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At least 19 records

Computationally Guided Design of Multiple Impurities Tolerant Electrode (Final Report)

The current project was based on a combined experimental and computational approach, which can help recommend better cathode materials under multiple impurities conditions. The PI will mainly take in charge of experimental and computational thermodynamics of the selected cathode materials for the SOFC applications under multiple impurities. While the co-PI will run the electrochemical tests of the cathodes recommended and eventually the long-term degradation tests. At the end of the project, a multiple tolerant cathode material based on the combined experimental and computational approach will be recommended and the reliability of the commonly used accelerated testing will be evaluated. It will address multiple impurities poisoning effect of SO2, CO2, Cr and H2O on the LSM, LSCF and LNO cathodes by identifying the formation of the detrimental secondary phases by XRD, SEM and TEM techniques. And further recommended cathode material will be subjected to electrochemical testing and the most promising ones will be applied to long-term tests. The hybrid approach the PI proposed will not only be applied to the design of multiple impurities tolerant cathodes but will also be considered in the future oxygen electrode applications in SOECs or reversible SOCs. This hybrid computational and experimental approach includes four sections: 1) Investigation of single impurity poisoning on LSM, LSCF and LNO cathodes in the presence of SO2, CO2, Cr. In this section, LSM, LSCF cathodes from FuelCellMaterials and LNO cathodes from Sol-Gel synthesis will be heat-treated in the above single impurity. And the formation of the secondary phases as well as the corresponding simulations will be cross compared, which shows good agreement between each other. Meanwhile, the accelerated testing approach will be evaluated in these systems compared with the previous published work to understand the reliability of the approach. 2) Investigation of multiple impurities poisoning on LSM, LSCF and LNO cathodes in the presence of Cr+H2O, SO2+Cr and SO2+Cr+H2O conditions. We have also applied these 3 candidate cathodes under these multiple impurities’ conditions and the long-term degradation mechanism of the multiple impurities will be understood with the help of the combined experimental and computational approach. Meanwhile, the synergistic effect of those impurities will be compared with the individual ones in the same cathode system to further reveal the actual operating conditions. 3) Electrochemical testing and polarization of the recommended cathode. We have demonstrated very low polarization resistance in LSCF (core)-LSM (shell) electrodes using MSD process and analyzed impedance spectra using DRT analysis and confirming that the low polarization resistance in LSM infiltrated MSD cells is due to reduction in polarization resistance associated with O2-adsorption process. 4). Long-term degradation testing. We have developed a versatile MSD-based process to deposit various continuous coatings onto porous scaffolds and established baseline for longer term Cr-impurity testing in future projects.

36 MATERIALS SCIENCE↗

Computationally Guided Design of Multiple Impurities Tolerant Cathode for Solid Oxide Fuel Cell Applications

Solid oxide fuel cells (SOFCs) have been recognized as promising candidates in the demand of reducing the dependence on fossil fuels, which is one of the solutions to the threat of global warming. It was reported that the direct chemical-to-electrical energy conversion in SOFCs comes with negligible emission of greenhouse gases and up to 60% working efficiency. SOFC has unique advantages over traditional power generation technologies and other types of fuel cells due to the use of relatively inexpensive materials, low sensitivity to poisoning impurities in fuels, relatively high conversion efficiency, and fuel flexibility (like carbon-based fuels). However, during the SOFC operation, the cathode is exposed to intrinsic and extrinsic airborne contaminants at high temperatures (600–900°C), leading to their reaction with electrode materials, irreversible chemical and structural changes, and electrochemical performance degradation. of which CO2, SO2, Cr6+ and H2O are known to be concerns. Thus, developing a comprehensive understanding of the multiple impurities poisoning of SOFC cathodes in the presence of single or multiple impurities is necessary to address the long-term degradation of the SOFC cathode systems at operating conditions. An integrated computational and experimental approach has been utilized in the current work aiming at the comprehensive investigation of the cathode materials under single or multiple impurities poisoning effects, understanding the multiple impurities poisoning mechanism(s), and improving the long-term durability of the SOFC cathodes to develop better performing impurity-tolerant cathode materials. We first examined the agreement between the simulation approach and the experimental observations at various atmospheric and temperature conditions to confirm the reliability of CALPHAD for poisoning simulations in these cathodes. Then, using this approach, we investigated the accelerated testing protocol, which has become the standard method for conducting impurity poisoning experiments involving these cathode materials. We found our simulation approach is able to predict in which systems, i.e., cathode material and treatment environment, the accelerated testing protocols reflect actual operating conditions. Finally, in-depth simulations were done for these three candidate cathodes under different experimental conditions and suggested directions toward alternative cathode materials that have superior impurity tolerance.

36 MATERIALS SCIENCE↗

Steady-state properties of multi-orbital systems using quantum Monte Carlo

A precise dynamical characterization of quantum impurity models with multiple interacting orbitals is challenging. In quantum Monte Carlo methods, this is embodied by sign problems. A dynamical sign problem makes it exponentially difficult to simulate long times. A multi-orbital sign problem generally results in a prohibitive computational cost for systems with multiple impurity degrees of freedom even in static equilibrium calculations. Here, we present a numerically exact inchworm method that simultaneously alleviates both sign problems, enabling simulation of multi-orbital systems directly in the equilibrium or nonequilibrium steady-state. The method combines ideas from the recently developed steady-state inchworm Monte Carlo framework [Erpenbeck et al., Phys. Rev. Lett. 130, 186301 (2023)] with other ideas from the equilibrium multi-orbital inchworm algorithm [Eidelstein et al., Phys. Rev. Lett. 124, 206405 (2020)]. We verify our method by comparison with analytical limits and numerical results from previous methods.

Chemistry↗

Sticking Coefficients of Fusion Reactor Impurities from Molecular Dynamics Simulations for the Design of Cryopumps

A cryopump can be utilized as an impurity removal component of a direct internal recirculation (DIR) system for the fusion fuel cycle. The DIR facilitates a low fuel inventory by continuously pumping unburnt fuel while removing impurities from the fusion exhaust stream. A cryopump can target multiple impurity species by maintaining a temperature lower than the gas triple-point temperature that promotes desublimation. The desublimation/condensation of gases in cryopumps can be characterized by the sticking coefficient, which is defined as the probability for a gas particle to stick to a (cryo-)surface upon collision. The sticking coefficient is one of the important design/operation parameters for cryopumps, and it depends on a variety of surface and gas properties. Here, in this study, molecular dynamics simulations were utilized to estimate the sticking coefficients of typical fusion gas impurity species N 2 , CO 2 , and CH 4 over a Cu surface for a range of gas temperatures and surface coverages. The molecular dynamics study showed that the sticking coefficients for gases decrease with an increase in gas temperature. The presence of a single full monolayer of condensate on the metallic surface showed an adverse effect on the sticking of gases; however the sticking improved with two full monolayers of condensate on the surface. The sticking of gases over the mixed condensate on a surface was more favorable than the condensate of the same species for N 2 and CH 4 , with an exception for CO 2 , which showed a decrease in sticking over the mixed condensate.

cryopump↗

A GPU ‐Accelerated 3D Unstructured Mesh Based Particle Tracking Code for Multi‐Species Impurity Transport Simulation in Fusion Tokamaks

ABSTRACT This paper presents the multi‐species global impurity transport capability developed in a GPU‐accelerated fully 3D unstructured mesh‐based code, GITRm, to simultaneously track multiple impurity species and handle interactions of these impurities with mixed‐material surfaces. Different computational approaches to model particle‐surface interaction or surface response have been developed and compared. Sheath electric field is taken into account by employing a fast distance‐to‐boundary calculation, which is carried out in parallel on distributed or partitioned meshes on multiple GPUs without the need for any inter‐process communication during the simulation. Several example cases, including two for the DIII‐D tokamak, that is, one with the SAS‐V divertor and the other with the collector probes, are used to demonstrate the utility of the current multi‐species capability. For the DIII‐D probe case, the capability of GITRm to resolve the spatial distribution of particles in localized regions, such as diagnostic probes, within non‐axisymmetric tokamak geometries is demonstrated. These simulations involve up to 320 million particles and utilize up to 48 GPUs.

Nath, Dhyanjyoti D. [Scientific Computation Resear↗

Impurity leakage and radiative cooling in the first nitrogen and neon seeding study in the closed DIII-D SAS configuration

A comparative study of nitrogen versus neon has been carried out to analyze the impact of the two radiative species on power dissipation, SOL impurity distribution, divertor and pedestal characteristics. The experimental results show that N remains compressed in the divertor, thereby providing high radiative losses without affecting the pedestal profiles and displacing carbon as dominant radiator. Neon, instead, radiates more upstream than N thus reducing the power flux through the separatrix leading to a reduced ELM frequency and compression in the divertor. A significant amount of neon is measured in the plasma core leading to a steeper density gradient. The different behavior between the two impurities is confirmed by SOLPS-ITER modeling which for the first time at DIII-D includes multiple impurity species and a treatment of full drifts, currents and neutral–neutral collisions. The impurity transport in the SOL is studied in terms of the parallel momentum balance showing that N is mostly retained in the divertor whereas Ne leaks out consistent with its higher ionization potential and longer mean free path. This is also in agreement with the enrichment factor calculations which indicate lower divertor enrichment for neon. The strong ionization source characterizing the SAS divertor causes a reversal of the main ions and impurity flows. The flow reversal together with plasma drifts and the effect of the thermal force contribute significantly in the shift of the impurity stagnation point affecting impurity leakage. This work provides a demonstration of the impurity leakage mechanism in a closed divertor structure and the consequent impact on pedestal. Since carbon is an intrinsic radiator at DIII-D, in this paper we have also demonstrated the different role of carbon in the N vs Ne seeded cases both in the experiments and in the numerical modeling. Here, carbon contributes more when neon seeding is injected compared to when nitrogen is used. Finally, the results highlight the importance of accompanying experimental studies with numerical modeling of plasma flows, drifts and ionization profile to determine the details of the SOL impurity transport as the latter may vary with changes in divertor regime and geometry. In the cases presented here, plasma drifts and flow reversal caused by high level of closure in the slot upper divertor at DIII-D play an important role in the underlined mechanism.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multi-atom quasiparticle scattering interference for superconductor energy-gap symmetry determination

Complete theoretical understanding of the most complex superconductors requires a detailed knowledge of the symmetry of the superconducting energy-gap Δ$^α_k$, for all momenta k on the Fermi surface of every band α. While there are a variety of techniques for determining |Δ$^α_k$|, no general method existed to measure the signed values of Δ$^α_k$. Recently, however, a technique based on phase-resolved visualization of superconducting quasiparticle interference (QPI) patterns, centered on a single non-magnetic impurity atom, was introduced. In principle, energy-resolved and phase-resolved Fourier analysis of these images identifies wavevectors connecting all k-space regions where Δ$^α_k$ has the same or opposite sign. But use of a single isolated impurity atom, from whose precise location the spatial phase of the scattering interference pattern must be measured, is technically difficult. Here we introduce a generalization of this approach for use with multiple impurity atoms, and demonstrate its validity by comparing the Δ$^α_k$ it generates to the Δ$^α_k$ determined from single-atom scattering in FeSe where s ± energy-gap symmetry is established. Finally, to exemplify utility, we use the multi-atom technique on LiFeAs and find scattering interference between the hole-like and electron-like pockets as predicted for Δ$^α_k$ of opposite sign.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Impurity gas detection for SNF canisters using probabilistic deep learning and acoustic sensing *

Abstract Monitoring impurity gases in spent nuclear fuel (SNF) canisters is a novel structural health monitoring approach for SNF in dry storage. The SNF canisters are sealed containers that do not facilitate visual access to the inside. Acoustic sensing can be deployed by taking advantage of the pathways unobstructed by internal hardware. Although the ultrasonic time-of-flight measurement can provide valuable information, it is limited in its ability to discern the concentration of only one impurity gas. As such, deep learning algorithms, particularly convolutional neural networks (CNNs), offer a promising solution. In this study, CNN-based probabilistic deep learning models were implemented to detect and quantify multiple impurity gases in helium. An experimental platform was established to simulate canister conditions, and ultrasonic test data were collected. The presence of argon and air in helium at concentrations ranging from 0% to 1.2% at increments of 0.05% was considered. The multi-layer perceptron, decision tree, and logistic regression classifiers achieved high accuracies when distinguishing pure helium from helium with impurities. CNN with dropout layers and CNN using maximum likelihood estimation showed a similar performance, indicating their ability to capture uncertainties. The ensemble CNN model exhibited improved predictions and the ability to balance individual gas concentration by integrating 1D- and 2D-CNN models. These findings contribute probabilistic deep learning solutions for impurity gas detection and analysis within SNF canisters, thus ensuring safe storage and management of SNFs.

47 OTHER INSTRUMENTATION↗

Hydrogen Detection Strategies to Support H2@SCALE - The NREL Sensor Laboratory

Hydrogen represents a major pathway to decarbonize and stabilize the national and international energy industry and select manufacturing markets. To facilitate the development of hydrogen markets, the US Department of Energy initiated H2@Scale to bring together stakeholders to advance affordable hydrogen production, transport, storage, and utilization to increase revenue opportunities in multiple energy sectors. One major impediment to hydrogen implementation is cost. To expedite the use of hydrogen in energy and other markets, the United States announced in 2021 the Hydrogen Shot, which seeks to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). As the cost of hydrogen drops, new applications will emerge that will require unique configurations of existing equipment and infrastructure, and eventually lead to advances in the generation and utilization of hydrogen. As the hydrogen economy expands, sensors and detection methods will need to adapt to changing infrastructure demands to address the primary targets of health & safety, emissions monitoring, and process control. The NREL Sensor Laboratory is playing a pivotal role in advancing the use of hydrogen sensors and detection methodologies in each of these categories to support DOE's mission for safe and efficient utilization in emerging markets. Health & safety monitors are required to ensure that operators and facilities can react to unintended hydrogen releases, either as GH2, LH2, or as a constituent of blends (e.g., natural gas or ammonia). Current detection methodologies focus on safety applications to detect near its lower flammable limit (4 vol %), and typically include point sensors in applications such as fixed or mobile detectors (e.g., personal gas monitors). Methodologies amenable for area detection include acoustic, emerging optical imaging methods, and flame detectors. Comparable detection strategies can be utilized for emissions monitoring and quantization, however few methods can simultaneously cover both low (emissions) and high (health & safety) levels. Deployment of emission level detectors will be required to 1) reduce product loss through small but potentially significant leaks from an environmental or cost perspective, 2) reduce downtime of high demand systems by early identification of eminent system failures (leaks through pump or compressor seals indicative of impending failure), and 3) address potential emission monitoring requirements that may be set by regulating bodies. The first two points should be adopted by industry to reduce the cost-of-goods-sold. The third main category for hydrogen detection relates to process control and may be advantageous for many existing applications. Two main applications are emerging. For example, the purity requirements for hydrogen that is dispensed from refueling systems for hydrogen fuel cell electric vehicles (FCEV) is rigorously regulated by the Standard SAE J2719, which prescribes maximum allowable levels of multiple impurities in the hydrogen fuel and must be verified by a regulatory body. Hydrogen contaminant detectors (HCD) integrated to the fueling station can assure this compliance. HCDs must be able operate in 100% H2 backgrounds and be able to distinguish between multiple contaminants at low ppm to low ppb levels. Secondly, as a strategy to decarbonize the natural gas grid, there are proposals to blend hydrogen with natural gas. This blending will affect transport applications (pipeline infrastructure), stationary combustion systems (turbines), and consumer and commercial appliances. In the short-term, hydrogen levels up to 20% are proposed. Variations in the hydrogen level can have dramatic impact on the combustion process and on the potential response of safety sensors. These mixtures may be regulated so that the concentration at a delivery point must be monitored with high precision. However, routine maintenance may introduce background gases such as ambient air (with water) or maintenance gases (introduced with welding processes or adhesive outgassing.) Therefore, the detection methodology must be robust enough to recover or respond to various contaminants. Several reviews can be found in literature addressing sensing and detection technologies, including their limitations and applications. However, for most applications, limitations can be alleviated by combining various detection techniques either through system integration or implementation of machine learning methods (artificial intelligence). In this presentation, we will discuss several applications, highlight their current approach for hydrogen detection, and suggest detection strategies to supplement their limitations.

ENERGY STORAGE,HYDROGEN↗

Visible core spectroscopy at Wendelstein 7-X

This paper presents an overview of recent hardware extensions and data analysis developments to the Wendelstein 7-X visible core spectroscopy systems. These include upgrades to prepare the in-vessel components for long-pulse operation, nine additional spectrometers, a new line of sight array for passive spectroscopy, and a coherence imaging charge exchange spectroscopy diagnostic. Progress in data analysis includes ion temperatures and densities from multiple impurity species, a statistical comparison with x-ray crystal spectrometer measurements, neutral density measurements from thermal passive Balmer-alpha emission, and a Bayesian analysis of active hydrogen emission, which is able to infer electron density and main ion temperature profiles.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Sulfur poisoning mechanism of LSCF cathode material in the presence of SO 2 : a computational and experimental study

Aiming at the comprehensive understanding of the single sulfur poisoning effect and, eventually, the multiple impurities poisoning phenomena on the SOFC (Solid Oxide Fuel Cell) cathode materials, the sulfur poisoning effect on the (La 0.6 Sr 0.4 ) 0.95 Co 0.2 Fe 0.8 O 3 (LSCF-6428) has been investigated in the presence of 10 ppm SO 2 at 800, 900, and 1000°C, respectively, with a combined computational and experimental approach. The good agreement between the CALPHAD (Computer Coupling of Phase Diagrams and Thermochemistry) simulations and the XRD (X-Ray Diffraction), SEM (Scanning Electron Microscopy), and TEM (Transmission Electron Microscopy) characterization results support the reliability of the CALPHAD approach in the SOFC field. Furthermore, comprehensive simulations were made to understand the impact of temperature, P(SO 2 ), P(O 2 ), and Sr concentration on the threshold of SrSO 4 stability. Results showed that the formation of SrSO4 is thermodynamically favored at lower temperatures, higher P(SO 2 ), higher P(O 2 ), and higher Sr concentration. Finally, comparisons were also made between LSCF-6428 and LSM20 (La 0.8 Sr 0.2 MnO 3 ) using simulations, which confirmed that LSCF-6428 is a poor sulfur-tolerant cathode, in agreement with the literature.

36 MATERIALS SCIENCE↗

Fine Gradient Electrode and Micro Porous Layer Structures for Improved Heavy Duty Fuel Cells (Final Report)

The commercial deployment of Heavy Duty Fuel Cells(HDFC) for applications such as large trucks (for example, Class 8 capable of carrying 50,000 lb. loads) depends vitally on achieving high efficiency and durability at reasonable costs. Furthermore, the HDFC must operate under practical conditions such as with fuel and air impurities, multiple stop-start cycles, and under the extremes of climate our planet offers – from hot and cold to dry and wet. These conditions place a premium on the stability and utilization of the materials comprising the membrane electrode assemblies (MEAs) powering the fuel cell. and the current catalysts, MicroPorous Layers, and Electrode structures and additives are insufficient for these needs. In Phase I Pajarito and Advent will develop durable electrocatalysts, MicroPorous Layer and electrode additives, and electrode structures for heavy duty fuel cells designed for zero-emission long-haul trucking. The electrocatalyst products are designed to solve the challenging durability and performance needs of fuel cells designed for long life and high efficiency through a combination of uniquely structured designed catalysts as well as new MicroPorous Layers (MPLs) and electrode structure additives. These improved materials will provide Pajarito both an expanded commercial opportunity in electrocatalysts, as well as new markets for MPL and electrode additives. The resulting public benefits include improved economics of fuel cells, a leading zero-emission technology for mobility, as well as reduced reliance on the critical minerals and metals used in the heavy-duty trucks industry. Possible follow-up Phase II and III projects would add full MEA products based on the Phase I efforts catalysts and additives, with full system validation by leading Fuel Cell Truck developers.

08 HYDROGEN↗

Impurity Monitoring During Multiple Recycles of Mo Targets for Accelerator-Produced Mo-99

Accelerator-based methods have been developed to produce kilocurie quantities of low specific-activity 99 Mo from Mo targets. The irradiation of enriched 100 Mo, in place of nat Mo, greatly reduces the activity of side-reaction products formed from other Mo isotopes, which have a fairly wide distribution of natural isotopic abundances: 92 Mo (14.8%), 94 Mo (9.3%), 95 Mo (15.9%), 96 Mo (16.7%), 97 Mo (9.5%), and 98 Mo (21.4%). The side-reaction impurities of chief concern are 91m Nb and 88 Zr/ 88 Y (from 92 Mo), 92m Nb (from 94 Mo), and 95 Nb, 96 Nb, and 97 Nb (from 98 Mo). The new production technologies also require new chemical processing and purification schemes that emphasize low-waste recycling of the expensive, enriched Mo material.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Tracer Study on sCO2 Corrosion with Multiple Oxygen-Bearing Impurities

Abstract Several modern power production systems utilize supercritical CO 2 (sCO 2 ), which can contain O 2 and H 2 O as impurities. These impurities may degrade the compatibility of structural alloys through accelerated oxidation. However, it remains unclear which of these impurities plays a bigger role in high-temperature reactions taking place in sCO 2 . In this study, various model and commercial Fe‐ and Ni‐based alloys were exposed in 300 bar sCO 2 at 750 °C to low levels (50 ppm) of O 2 and H 2 O for 1,000 h. 18 O-enriched water was used to enable the identification of the oxygen source in the post-exposure characterization of the samples. However, oxygen from the water did not accumulate in the scale, which consisted of Cr 2 O 3 in the cases where a protective oxide formed. A 2wt.% Ti addition to a Ni-22%Cr model alloy resulted in the formation of thicker oxides in sCO 2 , while a 1wt.% Al addition reduced the scale thickness. A synergistic effect of both Al and Ti additions resulted in an even thicker oxide than what was formed solely by Ti, similar to observations for Ni-based alloy 282.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Carbon complexes in highly C-doped GaN

We investigate the properties of heavily C-doped GaN grown by hydride vapor phase epitaxy using both optical experiments and hybrid density functional theory calculations. Previous work has established that carbon acceptors (C N ) give rise to a yellow luminescence band near 2.2 eV along with a blue luminescence band near 2.9 eV. Photoluminescence measurements show the yellow band shifting as a function of carbon concentration, suggesting a change in the behavior of carbon species as carbon content increases. With hybrid density functional theory we calculate the electrical and optical behavior of carbon centers containing multiple carbon impurities, which may arise in heavily doped material. We compare the behavior of these complexes to the isolated centers, and find that the dicarbon donor-acceptor (C Ga –C N ) complex is a candidate to explain the shift in the yellow luminescence peak. Tricarbon complexes have high formation energies and modest binding energies, and also give rise to optical transitions that are inconsistent with the observed spectra. We also identify the split dicarbon interstitial on the gallium site as a low-energy species with a large binding energy that may act to compensate carbon acceptors. Here, local vibrational modes are calculated for carbon impurity centers, and we compare these results to recent experiments. Dicarbon and tricarbon complexes involving C Ga and C N exhibit modes that are only slightly higher than the isolated species, while carbon interstitials and related complexes give rise to vibrational modes much higher than C Ga and C N .

36 MATERIALS SCIENCE↗

Laboratory multiple-crystal X-ray topography and reciprocal-space mapping of protein crystals: influence of impurities on crystal perfection

Double-axis multiple-crystal X-ray topography, rocking-curve measurements and triple-axis reciprocal-space mapping have been combined to characterize protein crystals using a laboratory source. Crystals of lysozyme and lysozyme crystals doped with acetylated lysozyme impurities were examined. It was shown that the incorporation of acetylated lysozyme into crystals of lysozyme induces mosaic domains that are responsible for the broadening and/or splitting of rocking curves and diffraction-space maps along the direction normal to the reciprocal-lattice vector, while the overall elastic lattice strain of the impurity-doped crystals does not appear to be appreciable in high angular resolution reciprocal-space maps. Multiple-crystal monochromatic X-ray topography, which is highly sensitive to lattice distortions, was used to reveal the spatial distribution of mosaic domains in crystals which correlates with the diffraction features in reciprocal space. Discussions of the influence of acetylated lysozyme on crystal perfection are given in terms of our observations.

Muramidase/chemistry↗

Unique & challenging aspects of plutonium metal standards exchange program for actinide measurements

The Los Alamos National Laboratory exchange program is the only program of its kind for the distribution of plutonium (Pu) standards materials with a range of impurity contents to multiple laboratories for destructive measurements of elemental concentration. This paper discusses statistical methods used to address challenges in Pu metal exchange data by way of two case studies. Challenges include how to evaluate a data set when a large fraction of the values are minimum detection limits (MDLs), and how to determine potential outliers with limited in-formation on the true spread of the data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗