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Np-237 LoD Measurement by TIMS-Multi-Ion Counting Total Evaporation [Poster]
Requests for ultra-low-level 237 Np analyses highlight the importance of a robust chemical purification and measurement technique for Np. In FY2022, LANL is quantifying the instrumental 237 Np LoD. Need to incorporate a chemical purification procedure for TIMS-MICTE sample preparation. What is the recovery of the chemical purification procedure? What is the ultimate detection limit that can be achieved while incorporating a chemical purification procedure? We have adapted and refined the Pu TIMS-MICTE method for Np analyses. We have determined expected uncertainties for 237 Np TIMS-MICTE measurements. We have increased sensitivity through technique improvements. We have improved method reliability for Np analyses and increased throughput. Apply knowledge gained from progress made in FY2022 to further develop Np sample purification and analyses by TIMSMICTE.
Modification and Modeling of a Silicon Photomultiplier for Reduced High Temperature Dark Count Rate.
Abstract not provided.
Counting Calories: Light Yield Studies for ADRIANO Calorimeter Prototype
To estimate the light yield for ADRIANO prototype, we must calibrate the light sensors as well as collect data from beams of known properties. Future experiments searching for new physics require special calorimetric techniques to detect new particles. ADRIANO2(A Dual Readout Integrally Active Non-segmented Option) is one such technique. Several prototypes have been tested at Mtest Facility at Fermi National Accelerator Laboratory in the last few years. This work consisting of new and more refined analysis of the data taken with the intent of improving the understanding of this calorimeter.
Counting Neutrons: A Case Study from the Nuclear Weapons Enterprise
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Low-Rank Models for Tensor Count Data Corrupted by False Zeros
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BB-CVXOPT: Basic Block Execution Count Estimation and Extrapolation using Constrained Convex Optimization
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Microfabricated Ion Traps on Sapphire for Larger Trap Areas and Higher Qubit Count
Surface ion traps are a promising platform for quantum computing due to their potential to store large numbers of ions that can be addressed by electrical and optical control signals in order to implement quantum algorithms. Increasing the power of the quantum computer requires increasing the number of ions, but this poses a significant challenge in that it leads to a non-linear increase in on-chip power dissipation. The primary contributor to this power scaling in current devices is the capacitance between the radio frequency (RF) electrode and the metal plane that shields the silicon substrate from the RF signals applied to it. Silicon has traditionally been chosen for the substrate material for compatibility with the processing required for multi-metal-level traps. In this work, we address these capacitance and fabrication challenges by replacing the commonly used silicon substrate with an insulating sapphire substrate to fabricate a multi-metal-level ion trap, while still employing common semiconductor manufacturing techniques. This change in substrate allows the design to remove the metal shielding from the device design, reducing the capacitance of the RF electrode. The electrical characteristics of these traps were measured, specifically trap impedance, capacitance, and voltage breakdown, and compared to nearly identical silicon trap devices. Finally, we used laser cutting techniques to shape a sapphire wafer into bowtie shapes matching silicon traps previously fabricated at Sandia National Labs to explore solutions for integrating sapphire substrates into non-rectangular ion trap designs.
Examining Microalgae Growth with Respect to Cell Count and Salinity
In recent years, microalgae have been identified as potential source of biofuel due to their ability to grow abundantly in little time. As photosynthetic organisms, microalgae only need water, light, micronutrients, and carbon dioxide to yield algal biomass. Several applications for this biomass are being studied, such as the extraction of biofuel (Zhang et al. 2022) as well as wastewater treatment (Rude et al. 2022). Two specific microalgae species have been identified as uniquely prolific: Picochlorum celeri, a saltwater species, and Chlorella sorokiniana 1116, a freshwater species. Both species showcased survival in less-than-ideal conditions and showcased hardiness in their respective waters (Krishnan et al. 2021), making them popular specimen to be studied for a variety of applications. This project involved two components, the first component focusing on the development of a growth curve for P. celeri and the second studying varying salt concentration in both species.
Ratio of 1,275 and 186 keV Gamma Ray Count Rates for Age Determination of Material in UF 6 Cylinders
In this work, a method for using ratios of passive gamma ray measurements to determine the time since the filling of UF 6 cylinders was explored. This method uses the 186 keV gamma ray emitted by 235 U and the 1,275 keV gamma ray that results from interactions of alpha particles in fluorine. Studies were made using MCNP models of both 30B cylinders and smaller 5A cylinders. Results indicate that for enrichments at or above that of natural uranium, this approach may provide a method for determining age up to 10 years or identifying whether the age is greater than 10 years, even if the uranium enrichment is unknown. The calculated results show the same behavior as the results of a recent measurement campaign, indicating the possibility of using this method for real-world cylinders.
Multi-Metal Patterned Transmission Targets for Improved Photon Counting CT Imaging
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Quantum Approximate Counting with Additive Error: Hardness and Optimality
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A Short-Lived Isotope Counting System (SLICS) to measure reaction cross sections producing light, beta-decaying nuclei on OMEGA
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Scaling Factors for Single Event Upsets with High Error Counts
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Macro-driven GEANT4 Application for the Nuclear Counting Facility at Lawrence Livermore National Laboratory
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Extrapolation of the Rainflow-Counted Load Ranges for Fatigue Assessment of the Wind Turbine's Blades
Wind turbine design standards recommend the use of statistical modeling coupled with extrapolation of the short-term load data to long-term periods for fatigue reliability assessment. However, statistical error and computational expense can limit the accuracy of such approaches. In the case of wind turbine blades, the errors are more significant because of the high material fatigue exponent that makes the damage estimations more sensitive to variations. In addition, due to different excitation sources, the flapwise load range histogram is not unimodal, and thus its statistical modeling is complex. In the present work, we provide three methods for statistical modeling of the flapwise bending moment ranges including a novel approach based on frequency-based separation of the modes. The first two methods are simplified approaches for modeling the most crucial load ranges using unimodal distributions and the third method involves multimodal distribution fitting. The research is based on 3600 10-minute aeroelastic simulations of DTU 10MW case study wind turbine from which a benchmark damage equivalent load (DEL) is calculated. The DEL calculated by each of the three proposed methods is compared to this reference. The results show that the conventional approach based on using 6 seeds as well as using mixture models fitted on the limited data lead to under-conservative results with errors up to 23%. On the other hand, the simplified unimodal approaches provided in this work can provide conservative estimations of the fatigue damage with mean values 5% and 12% higher than the benchmark. However, the variability of the DEL estimates is higher when using unimodal extrapolation of the load ranges, and the data can be conservative by 17.5%. The proposed unimodal fits suggested for modeling and extrapolation of the blade's load ranges provide less errors relatively and most importantly conservative DEL estimations while maintaining computational efficiency.
Soil viral production count, respiration, and amplicon data
This study aimed to quantify rates of viral production in aridisol soil under conditions as close to natural field soil as possible given the perturbations necessary to manipulate viral abundances. Viruses were removed from soil, then added back to virus-depleted soil to control the initial viral abundances at either 100% (field_abund) or 10% (reduced_abund) of measured field viral abundance to generate treatments with field-relevant and reduced viral infection pressure, respectively. Replicates of batch incubation jars were harvested every 8 hours for 48 hours to enumerate bacteria and viruses by microscopy (n=5) and profile bacterial community composition by 16S rRNA amplicon sequencing (n=3).