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At least 1,297 records · Page 72

A low-temperature, one-step synthesis for monazite can transform monazite into a readily usable advanced nuclear waste form

It has been demonstrated that monazite-type materials are excellent candidates for nuclear waste forms, and hence, their facile synthesis is of great importance for the needed sequestration of existing nuclear waste. The synthesis of monazite, LaPO 4 , requires inconveniently high temperatures near 1000°C and generally involves the conversion of the presynthesized rhabdophane, LaPO 4 •nH 2 O, to the LaPO 4 monazite phase. During this structure transformation, the rhabdophane converts irreversibly to the thermodynamically stable monoclinic monazite structure. A low-temperature (185° to 260°C) mild hydrothermal acid-promoted synthesis of monazite is described that can both transform presynthesized rhabdophane or assemble reagents to the monoclinic monazite structure. The pH dependence of this reaction is detailed, and its applicability to the LnPO 4 (Ln = La, Ce, Pr, Nd, Sm-Gd), Ca 0.5 Th 0.5 PO 4 , and Sr 0.5 Th 0.5 PO 4 systems is discussed. The crystal growth of Ca 0.5 Th 0.5 PO 4 and Sr 0.5 Th 0.5 PO 4 is described, and their crystal structures were reported. In situ x-ray diffraction studies, performed as a function of temperature, provide insight into the structure transformation process.

Biogeochemistry↗

Response of Total (DNA) and Metabolically Active (RNA) Microbial Communities in Miscanthus × Giganteus Cultivated Soil to Different Nitrogen Fertilization Rates

Miscanthus × giganteus is a promising high-yielding perennial plant to meet growing bioenergy demands; however, the degree to which the soil microbiome affects its nitrogen cycling and subsequently, biomass yield remains unclear. In this study, we hypothesize that contributions of metabolically active soil microbial membership may be underestimated with DNA-based approaches. We assessed the response of the soil microbiome to nitrogen availability in terms of both DNA and RNA soil microbial communities from the Long-term Assessment of Miscanthus Productivity and Sustainability (LAMPS) field trial. DNA and RNA were extracted from 271 samples, and 16S small subunit (SSU) rRNA amplicon sequencing was performed to characterize microbial community structure. Significant differences were observed in the resulting soil microbiomes and were best explained by the sequencing library of origin, either DNA or RNA. Similar numbers of membership were detected in DNA and RNA microbial communities, with more than 90% of membership shared. However, the profile of dominant membership within DNA and RNA differed, with varying proportions of Actinobacteria and Proteobacteria and Firmicutes and Proteobacteria. Only RNA microbial communities showed seasonal responses to nitrogen fertilization, and these differences were associated with nitrogen-cycling bacteria. The relative abundance of bacteria associated with nitrogen cycling was 7-fold higher in RNA than in DNA, and genes associated with denitrifying bacteria were significantly enriched in RNA, suggesting that these bacteria may be underestimated with DNA-only approaches. Our findings indicate that RNA-based SSU characterization can be a significant and complementing resource for understanding the role of soil microbiomes in bioenergy crop production.

59 BASIC BIOLOGICAL SCIENCES↗

Fast tree-based algorithms for DBSCAN for low-dimensional data on GPUs

DBSCAN is a well-known density-based clustering algorithm to discover arbitrary shape clusters. While conceptually simple in serial, the algorithm is challenging to efficiently parallelize on manycore GPU architectures. Common pitfalls, such as asynchronous range query calls, result in high thread execution divergence in many implementations. In this paper, we propose a new framework for GPU-accelerated DBSCAN, and describe two tree-based algorithms within that framework. Both algorithms fuse the search for neighbors with updating cluster information, but differ in their treatment of dense regions of the data. We show that the time taken to compute clusters is at most twice that of determination of the neighbors. We compare the proposed algorithms with existing CPU and GPU implementations, and demonstrate their competitiveness and performance using a fast traversal structure (bounding volume hierarchy) for low dimensional data. We also show that the memory usage can be reduced by processing object neighbors dynamically without storing them.

Prokopenko, Andrey↗

Intermediate Temperature Solid Oxide Cell with a Barrier Layer Free Oxygen Electrode and Phase Inversion Derived Hydrogen Electrode

High-temperature solid oxide cells (SOCs) have fundamental advantages in efficiency and product rate over their low-temperature counterparts. However, the commercial development of SOCs is hindered by cost and reliability. To solve the issues, lowering the operating temperature of SOCs is deemed the best solution. Here we report on our effort toward intermediate temperature (IT) SOCs by developing a barrier layer free high-performance oxygen electrode and open structured hydrogen electrode. The results show that the new oxygen electrode provides reasonably good oxygen electrocatalytic activity at IT range for oxygen reduction and evolution reactions and the open structured hydrogen electrode provides low gas diffusion path for H 2 /H 2 O. However, at high electrolysis current density such as 1 A cm −2 and 650 °C, the present oxygen electrode delaminates after 200 h. The phase-inversion derived open structured hydrogen electrode helps gas diffusion but, in the meantime, reduces reactive sites. A proper balance of porosity and number of reactive sites is still needed for future hydrogen electrode development.

25 ENERGY STORAGE↗

Budget Constrained Machine Learning for Early Prediction of Adverse Outcomes for COVID-19 Patients

Background: Machine learning (ML) based risk stratification models of Electronic Health records (EHR) data may help to optimize treatment of COVID-19 patients, but are often limited by their lack of clinical interpretability and cost of laboratory tests. We develop a ML based tool for predicting adverse outcomes based on EHR data to optimize clinical utility under a given cost structure. This cohort study was performed using deidentified EHR data from COVID-19 patients from ProMedica Healthcare in northwest Ohio and southeastern Michigan. Methods: We tested performance of various ML approaches for predicting either increasing ventilatory support or mortality and the set of model features under a budget constraint was optimized via exhaustive search across all combinations of features. Results: The optimal sets of features for predicting ventilation under any budget constraint included demographics and comorbidities (DCM), basic metabolic panel (BMP), D-dimer, lactate dehydrogenase (LDH), erythrocyte sedimentation rate (ESR), CRP, brain natriuretic peptide (BNP), and procalcitonin and for mortality included DCM, BMP, complete blood count, D-dimer, LDH, CRP, BNP, procalcitonin and ferritin. Conclusions: This study presents a quick, accurate and cost-effective method to evaluate risk of deterioration for patients with SARS-CoV-2 infection at the time of clinical evaluation.

Cadena Pico, JoseE.↗

Lattice Optimization for Porous Electrode

This code performs an optimization over the structure of a porous electrode formed from a lattice of unit cells. This is a steepest descent version of the code used in: V. A. Beck, J. J. Wong, C. F. Jekel, D. A. Tortorelli, S. E. Baker, E. B. Duoss and M. A. Worsley, Computational design of microarchitected porous electrodes for redox flow batteries, J. Power Sources, 2021, 512, 230453.

Wong, JonathanJ↗

Characteristics and selection of near-fault simulated earthquake ground motions for nonlinear analysis of buildings

Earthquake-induced ground shaking near rupturing faults is highly sensitive to the rupture characteristics, seismic wave propagation patterns and site conditions, and field recordings of near-fault shaking are relatively sparse. These challenges complicate the assessment of the seismic performance of near-fault structures. A common approach to representing near-fault ground motion in engineering analysis is to explicitly consider and select records with strong directivity pulses (pulse records). We use three-dimensional high-resolution physics-based earthquake simulations to test this approach in the context of scenario-based ground motion record selection, and to study the important characteristics of near-fault ground shaking. We highlight the deficiencies associated with classifying near-fault simulated records as “pulse” or “non-pulse,” based on the presence of a single dominating pulse in the velocity time history. We show that this approach is inadequate for characterizing near-fault shaking on soft soils which can be dominated by both forward rupture directivity and basin amplification effects. We conduct ground motion selection experiments for the analysis of near-fault structures with and without explicit classification of the pulse features in the records, and evaluate the bias in the predicted structural demands. We find that the maximum interstory drift demands on building structures imposed by unscaled site-specific simulated ground motion records selected based on relevant spectral shape features are not sensitive to the classification of records as pulse/non-pulse. Therefore, with regard to predicting the maximum interstory drifts in near-fault buildings, we do not find justification for the binary pulse classification of near-fault records.

42 ENGINEERING↗

Confidentiality-preserving machine learning algorithms for soft-failure detection in optical communication networks

Automated fault management is at the forefront of next-generation optical communication networks. The increase in complexity of modern networks has triggered the need for programmable and software-driven architectures to support the operation of agile and self-managed systems. In these scenarios, the European Telecommunications Standards Institute zero-touch network and service management approach is imperative. The need for machine learning algorithms to process the large volume of telemetry data brings safety concerns as distributed cloud-computing solutions become the preferred approach for deploying reliable communication network automation. This paper’s contribution is twofold. First, we propose a simple yet effective method to guarantee the confidentiality of the telemetry data based on feature scrambling. The method allows the operation of third-party computational services without direct access to the full content of the collected data. Additionally, the effectiveness of four unsupervised machine learning algorithms for soft-failure detection is evaluated when applied to the scrambled telemetry data. The methods are based on factor analysis, principal component analysis, nonlinear principal component analysis, and singular value decomposition. Most dimensionality reduction algorithms have the common property that they can maintain similar levels of fault classification performance while hiding the data structure from unauthorized access. Evaluations of the proposed algorithms demonstrate this capability.

97 MATHEMATICS AND COMPUTING↗

Split-well resonant-phonon terahertz quantum cascade laser

We present a highly diagonal “split-well resonant-phonon” (SWRP) active region design for GaAs/Al 0.3 Ga 0.7 As terahertz quantum cascade lasers (THz-QCLs). Negative differential resistance is observed at room temperature, which indicates the suppression of thermally activated leakage channels. The overlap between the doped region and the active level states is reduced relative to that of the split-well direct-phonon (SWDP) design. The energy gap between the lower laser level (LLL) and the injector is kept at 36 meV, enabling a fast depopulation of the LLL. Within this work, we investigated the temperature performance and potential of this structure.

47 OTHER INSTRUMENTATION↗

Structuring, stochastic behavior, and charge storage capacity of redox-active microemulsions formulated with mixtures of toluene and ionic liquid as oil phase

Oil/water microemulsions (µEs) are promising electrolytes for redox flow batteries (RFBs) as they simultaneously improve charge capacity and ionic conductivity. Here, we report the successful formulation of bicontinuous µEs where the oil phase is a solution of trihexyltetradecylphosphonium bis(trifluoromethylsulfonyl)amide ionic liquid in toluene with redox-active ferrocene. We examined the effect of supporting electrolyte anion (NO 3 – , Cl – , ClO 4 – ) on the structure, reactivity, transport, and electrolytic performance of redox-active µEs. Neutron scattering and nuclear magnetic resonance showed that the domain size increased as Cl – > NO 3 – > ClO 4 – while the ferrocene diffusion coefficient increased as NO 3 – > Cl – > ClO 4 – . Scanning electrochemical microscopy indicated anion-dependent current fluctuations during electrolysis, with ClO 4 – exhibiting the least high-frequency oscillations, which correlate to the highest charge and discharge capacity and reversibility. All ionic liquid containing systems improved the performance of toluene-based µEs, highlighting new design principles for these electrolytes.

diffusion↗

Initial framework for engineering-scale statistical creep-fatigue modeling

This report describes the integration of new solid and interface-cohesive mechanics systems into MOOSE. The purpose of these new systems is to support the ability of MOOSE to run full-field crystal plasticity finite element method simulations of key material processes in high temperature metallic materials. These simulations could be used to help accurately predict the performance of key high temperature structural materials in future advanced nuclear reactor components. Previous work implemented preliminary versions of many of these systems in MOOSE Apps. The current work reports on their integration into the main MOOSE tensor mechanics module along with associated improvements to the basic formulations and numerical implementations. Finally, the report provides an example of the full-field crystal plasticity simulations now possible in MOOSE, including examples of realistic geometries requiring millions of degrees of freedom to resolve the microstructural features and macroscale geometry.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Exotanium DOE SBIR Phase I Results Summary

Exotanium demonstrated this technology with the Idaho National Laboratory’s MASTODON application, a Multiphysics environment designed to run typical high-performance computing (HPC) simulations for structural dynamics, seismic analysis, and risk assessment. The MASTODON application was packaged into a container using Docker, Deployed on Amazon ECS, and managed through a custom Scale-Out Compute on AWS (SOCA) implementation.

97 MATHEMATICS AND COMPUTING↗

Quantifying and Optimizing the Energy Benefits of Mass Timber Construction

The International Mass Timber Alliance (IMTA) is a global organization of industry leaders, engineers, scientists, and associations dedicated to advancing mass timber construction. Its mission is to generate and disseminate scientific data supporting the development of standardized construction and energy efficient practices that promote the adoption of mass timber worldwide. IMTA collaborated with Oak Ridge National Laboratory (ORNL) to leverage ORNL’s expertise in building envelope modeling and testing to evaluate how mass timber construction can reduce peak heating and cooling demand, lower overall energy use, and improve resilience during power outages. A previous study of 80 mass timber buildings in Finland found measured energy use up to 50% lower than predicted by simulation. This project aimed to validate and extend those findings for U.S. buildings through analytical modeling, laboratory testing, and full-scale building evaluations. The research focused on the thermal performance of low-embodied-energy wall assemblies, such as cross-laminated timber (CLT) panels and log walls, with particular attention to the effects of thermal inertia on indoor comfort and energy performance. While mass timber’s structural and fire-resistance properties are well documented, its whole-building thermal behavior has received limited attention. Field data, simulation results, and resilience testing from this study will inform future modeling practices, design guidelines, and construction practices by quantifying the unique thermal and demand-flexibility benefits of mass timber construction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Presence of Induced Weak Ferromagnetism in Fe-Substituted YFe x Cr 1–x O 3 Crystalline Compounds

Fe-substituted YFe x Cr 1–x O 3 crystalline compounds show promising magnetic and multiferroic properties. Here we report the synthesis and characterization of several compositions from this series. Using the autocombustion route, various compositions (x = 0.25, 0.50, 0.6, 0.75, 0.9, and 1) were synthesized as high-quality crystalline powders. In order to obtain microscopic and atomic information about their structure and magnetism, characterization was performed using room temperature X-ray diffraction and energy dispersion analysis as well as temperature-dependent neutron diffraction, magnetometry, and 57 Fe Mössbauer spectrometry. Rietveld analysis of the diffraction data revealed a crystallite size of 84 (8) nm for YFeO 3 , while energy dispersion analysis indicated compositions close to the nominal compositions. The magnetic results suggested an enhancement of the weak ferromagnetism for the YFeO 3 phase due to two contributions. First, a high magnetocrystalline anisotropy was associated with the crystalline character that favored a unique high canting angle of the antiferromagnetic phase (13°), as indicated by the neutron diffraction analysis. This was also evidenced by the high magnetic hysteresis curves up to 90 kOe by a remarkable high critical coercivity value of 46.7 kOe at room temperature. Second, the Dzyaloshinskii–Moriya interactions between homogenous and heterogeneous magnetic pairs resulted from the inhomogeneous distribution of Fe 3+ and Cr 3+ ions, as indicated by 57 Fe Mössbauer studies. Together, these results point to new methods of controlling the magnetic properties of these materials.

36 MATERIALS SCIENCE↗

Productive Programming of Distributed Systems with the SHAD C++ Library

High-performance computing (HPC) is often perceived as a matter of making large-scale systems (e.g., clusters) run as fast as possible, regardless the required programming effort. However, the idea of "bringing HPC to the masses" has recently emerged. Inspired by this vision, we have designed SHAD, the Scalable High-performance Algorithms and Data-structures library. SHAD is open source software, written in C++, for C++ developers. Unlike other HPC libraries for distributed systems, which rely on SPMD models, SHAD adopts a shared-memory programming abstraction, to make C++ programmers feel at home. Underneath, SHAD manages tasking and data-movements, moving the computation where data resides and taking advantage of asynchrony to tolerate network latency. At the bottom of his stack, SHAD can interface with multiple runtime systems: this not only improves developer’s productivity, by hiding the complexity of such software and of the underlying hardware, but also greatly enhance code portability. Thanks to its abstraction layers, SHAD can indeed target different systems, ranging from laptops to HPC clusters, without any need for modifying the user-level code. We have prototyped and open-sourced the implementation of (a subset of) the C++ standard library (STL) targeting multi-node HPC clusters. Our work allows plain STL-based C++ code to scale on HPC systems, with no need for rewriting the code to exploit the complex hardware. SHAD is available under Apache v2 License at https://github.com/pnnl/SHAD. In this paper we overview the design of the SHAD library, depicting its main components: runtime systems abstractions for tasking; parallel and distributed data-structures; STL-compliant interfaces and algorithms.

Castellana, Vito G.↗

2.2.2.405 - Verdant/NREL Research Measurement Campaign

The marine renewable energy industry primarily uses thermoset composite materials for blades and other hydrodynamic components, which can have up to 50% reduction in strength when exposed to seawater and are not recyclable. Thermoplastic composite materials have been shown at a coupon-scale to have improved seawater saturated properties but have not been validated at full scale. The primary goal of the project is to demonstrate the structural properties of thermoplastic-fiberglass composite blades compared to epoxy-fiberglass composite blades in seawater at a tidal energy site on an operational turbine. Through this work, NREL manufactured, tested and deployed thermoplastic blades and a data acquisition system on Verdant Power's turbine TriFrame in the East River, NYC. The thermoplastic blades and DAQ were retrieved after a 6-month deployment with no signs of degradation and all cable connections, structural supports and strain gages had a 100% survival rate. The blades are currently undergoing post-deployment structural validation to compare their performance to traditional epoxy blades that were deployed for the same amount of time. This will increase confidence in thermoplastic materials and move it closer to commercial adoption, as well as increase confidence in the design of a DAQ and instrumentation method for a tidal turbine. However, due to an error in the DAQ software that was introduced after the DAQ and software were validated, there was no loads data collected during the deployment.

blade testing↗

A New Process for Small-Batch Purification of the Medical Isotope Molybdenum-99: Non-Technical Overview

The U.S. medical community depends on a reliable supply of the radioisotope molybdenum-99 (Mo-99) for nuclear medical diagnostic procedures. Mo-99's decay product, technetium-99m (Tc-99m), is used in over 40,000 medical procedures in the United States each day to diagnose heart disease and cancer, to study organ structure and function, and to perform other important medical applications. For example, patients undergoing a common procedure—the cardiac “stress test”—likely have benefited from Tc-99m. Historically, Mo-99 was primarily produced through the fission of uranium-235, in the form of highly enriched uranium (HEU) targets irradiated in research and test reactors. HEU is a proliferation-sensitive material that, if diverted or stolen, could be used as a component of a nuclear weapon. NNSA’s Office of Material Management and Minimization (M3) manages the Molybdenum-99 (Mo-99) Program as part of its mission to minimize the use of HEU in civilian applications. The Mo-99 Program assists global Mo-99 production facilities in converting to non-HEU processes and supports the establishment of domestic supplies of Mo-99 without the use of proliferation-sensitive HEU. As part of this program, M3 funds U.S. national laboratories to provide non-proprietary technical support to U.S. companies working to establish non-HEU-based Mo-99 production capabilities. The results of this research are published on OSTI.gov for the benefit of the Mo-99 community and the public. However, it can be difficult for readers without a scientific background to understand and interpret these publications. In order to increase public understanding of the work being done in M3’s Mo-99 Program, this paper aims to provide an overview of a key, recent national laboratory technical publication in terms that can be understood by readers without a technical background. To accomplish this, the paper first explains key scientific concepts—primarily related to chemistry—that provide a foundation for understanding research in this area. This includes chromatography, absorption vs. adsorption, dissolution and precipitation, and liquid-liquid extraction. Drawing on these concepts, the paper then provides an explanation for non-technical audiences of the Argonne National Laboratory publication entitled Recovery of High Specific Activity Molybdenum-99 from Accelerator-Induced Fission on Low-Enriched Uranium for Technetium-99m Generators (Brown, M.A. et al., 2021) and related article Separation and Purification of Mo-99 Produced from Natural U3O8 Targets via Photo-Fission (Brown, M.A. et al., 2021).

Stamler, Bradley↗

Shining a Light on the Nucleus: Photonuclear Measurements from Correlations to Charmonium

The atomic nucleus is comprised of a collection of nucleons (protons and neutrons), which are bound together by the nucleon-nucleon (NN) interaction that originates from Quantum Chromodynamics (QCD). While most nucleons experience the force from the rest of the nu- cleus as a single net “mean-field” interaction that binds them relatively weakly, a small but impactful fraction are in configurations called “Short-Range Correlations” (SRCs), in which they pair with another nucleon at very short distance to experience strong interactions, sig- nificant binding, and high momentum. Hard, high-energy scattering reactions in which an SRC pair is broken apart, knocking both nucleons out of the nucleus, provide the ability to probe the details of these SRC configurations in the nucleus. Previous measurements have had limited statistics and kinematic reach, and the theoretical tools available were in- sufficient to draw quantitative conclusions regarding the ground-state properties of SRCs. The studies described in this thesis represent the first global analysis of SRC breakup mea- surements in order to present a unified picture of SRCs within light- to medium-size nuclei. This includes the use of a novel theoretical framework, the Generalized Contact Formalism, which connects scattering cross-section measurements and the ground-state properties of the SRC pair, to quantitatively interpret a variety of electron-scattering measurements. This is brought to culmination by a report on the first measurement of SRC pairs via the use of hard meson photoproduction reactions, which, despite differing significantly from the me- chanics of electron-scattering, is well-described under a common framework, pointing to a consistent and universal picture of SRCs across reaction channels. I also report on the first measurement of J/¿ photoproduction in the near- and below-threshold kinematic region, giving the first insights to the gluonic structure of bound nucleons in the large-x “valence” region and providing constraints on a gluonic “EMC effect”. In addition to these studies, I provide details on the search for Primakoff production of axion-like particles using the pho- toproduction data taken for this experiment, and I conclude by describing studies of nucleon spin structure measurements that will be performed at the forthcoming U.S. Electron-Ion Collider.

Pybus, Jackson↗