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At least 1,495 records · Page 83

Gamma-ray spectra analyses of molten salts in spent nuclear fuels pyroprocessing facilities for mass measurement

To evaluate radioactive tracer dilution and gamma spectroscopy as a safeguards technique for monitoring the mass of liquid salt in molten salt systems, the gamma spectroscopy data of salt samples from the pyroprocessing facilities in Idaho National Laboratory were acquired and analyzed. The primary focus is the uncertainty analysis of the gamma radioactivity of 154 Eu isotope in the molten salts. The facilities include an electrorefiner for pyroprocessing spent oxide fuels (SOF-ER) and Mark-IV ER for processing the metallic fuels from Experimental Breeder Reactor-II (EBR-II). The relative gamma radioactivity uncertainty was consistently at 3% for 137 Cs for both Mark-IV ER and SOF-ER salts. However, for 154 Eu, it was 8% for SOF-ER salt and 7% for Mark-IV ER salt. Here, the main reason for the higher uncertainty for 154 Eu is believed to be the lower counting statistics in gamma spectroscopy. To improve the gamma radioactivity uncertainty of isotope 154 Eu, a longer data acquisition time (12 h instead of 4 h) and a higher count rate gamma detector for gamma spectroscopy were tested and it was found that the uncertainty for 154 Eu was significantly improved from 7% or 8–3%.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Fission fragment decay simulations with the CGMF code

The CGMF code implements the Hauser-Feshbach statistical nuclear reaction model to follow the de-excitation of fission fragments by successive emissions of prompt neutrons and γ rays. The Monte Carlo technique is used to facilitate the analysis of complex distributions and correlations among the prompt fission observables. Starting from initial configurations for the fission fragments in mass, charge, kinetic energy, excitation energy, spin, and parity, Y(A,Z,KE,U,J,π), CGMF samples neutron and γ-ray probability distributions at each stage of the decay process, conserving energy, spin and parity. Nuclear structure and reaction input data from the RIPL3 library are used to describe fission fragment properties and decay probabilities. Characteristics of prompt fission neutrons, prompt fission γ rays, and independent fission yields can be studied consistently. Correlations in energy, angle and multiplicity among the emitted neutrons and γ rays can be easily analyzed as a function of the emitting fragments. Finally, in its current version, CGMF is limited to certain spontaneous fission reactions on Pu and Cf isotopes, as well as neutron-induced fission reactions up to 20 MeV on U, Np, and Pu isotopes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Structural stability of mechanically alloyed amorphous (FeCoNi) 70 Ti 10 B 20 under high-temperature and high-pressure

Nanostructured (FeCoNi) 70 Ti 10 B 20 (at%) alloy was synthesized by mechanical alloying from elemental powder mixture of Fe, Co, Ni, Ti and B using ball milling. The effect of ball milling time on the evolution of structure and morphology was investigated by X-ray diffraction, scanning and transmission electron microscopy and differential thermal analysis. It was observed that the formation of solid solution of (FeCoNi) 70 Ti 10 B 20 started from the very onset of the milling process. Crystallite size and lattice strains seemed to be leveled off after 20 h of milling with no further major changes. The milling process for longer periods introduced severe plastic deformations causing formation of amorphous phase of (FeCoNi) 70 Ti 10 B 20 . The amorphous alloy composition was confirmed by energy dispersive X-ray spectroscopy analysis that showed an excellent homogeneity of the alloying elements. The phase stability of the mechanically alloyed amorphous sample was further verified by employing high-temperature and high-pressure studies. The alloy samples heat-treated at 700 °C revealed crystallization of the amorphous phase. However, synchrotron-based high-pressure ambient temperature X-ray diffraction studies confirmed that the amorphous phase of the alloy remained stable up to the pressure of 30 GPa. Here, the 50 h milled sample after being annealed at 350 °C showed improvement in the soft magnetic properties of the alloy, which was due to the probable elimination of the residual stress in the amorphous phase of the alloy powders.

36 MATERIALS SCIENCE↗

Observation, identification and characterization of strong self-reduction process in a orthophosphate phosphor CaZr{sub 4}(PO{sub 4}){sub 6}:Eu

Highlights: • CaZr{sub 4}P{sub 4}O{sub 24}:Eu was synthesized by solid state reaction in air. • Relationship between the structure and luminescence properties was discussed. • Strong self-reduction process was found in CaZr{sub 4}P{sub 4}O{sub 24}:Eu prepared in air. • Oxidation states of Eu were identified by muti-method approaches. • The self-reduction mechanism was investigated. - Abstract: CaZr{sub 4}P{sub 4}O{sub 24}:Eu orthophosphate phosphor was synthesized by traditional solid state reaction in air atmosphere. The relationship between the host structure and the characteristic luminescence properties was discussed detailedly. When irradiate the sample under 365 nm UV lamp, intense green emission was observed due to the strong self-reduction process of Eu ions. The oxidation states of Eu ions were identified by muti-method approaches, including photoluminescence spectra, fluorescence lifetimes, Electron spin resonance (ESR) spectroscopy and X-ray photoelectron spectroscopy analysis (XPS). The self-reduction process was controlled by adding the charge compensator Li{sub 2}CO{sub 3} and the self-reduction mechanism was further investigated.

36 MATERIALS SCIENCE↗

Optical detection of spin Hall effect in metals

Optical techniques have been widely used to probe the spin Hall effect in semiconductors. In metals, however, only electrical methods such as nonlocal spin valve transport, ferromagnetic resonance, or spin torque transfer experiments have been successful. These methods require complex processing techniques and measuring setups. We show here that the spin Hall effect can be observed in non-magnetic metals such as Pt and β-W, using a standard bench top magneto-optical Kerr system with very little sample preparation. Applying a square wave current and using Fourier analysis significantly improve our detection level. One can readily determine the angular dependence of the induced polarization on the bias current direction (very difficult to do with voltage detection), the orientation of the spin Hall induced polarization, and the sign of the spin Hall angle. This optical approach is free from the complications of various resistive effects, which can compromise voltage measurements. This opens up the study of spin Hall effect in metals to a variety of spin dynamic and spatial imaging experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Results of In-Depth Analysis of Data Obtained in the Experimental Search for 2K(2ν)-Capture in {sup 78}Kr

A brief description of the results of joint analysis of data obtained in long-term measurements of krypton samples differing in {sup 78}Kr content is presented. Low-background high-pressure proportional gas counters were used as detectors. The comparative analysis of experimental data on single and double K -capture provided the first estimate of the probability of production of a double K -shell vacancy in the process of K -shell electron capture in {sup 81}Kr: P{sub KK}=[5.7±0.8 (stat.)±0.4 (syst.)]×10{sup −5}. A new result for the half-life of {sup 78}Kr with respect to the 2K(2ν)-mode was also obtained: T{sub 1/2}=[1.9{sub −0.7}{sup +1.3} (stat.)±0.3 (syst.)]×10{sup 22} years (90% CL).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

RAVEN Beta Release

This documents the release of the Risk Analysis Virtual Environment (RAVEN) code. A description of the RAVEN code is provided, and discussion of the release process for the M2LW-16IN0704045 milestone. The RAVEN code is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. RAVEN is capable of investigating the system response as well as the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused toward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. RAVEN has now increased in maturity enough for the Beta 1.0 release.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

2D Graphene Sheets as a Sensing Material for the Electroanalysis of Zileuton

Zileuton (ZLT) is an active oral inhibitor of enzyme 5-lipoxygenase, and long-term intake and overdose of ZLT cause adverse effects, leading to critical conditions in patients. This is a well-recognized issue that necessitates a better approach for ZLT sensing. Given the increasing interest in ZLT sensing and the limitations of previous techniques, there is a need for a highly sensitive, robust, and fast operation method that is inexpensive and easy to use. Thus, for the sensitive detection and determination of ZLT, an electrochemical sensor based on graphene was fabricated. Graphene has excellent properties, such as high surface area, low toxicity, conductivity, and electroactive conjugation with biomolecules, making it suitable for sensing. The electrocatalytic property of graphene promotes the redox-coupled reaction of ZLT. Electrochemical investigation of the modifier was carried out by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). An optimization and analysis of the influence of different parameters on the electrochemical behavior of ZLT were carried out using the CV approach. The scan rate study aided in exploring the physicochemical properties of the electrode process, and two electrons with two protons were found to be involved in the electrooxidation of ZLT. The fabricated sensor showed a wide range of linearity with ZLT, from 0.3 µM to 100.0 µM, and the detection limit was evaluated as 0.03 µM under optimized conditions. The analysis of spiked urine samples, with good recovery values for percent RSD, provided support for the efficiency and applicability of the developed electrode.

2D Material↗

Refining Groundwater Monitoring Approaches Through an Objectives-Driven Process - 16333

Groundwater monitoring is conducted throughout the groundwater remediation process, from initial site characterization through demonstration of cleanup objectives attainment. The DOE uses the groundwater monitoring data to define plumes, manage ongoing remediation, and determine how close the contamination levels are to meeting an endpoint criteria, such as a drinking water standard. Due to the expense of groundwater sampling and analysis, the DOE Office of Environmental Management compiled a synopsis of monitoring technologies and approaches, and defined opportunities for improving environmental remediation monitoring. This information included techniques to optimize and streamline groundwater monitoring. At the Hanford Site, years of extensive groundwater monitoring have been applied to support characterization and remedy-selection activities. Continuation of this monitoring intensity would be costly and would need to be reviewed in the context of future activities for groundwater remedy implementation. A structured review of monitoring plans is underway and has identified significant potential changes to the monitoring approach. These changes have been developed based on careful definition of monitoring objectives and consideration of innovative and targeted techniques to gather the appropriate data for remedy performance monitoring and transition to longer-term monitoring and closure. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

3-D Radiological Data Acquisition, Visualization and Modeling - 20211

The U.S. Army Corps of Engineers (USACE) was tasked to investigate and remediate low activity radiological contamination from research and production of the nation's first nuclear weapons at the former DuPont Chambers Works Formerly Utilized Sites Remedial Action Program (FUSRAP) site (DuPont). The DuPont site had several buildings used for the Manhattan project that were demolished in the 1940's and 1950's apparently using heavy earthmoving equipment. Some of the contaminated rubble from the demolition appears to have been spread out by this equipment resulting in somewhat random scattering of radiologically contaminated soil and debris along with aqueous spills. Traditional investigative methods such as soil borings, test pits and 2-dimensional gamma walkovers were only partially successful in delineating the radiological contamination at the site. It was feared that even 'chasing' the contamination during remediation would miss contamination if the demolition resulted in discontinuous trails of radiologically contaminated soils. In evaluating the data generated over the interceding decades, the USACE determined that a better method to collect and process the remedial action radiological data was needed to enable the project team to optimize predictive planning and meet documentation expectations. The purpose of this paper is to provide an overview of the effort and progress to combine and organize radiological survey methods into a highly flexible sampling, modeling, and decision analysis approach that emphasizes the quality of decision-making during remediation. This innovative system blends multiple tools to develop a methodology that can extend MARRSIM [1] into the subsurface and provide tools that can be applied to other sites. (authors)

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

3013 DE Inner Container Closure Weld Corrosion Evaluation

Destructive evaluation (DE) of 3013 containers is one part of the U. S. Department of Energy Integrated Surveillance Program. During standard DE of 3013 containers, visual examinations for pitting and stress corrosion cracking (SCC) are performed on the accessible surfaces of the outer, inner, and convenience containers, which make up the 3013 container. As a result of 3013 DE additional analysis, the area near the inner container closure weld has been identified as being a region of increased corrosion susceptibility, which may provide a pathway for corrosive gases to the outer container. This area has a higher residual stress, an altered microstructure, and less corrosion resistant weld oxides as a result of the welding process as well as a lower temperature than other areas of the container, which may increase the absorption of moisture on the surface. The deposition of moisture in this stressed region could lead to pitting and stress corrosion cracking. During FY2013, the inner container closure weld area was more closely evaluated on several archived samples from DE containers. These containers included FY09 DE2, FY12 DE4, FY12 DE6 and FY12 DE7 and the Hanford High Moisture Container. The additional examinations included visual observations with a stereomicroscope, scanning electron microscopy along with energy dispersive spectroscopy for chemical analysis, and serial metallography of the sidewall and lid that are part of the inner container closure weld region. Pitting was observed in all the samples taken from the closure weld regions of the examined inner containers. This pitting was generally less 20 µm with most less than 5µm. These pits were similar in depth to those observed in the vapor exposed surfaces of teardrops in the shelf life corrosion testing. Cracking was not observed on either the vapor-exposed surfaces of the teardrop coupons or the inner container closure weld region. Further testing is necessary to determine if the conditions in the welded inner container could support SCC during the 50 year life time for the 3013 container.

36 MATERIALS SCIENCE↗

Sustainable network design for multi-purpose pellet processing depots under biomass supply uncertainty

This work develops a two-stage stochastic mixed-integer programming model to manage multi- purpose pellet processing depots under feedstock supply uncertainty. The proposed optimization model would help to minimize cost and to mitigate emissions from the supply chain network. We consider three alternative Biomass Processing and Densi cation Depot (BPDD) technologies; namely, conventional pellet processing, high moisture pellet processing, and ammonia ber expansion. These three technologies pre-process/pre-treat and densify different types of biomass into more highly densi ed intermediate products for different markets in order to improve movability and overall supply network performance in terms of costs and emissions. A hybrid decomposition algorithm was developed that combines sample average approximation with an enhanced Progressive Hedging (PH) algorithm to solve this challenging NP -hard problem. Some heuristics such as Rolling Horizon (RH) heuristic, variable xing technique were later applied to further enhance the PH algorithm. Mississippi and Alabama were selected as a testing ground and ArcGIS was employed to visualize and validate the modeling results. The results of the analysis reveal promising insights that could lead to recommendations to help decision makers achieve a more cost-effective environmentally-friendly supply chain network.

09 BIOMASS FUELS↗

Rapid Analytical Methodology for Chloride Molten Salt Reactor Safeguards and Process Monitoring

Technologies that enable near real-time isotopic analysis of advanced molten salt reactor (MSR) fuels are critically needed to safeguard these reactors, increase their operational efficiency, and enable their widespread deployment with confidence. We present a systematic approach to developing near real-time dissolution and chemical isolation of U, Pu, and major fission products from highly radioactive chloride molten salt samples. Chemical yields greater than 95% were observed for both uranium and the lanthanides. Interference reduction enabled the detection and quantification of key diagnostic isotopes (including 112Ag, 147Nd, and 153Sm) that were previously undetectable in the original sample. The results from this initial scoping study lay the foundation for the development of future automated systems that can enable cost-efficient, near-real time chemical separation and analysis of extremely highly radioactive molten salt samples.

38 - RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCL↗

Analysis of Inlier and Outlier Compounds with Respect to Artificial Neural Network Cetane Number Prediction Accuracy

Artificial neural networks (ANNs) are exceptional at forming non-linear correlations between multivariate input and target variables; however, they are often seen as a “black box” approach, since how ANNs form these correlations is somewhat ambiguous. Furthermore, the process underlying how ANNs learn from inlier and outlier samples within the input dataset is not fully understood. Intuitively, it is expected that training ANNs with inlier samples will increase prediction accuracy and training with outlier samples will reduce prediction accuracy; though, in practice, this is not always true. The present work identifies and analyzes inliers and outliers of existing experimental cetane number (CN) data encompassing a variety of compounds and compound groups. It also investigates how ANNs trained to predict CN perform with and without outliers included in the training data, and whether a relationship exists between inliers/outliers and ANN prediction accuracy across the whole dataset and for individual samples. Additionally, individual outlier compounds are analyzed, highlighting how they structurally differ from inlier compounds.

09 BIOMASS FUELS↗

Micro-Spectroscopic Imaging and Characterization of Individually Identified Ice Nucleating Particles from a Case Field Study

The effect of anthropogenic and biogenic organic particles on atmospheric glaciation processes is poorly understood. We use an optical microscopy (OM) setup to identify the location of ice nuclei (IN) active in immersion freezing and deposition ice nucleation for temperatures of 200-273 K within a large population of particles sampled from an ambient environment. Applying multi-modal micro-spectroscopy methods we characterize the physicochemical properties of individual IN in particle populations collected in central California. Chemical composition and mixing state analysis of particle populations are performed to identify characteristic particle-type classes. All particle-types contained organic material. Particles in these samples take up water at subsaturated conditions, induce immersion freezing at subsaturated and saturated conditions above 226 K, and act as deposition IN below 226 K. The identified IN belong to the most common particle-type classes observed in the field samples: organic coated sea salt, Na-rich, and secondary and refractory carbonaceous particles. Based on these observations, we suggest that the IN are not always particles with unique chemical composition and exceptional ice nucleation propensity; rather, they are common particles in the ambient particle population. Thus, particle composition and morphology alone are insufficient to assess their potential to act as IN. The results suggest that particle-type abundance is also a crucial factor in determining the ice nucleation efficiency of specific IN types. These findings emphasize that ubiquitous organic particles can induce ice nucleation under atmospherically relevant conditions and that they may play an important role in atmospheric glaciation processes.

Environmental Molecular Sciences Laboratory↗

An approach to nearest neighbor analysis of pigment-protein complexes using chemical cross-linking in combination with mass spectrometry

Herein, protein cross-linking is the process of chemically joining two amino acids in a protein or protein complex by a covalent bond. When combined with mass spectrometry, it becomes one of the structural mass spectrometry techniques gaining in importance for deriving valuable three-dimensional structural information on proteins and protein complexes. This platform complements existing structural methods, such as NMR spectroscopy, X-ray crystallography, and cryo-EM. Photosynthetic pigment protein complexes serve as light-energy harvesting systems and perform photochemical conversion as part of the “early events” of photosynthesis. This chapter outlines how to prepare cross-linking pigment protein complex samples for LC-MS/MS analysis, including identification of the cross-linked species, network analysis in a protein complex, and structural modeling and justification.

59 BASIC BIOLOGICAL SCIENCES↗

Atmospheric Solid Analysis Probe Coupled to Ion Mobility Spectrometry-Mass Spectrometry, a Fast and Simple Method for Polyalphaolefin Characterization

Polyalphaolefins (PAOs) are polymers produced from linear alpha olefins through catalytic oligomerization processes. The PAOs are known as synthetic high-performance base stock fluids used to improve the efficiency of many other synthetic products. In this study, we report the direct characterization of PAOs using atmospheric solid analysis probe (ASAP) coupled with ion mobility spectrometry-mass spectrometry (IMS-MS). We studied different PAOs grades exhibiting low- and high-viscosity index. Specific adjustments of the ASAP source parameters permitted the monitoring of ionization processes as three mechanisms could occur for these compounds: hydride abstraction, nitrogen addition, and/or the formation of [M−2H]{sup +•} ions. Several series of fragment ions were obtained, which allowed the identification of the alpha olefin used to synthesize the PAO. The use of the ion mobility separation dimension provides information on isomeric species. In addition, the drift time versus m/z plots permitted rapid comparison between PAO samples and to evidence their complexity. These 2D plots appear as fingerprints of PAO samples. To conclude, the resort to ASAP-IMS-MS provides a rapid characterization of the PAO samples in a direct analysis approach, without any sample preparation. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Near-infrared spectroscopy as a green analytical tool for sustainable biomass characterization for biofuels and bioproducts: An overview

Biomass, a widely used renewable energy source, requires characterization to optimize biofuel and bioproduct processes, customize feedstocks, and ensure economic and environmental sustainability. Conventional wet-chemistry methods for biomass analysis are slow, expensive, and require significant reagents and skilled personnel. In contrast, near-infrared (NIR) spectroscopy, a faster, cost-effective, and reagent-free green technology, enables non-destructive biomass analysis with minimal sample preparation. This study provides an overview of the fundamentals of NIR spectroscopy and explores its recent applications for analyzing various biomass properties important to the biofuel and bioproduct industry. The study also critically evaluates the challenges and opportunities of using NIR spectroscopy for biomass analysis. This review aims to guide future research for rapid and high throughput characterization of biomass in the biomass industry, supporting the United Nations’ sustainable development goal (SDG) 7: producing affordable and sustainable energy.

Biofuels↗