficult to fully characterize with traditional laboratory techniques. Here, we explore a cross-disciplinary and high-resolution approach using synchrotron radiation for X-ray diffraction, pair distribution function analysis, and submicrometer-scale X-ray fluorescence, combined with transmission electron microscopy, to better understand the nanostructure and composition of mud-sized sediments from a glacio-fluvial watershed in southwest Iceland. Our results demonstrate that sediments in the cold and wet climate of Iceland are more altered than previously thought, as evidenced by the identification of kaolinite and mixed-layer kaolinite-smectite. Additionally, sediments are enriched in amorphous materials and nanocrystalline phases, as determined from grain morphologies and compositions consistent with allophane, hisingerite, ferrihydrite, and halloysite. These alteration products are present as intimate mixtures that vary across depositional sites, demonstrating the dynamic nature of the secondary assemblage from source to sink. This work has implications for Mars, where, for example, basalt-sourced sedimentary rocks from Gale crater are abundant in clay minerals and amorphous materials. Finally, this work underpins the importance of using high-resolution techniques, a coordinated methodology, and developing innovative approaches for future planetary sample return missions (e.g., Mars sample return).

36 MATERIALS SCIENCE↗

Optimization of the JUNO liquid scintillator composition using a Daya Bay antineutrino detector

To maximize the light yield of the liquid scintillator (LS) for the Jiangmen Underground Neutrino Observatory (JUNO), a 20 t LS sample was produced in a pilot plant at Daya Bay. The optical properties of the new LS in various compositions were studied by replacing the gadolinium-loaded LS in one antineutrino detector. The concentrations of the fluor, PPO, and the wavelength shifter, bis-MSB, were increased in 12 steps from 0.5 g/L and 0.01 mg/L to 4 g/L and 13 mg/L, respectively. The numbers of total detected photoelectrons suggest that, with the optically purified solvent, the bis-MSB concentration does not need to be more than 4 mg/L. In order to bridge the one order of magnitude in the detector size difference between Daya Bay and JUNO, the Daya Bay data were used to tune the parameters of a newly developed optical model. Then, the model and tuned parameters were used in the JUNO simulation. Overall, this enabled to determine the optimal composition for the JUNO LS: purified solvent LAB with 2.5 g/L PPO, and 1 to 4 mg/L bis-MSB.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Manufacturing of Fabric Electrodes using a High-Throughput Screening Platform for Redox Flow Batteries

The objective of this project is to establish a new manufacturing methodology with machine learning- based high-throughput screening for the design and development of hierarchical structured, high-performance fabric electrodes for redox flow batteries (RFBs). The end goal of the project is to design and manufacture fabric electrodes for RFB applications that can provide 250 mA/cm2 current density operation for 100-cycles with 80% average energy efficiency. This was accomplished by first examining the structure-performance-property linkages of the electrodes provided by our partner, AvCarb. The electrodes’ microstructure was characterized by determining their pore size distribution, tortuosity, specific surface area, and porosity. The ohmic, charge transfer and mass transfer resistances were then calculated using electrochemical impedance spectroscopy. Carbon cloth electrodes showed the greatest resistance, which was dominated by charge transfer resistance, which we believe is related to the surface functionalization. Full cell cycling was used in order to determine the area specific resistance and energy efficiency of the cells. All of this experimental data and the results of the mathematical model (to increase the amount of inputs with parametric sweeping) were used to develop a machine learning-based model for the design of high-performance fabric electrodes. Using the results from the machine learning tool, optimized electrodes were fabricated by AvCarb. The ohmic, charge transfer and mass transfer resistances for these new electrodes were measured, and both performed better than any of the initial samples which had been provided by AvCarb.

25 ENERGY STORAGE↗

Hydraulic Conductivity Measurements, Utqiagvik (Barrow), Alaska, 2014

Six individual ice cores were collected from the Barrow Environmental Observatory in Barrow, Alaska, in May of 2013 as part of the Next Generation Ecosystem Experiment (NGEE). Each core was drilled at a different location to varying depths. After drilling, the cores were stored in coolers packed with dry ice and flown to Lawrence Berkeley National Laboratory (LBNL) in Berkeley, CA. 3-dimensional images of the cores were constructed using medical X-ray computed tomography (CT) scanner at 120kV. Hydraulic conductivity samples were extracted from these cores at LBNL Richmond Field Station in Richmond, CA, in February 2014 by cutting 5 to 8 inch segments using a chop saw. Samples were packed individually and stored at -20C freezing temperatures to minimize any changes in structure or loss of ice content prior to analysis. Hydraulic conductivity was determined through falling head tests using a permeameter [ELE International, Model #: K-770B] (Appendix A). Samples were placed in a latex membrane via a membrane stretcher while frozen. Use of a membrane stretcher made the membranes easier to secure and minimized contact with the sample. A clear polycarbonate sleeve, fabricated with a stainless steel ring at the bottom to keep the sleeve from floating, was placed around the sample inside the permeameter to minimize deformation during analysis. The permeameter was filled with water and 1.0 PSI of air was applied for confining pressure during sample defrost. Outflow valves were left open to allow for incremental thawing and samples were left to thaw for approximately 12 hours. After approximately 12 hours of thaw, initial falling head tests were performed. When the flow was significantly too fast or too slow, the analysis was stopped and the burette size was adjusted accordingly (i.e. a larger diameter burette was used for flows that were faster than desired or a smaller diameter burette was used for flows that were slower than desired). Two to four measurements were collected on each sample and collection stopped when the applied head load exceeded 25% change from the original load. Analyses were performed between 2 to 3 times for each sample. The final hydraulic conductivity calculations were computed using methodology of Das et al., 1985.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Waffle Homes: Utilizing Aerial Imagery of Unfinished Buildings to Determine Average Room Size

A primary function of the Population Density Tables Project (PDT) at Oak Ridge National Laboratory is to produce residential population densities per 1000 sq. ft. for each country and their associated first-level administrative units. This is accomplished by utilizing the average size of different types of dwelling areas (urban, rural, single-family, multi-family, etc.) and the average household size provided by a country’s Census or statistical bureau records. This data is available for the majority of Europe, North America, and large swathes of Asia, but is less easily found in Africa and South America. In these regions, Censuses generally report dwelling area by number of rooms, which poses the challenging question of how we can translate number of rooms to dwelling size when no dwelling size areas are available with which to compare. Using sub-meter resolution satellite imagery of Accra, Ghana, this challenge can be tackled using imagery of roofless buildings currently under construction that show the interior floor plan of the dwelling. A sample of buildings from the different neighborhoods of Accra can be digitized to provide an estimate and range of average room sizes of dwellings. This average room size can then be translated to a total dwelling area using the "number of rooms occupied by a household" variable from the Ghanaian Census. This intermediate step between average dwelling size and number of rooms occupied, fills the missing link that prevents PDT from continually producing new population densities for countries where dwelling size is unavailable through any official means.

Woody, Carson↗

The influence of chemical short-range order on the nanoindentation properties of high-entropy alloys prepared via laser powder bed fusion

Chemical short-range order (CSRO) plays an instrumental role in determining the mechanical properties of high-entropy alloys (HEAs). Current methods for controlling CSRO mainly focus on cast HEAs, which can not solve the problem of grain coarsening caused by homogenization treatments. Laser Powder Bed Fusion (LPBF), which has extremely high cooling rates, can suppress compositional segregation, refine grain structures, and achieve low CSRO. This offers a promising avenue for quantitatively controlling CSRO without the need for homogenization treatments. In this study, we investigate the CSRO of HEAs fabricated via LPBF and elucidate their influence on nanoindentation behavior. The results show that, at the low cooling rate, the average size of CSRO is 0.66 nm and they occupy 2.8% of the cross-sectional area, while at high cooling rate, the corresponding values are 0.92 nm and 9.9%, respectively, both of which are significantly smaller than those of cast HEAs. Furthermore, by analyzing samples with different CSROs, we observe that the hardness increases and then decreases with the increase of CSRO, primarily due to the preferential formation of dislocations in regions enriched with Cr-Mn-Ni. With the improvement of CSRO, both the size and quantity of Cr-Mn-Ni rich region gradually increased; subsequently, as multiple Cr-Mn-Ni rich regions tend to merge into one during the CSRO improvement, the size of the Cr-Mn-Ni rich region continued to increase while the quantity gradually decreased; when the size of the Cr-Mn-Ni rich region is moderate and widely dispersed, the dislocation density is higher with much more uniform distributions, which favorably improves nanoindentation hardness.

36 MATERIALS SCIENCE↗

Model-independent measurement of the matter-radiation equality scale in DESI 2024

The peak of the matter power spectrum, known as the turnover (TO) scale, is determined by the horizon size at the time of matter-radiation equality. This scale can serve as a standard ruler, independent of other features in the matter power spectrum, such as baryon acoustic oscillations (BAO). Here, in this work, we present the first detection of the turnover in the galaxy autopower spectrum, utilizing the distribution of quasars and luminous red galaxies (LRG) measured by the Dark Energy Spectroscopic Instrument (DESI) during its first year of survey operations in a model-independent manner. To avoid confirmation bias, we first analyze the data using data blinding methods designed for the DESI baryon acoustic oscillation, redshift space distortion and scale-dependent bias signals. We measure the angle-averaged dilation distance 𝐷 V ⁡(𝑧 = 1.651) = (38.1 ± 2.5)⁢𝑟 H from the quasars and 𝐷 V ⁡(𝑧 = 0.733) = (21.8 ± 1.0)⁢𝑟 H from the LRG sample in units of the horizon 𝑟 H at the matter-radiation-equality epoch. Combining these two constraints and assuming a flat Λ⁢CDM model with three standard neutrino species, we can translate this into a constraint of Ω m ⁢ℎ 2 = 0.13⁢9$^{+0.036}_{−0.046}$. We can break the Ω m −𝐻 0 degeneracy with low-redshift distance measurements from type-Ia supernova (SN) data from Pantheon+, we obtain a sound-horizon free estimate of the Hubble-Lemaître parameter of 𝐻 0 = 65.2$^{+4.9}_{−6.2}$ km/s/Mpc, consistent with sound-horizon dependent DESI measurements. On the other hand, combining the DESI BAO and TO, we find a truly DESI-only measurement of 𝐻 0 = 74.0$^{+7.2}_{−3.5}$ km/s/Mpc, in line with DESI-only full-shape results where the sound-horizon scale is marginalized out. This discrepancy in 𝐻 0 can be reconciled in a 𝑤 0 ⁢𝑤 𝑎 ⁢ CDM cosmology, where the combination of DESI BAO and TO data yields 𝐻 0 = 66.5 ± 7.2 km/s/Mpc.

cosmological parameters↗

Probing the Mechanical Performance of Micro-architected Porous Structures Through In Situ Characterization and Analysis

Micropores play critical roles in both natural and man-made materials. Such pores take on a variety of shapes and sizes ranging from spherical to irregular sphere-like voids with diameters spanning from the nanometer to millimeter scales. When porous structures are mechanically loaded, the pores direct the stress around their free surfaces, altering the material’s mechanical response relative to fully dense materials. In this study, for the first time, we create micro-architected porous samples using nanolithography and investigate the role of pore morphology by conducting a series of in situ micropillar compression tests in scanning electron microscopy. The findings demonstrate that porosity is the primary factor influencing the mechanical response of these micro-architected materials, as often seen on a macroscopic level. Additionally, we observed that pore geometry had a significant impact on Young’s modulus, yield stress, and strain energy density as a secondary parameter. Then, the extracted Young’s modulus was compared to macroscopic empirical models and determined the analytical models sufficiently described the impact of porosity in the microscopic scale but failed to capture the impact of second-order parameters. Furthermore, these results suggest how porous materials can be tailored to achieve desired mechanical properties based on the engineering applications of interest.

36 MATERIALS SCIENCE↗

Establishing metrics to quantify spatial similarity in spherical and red blood cell distributions

As computational power increases and systems with millions of red blood cells can be simulated, it is important to note that varying spatial distributions of cells may affect simulation outcomes. Since a single simulation may not represent the ensemble behavior, many different configurations may need to be sampled to adequately assess the entire collection of potential cell arrangements. In order to determine both the number of distributions needed and which ones to run, we must first establish methods to identify well-generated, randomly placed cell distributions and to quantify distinct cell configurations. We utilize metrics to assess (1) the presence of any underlying structure to the initial cell distribution and (2) similarity between cell configurations. We propose the use of the radial distribution function to identify long-range structure in a cell configuration and apply it to a randomly distributed and structured set of red blood cells. To quantify spatial similarity between two configurations, we make use of the Jaccard index, and characterize sets of red blood cell and sphere initializations. As an extension to our work submitted to the International Conference on Computational Science, we significantly increase our data set size from 72 to 1048 cells, include a similar set of studies using spheres, compare the effects of varying sphere size, and utilize the Jaccard index distribution to probe sets of extremely similar configurations. Our results show that the radial distribution function can be used as a metric to determine long-range structure in both distributions of spheres and RBCs. We determine that the ideal case of spheres within a cube versus bi-concave shaped cells within a cylinder affects the shape of the Jaccard index distributions, as well as the range of Jaccard values, showing that both the shape of particle and the domain may play a role. Furthermore, we also find that the distribution is able to capture very similar configurations through Jaccard index values greater than 95% when appending several nearly identical configurations into the data set.

59 BASIC BIOLOGICAL SCIENCES↗

Optimization of a Mixed Fleet of Aerial Drones for Medical Supplies: A Case Study of Blood Delivery Logistics

Aerial drones have emerged as an innovative solution for faster transportation of time-sensitive items (e.g., emergency medical supplies), potentially reducing the transmission of contagious diseases and enhancing healthcare availability through contactless autonomous delivery. We study fleet sizing and efficient scheduling of a mixed fleet of drones for delivering time-sensitive medical items having distinct release and due times to minimize the required fleet size and fleet composition, the required number of additional batteries, and the total energy consumption. We continuously track the remaining battery energy of drones to determine the optimal timing for battery replacement, rather than replacing the battery at each node. Using actual drone flight test data, we employed a machine learning (ML) method to estimate the energy consumption of different drone types during flight segments for different operating parameters. We present a novel mixed-integer programming model to efficiently formulate the problem that integrates the estimated energy consumption functions from ML. We propose a new greedy heuristic (GH) algorithm and a customized genetic algorithm (GA) for solving large-scale instances of this problem faster. Results demonstrate that the GH algorithm is substantially faster than the accelerated CPLEX and the GA, while sacrificing the solution quality by a small amount. Results based on an actual blood sample delivery case study from Pendleton, Oregon, United States, show that using a mixed fleet of drones reduces the total cost and total energy consumption up to 18.18% and 28.7%, respectively, compared to using a homogeneous fleet.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗

Improved measurements of the Dalitz decays η / η ′ → γ e + e −

Based on a data sample of 10 billion J / ψ events collected with the BESIII detector, improved measurements of the Dalitz decays η / η ′ → γ e + e − are performed, where the η and η ′ are produced through the radiative decays J / ψ → γ η / η ′ . The branching fractions of η → γ e + e − and η ′ → γ e + e − are measured to be ( 7.07 ± 0.05 ± 0.23 ) × 10 − 3 and ( 4.83 ± 0.07 ± 0.14 ) × 10 − 4 , respectively. Within the single-pole model, the parameter of electromagnetic transition form factor for η → γ e + e − is determined to be Λ η = ( 0.749 ± 0.027 ± 0.007 ) GeV / c 2 . Within the multipole model, we extract the electromagnetic transition form factors for η ′ → γ e + e − to be Λ η ′ = ( 0.802 ± 0.007 ± 0.008 ) GeV / c 2 and γ η ′ = ( 0.113 ± 0.010 ± 0.002 ) GeV / c 2 . The results are consistent with both theoretical predictions and previous measurements. The characteristic sizes of the interaction regions for the η and η ′ are calculated to be ( 0.645 ± 0.023 ± 0.007 ) fm and ( 0.596 ± 0.005 ± 0.006 ) fm , respectively. In addition, we search for the dark photon in η / η ′ → γ e + e − , and the upper limits of the branching fractions as a function of the dark photon are given at 90% confidence level. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

Unravelling crystal growth of nanoparticles

Crystal growth from nanoscale constituents is a ubiquitous phenomenon in biology, geology and materials science. Numerous studies have focused on understanding the onset of nucleation and on producing high-quality crystals by empirically sampling constituents with different attributes and varying the growth conditions. However, the kinetics of post-nucleation growth processes, an important determinant of crystal morphology and properties, have remained underexplored due to experimental challenges associated with real-space imaging at the nanoscale. Here we report the imaging of the crystal growth of nanoparticles of different shapes using liquid-phase transmission electron microscopy, resolving both lateral and perpendicular growth of crystal layers by tracking individual nanoparticles. We observe that these nanoscale systems exhibit layer-by-layer growth, typical of atomic crystallization, as well as rough growth prevalent in colloidal systems. Surprisingly, the lateral and perpendicular growth modes can be independently controlled, resulting in two mixed crystallization modes that, until now, have received only scant attention. Combining analytical considerations with molecular dynamics and kinetic Monte Carlo simulations, we develop a comprehensive framework for our observations, which are fundamentally determined by the size and shape of the building blocks. Furthermore, these insights unify the understanding of crystal growth across four orders of magnitude in particle size and suggest novel pathways to crystal engineering.

Imaging techniques↗

Validation of Jezebel Reactivity Coefficients and Sensitivity Analysis

Nuclear data validation is often performed today using criticality measurements. The gold standard for criticality measurements is the International Criticality Safety Benchmark Experiment Project (ICSBEP). The validation specifically focuses on the effective multiplication factor ($k_{eff}$). $K_{eff}$ is a relatively easy parameter to infer and has reduced uncertainty due to being at or above critical. However, while $k_{eff}$ is the most documented parameter and its uncertainties and sensitivities have been evaluated in great detail, it cannot be used as a standalone metric to determine inaccuracies in nuclear data (e.g., cross section data, PFNS, nu), which is based on theory, physics, and differential measurements. The Experiments Underpinned by Computational Learning for Improvements in nuclear Data (EUCLID) project aims to identify compensating errors in specific isotope nuclear data by optimally designing experiments that are, or are not sensitive to a suite of measurement parameters beyond $k_{eff}$. By identifying parameters that are sensitive to each other, oppositely sensitive, or have substantial magnitude differences in sensitivity, experiments can be designed to constrain questionable nuclear data. One sensitivity that is of particular interest to this project includes the sensitivity of reactivity coefficients. Reactivity coefficients compare reactivity, which is related to $k_{eff}$ at two different states therefore being sensitive to small changes in the system. The most common type of reactivity coefficient measurements is comparison to void for a small sample within the assembly. It is key that the sample sizes are small enough to not affect the flux of the full system. Reactivity coefficients were evaluated for many early experiments to better understand transport corrected cross sections. In fact, ICSBEP includes reactivity coefficient results as “Supplemental Measurements” in appendices for a handful of older benchmarks. One of those benchmarks is Jezebel, the bare Pu critical assembly. This paper compares new simulations of reactivity coefficients for Jezebel, and explores the sensitivity of reactivity coefficients to small changes in nuclear data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Anatomical Fraction segmentation in the biomass bales

The U.S. Department of Energy Bioenergy Technologies Office (BETO) is committed to the development of sustainable, nationwide, commercial biofuel production to displace petroleum-derived fuels, increase domestic energy production, and encourage the creation of a domestic bioenergy and bioproducts industry. Operating a commercial-scale bioenergy operation requires significant technological advancements for determining biomass feedstock quality during the preprocessing stage. Usage of non-food feedstocks- e.g., corn-stover, pine residue, and forest residue - at the biorefineries reduces strain on the food supply chain. But the non-food feedstock heterogeneity- physical size, shape, and chemical composition-poses a significant challenge during milling, conveyance, feeding, and biofuel conversion processes. 3D X-Ray imaging (CT) is capable of distinguishing material features by detecting density and compositional differences. But the inherent complexity introduced during harvesting and bailing makes the reconstruction and interpretation of baled biomass materials from x-ray data time consuming, laborious, and expensive. Feedstocks are low-density materials that produce small contrast differences in the x-ray images. This paper focuses on using the shape and texture properties, using 3D image processing techniques like 3D skeletonization, directional statistics to characterize and extract volumetric content of the different tissue samples in the biomass bales.

09 BIOMASS FUELS↗

Properties and microstructure evolution of silicon nitride and zirconium nitride following Ni ion irradiation

We report that silicon nitride and zirconium nitride have been proposed as potential materials for multiple nuclear applications (inert matrix fuels, accident tolerant fuels, space nuclear power, fusion reactor design), yet knowledge on their behavior under irradiation remains limited. Ion irradiations were performed using 15 MeV Ni 5+ ions on Si 3 N 4 and ZrN samples, with midrange doses (around 3 µm) from 1 to 50 dpa and temperatures from 300 to 700°C. Volumetric lattice swelling was determined by grazing incidence X-ray diffraction, defect production and evolution were tracked using Transmission Electron Microscopy, and nanoindentation was performed to quantify the ceramics’ mechanical properties evolution. The results from these irradiation studies on nitride ceramics help fill the current gap present in the literature. Behavior consistent with past work on irradiated Si 3 N 4 was observed with respect to mechanical properties and defect formation up to 15 dpa and 500°C. Failure of the grain boundary sintering aid in Si 3 N 4 was observed above these conditions. Different behavior was observed in both nitrides at 50 dpa and 700°C, where lattice swelling increased past potential saturation values. Unreported cavity formation was witnessed in both materials under all irradiation conditions, with stable number density and slight size increase above 15 dpa. The mechanism for the cavity formation remains to be determined.

36 MATERIALS SCIENCE↗

Tailoring additive manufacturing to optimize dynamic properties in 316L stainless steel

With the advent of additive manufacturing, manipulation of typical microstructural elements such as grain size, texture, and defect densities is now possible at a faster time scale. While the processing–structure–property relationship in additive manufactured metals has been well studied over the past decade, little work has been done in understanding how this process affects the dynamic behavior of materials. We postulate that additive manufacturing can be used to alter the material microstructure and used to enhance its dynamic strength. In this work, 316L stainless steel (SS) was manufactured via selected laser melting and its microstructure was altered through changing build parameters like laser power, speed, and hatch spacing systematically. These samples were then subjected to spall recovery experiments to measure the spall strength and quantify the amount of damage as a function of build parameters. By mapping the spall strength as a function of build parameters, this work demonstrated that indeed additive manufacturing can be used to tailor the spall strength of 316L SS. This work also determined the optimum build parameters (laser power=195W; scanning speed=1083mm/s; hatch spacing=0.09mm; layer thickness=0.02mm) to obtain the highest spall strength and the least amount of total damage in 316L SS. Microstructural characterization of the pre- and post-mortem samples revealed that increased grain average misorientation and textural index were the main driving force behind this higher spall strength. This work aims to enhance microstructural engineering techniques to design materials with greater resistance to dynamic shock loading.

36 MATERIALS SCIENCE↗

Cesium Removal and Hydraulic Performance Comparisons of CST Ion Exchange Media Batches in Support of the Tank Closure Cesium Removal Project - 20522

Three batches of Crystalline Silicotitanate (CST) ion exchange media have been evaluated for cesium removal efficiency from a Savannah River Site (SRS) High Level Waste (HLW) supernate simulant in support of the Tank Closure Cesium Removal (TCCR) Project, which involves at-tank column waste treatment. Results will be utilized to select the CST media batch to be added to the next TCCR unit columns. Two of the CST media samples were recent production batches and the third was an archived batch studied extensively at SRS nearly two decades ago. The archived CST batch had a significantly smaller average particle diameter than more recent batches. Small-scale (∼23 mL), side-by-side column tests were conducted at 35 deg. C with each of the CST batches using the same simulant at flow rates near 1.2 mL/min (3.0-3.4 CST bed volumes/hr). The cesium ion exchange column performance results were lower than expected for all three CST batches, but the data indicated that 30% more simulant volume and 40% more equivalent CST bed volumes of solution can be processed with the older CST batch prior to reaching the 50% cesium breakthrough point than can be processed with the newer CST batches. Hydraulic evaluations of the CST columns were also conducted in simulant at 24 deg. C to determine the impact of the different particle size distributions and associated bed porosities on frictional pressure drop under dynamic flow conditions. Higher differential pressure drops were observed with the archived CST batch relative to recent production batches, due to the smaller particle size distribution and the packing characteristics of the archived batch. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Experimental and theoretical study of hole scattering in RF sputtered p-type Cu 2 O thin films

One of the key materials of interest for p-type oxide semiconductor thin film electronics is cuprous oxide (Cu 2 O), due to its relatively high hole mobility. Here, in this work, we use experiments, analytical models, and density functional theory calculations to study the scattering mechanisms that determine Hall mobility in two Cu 2 O samples. First, we examine a polycrystalline Cu 2 O thin film deposited by RF magnetron sputtering, and second, a single-crystalline Cu2O bulk substrate. Temperature-dependent Hall measurements indicate that neutral impurity and grain boundary scattering are dominant for the polycrystalline Cu 2 O thin film, while phonon scattering is dominant for single-crystalline Cu 2 O. Our first-principles calculations show that the room-temperature intrinsic hole mobility of Cu 2 O is 106 cm 2 V –1 s –1 , indicating the great promise of the material for p-type electronic devices. This intrinsic mobility is limited by phonon scattering, with the most dominant scattering modes having phonon energies of 88.4 and 17.1 meV. These results indicate that the key pathways to increase the hole mobility in Cu 2 O thin films are by reducing the impurity concentration and by increasing grain size. Our work thus sets the stage for the future development of high performance Cu 2 O-based p-type thin film transistors.

36 MATERIALS SCIENCE↗