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At least 739 records · Page 41

Integral Experiment Final Design for Thermal/Epithermal eXperiments with 233U3O8 ZPR Fuel Elements and Polyethylene (IER-329 CED-2 Report)

This report documents the integral experiment final design for IER-329, Thermal/Epithermal eXperiments (TEX) with 233 U 3 O 8 Zero Power Reactor (ZPR) Fuel Elements and Polyethylene. IER-329 (TEX-23) is the third baseline design in the Thermal/Epithermal eXperiments (TEX) series led by Lawrence Livermore National Laboratory (LLNL) and funded by the DOE’s Nuclear Criticality Safety Program. This experiment was designed to address the existing 233U integral benchmark experiments over prediction in k eff by up to 2% for thermal systems and under-prediction in k eff by up to 4% for intermediate systems. The TEX-23 design utilizes assemblies of 233 U 3 O 8 Zero Power Reactor (ZPR) fuel elements moderated and reflected by high-density polyethylene. This design is similar to the existing TEX-Pu and TEX-HEU designs, utilizing an adjustable moderator to tune the neutron energy spectra and modular layers for the incorporation of diluent materials.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Preliminary NBSR Design-Demonstration Element Thermal-Hydraulics and Structural Analyses

1.1 OBJECTIVE The United State High Performance Research Reactor (USHPRR) program aims to eliminate more than 200kg of High Enriched Uranium (HEU) from commerce annually by converting five U.S. high-performance research reactors and one associated critical assembly to Low Enriched Uranium (LEU) fuel using a high-density alloy of uranium-10 wt% molybdenum (U-10Mo). The National Bureau of Standards Reactor (NBSR) is one of five research reactors selected for this program. The objective of this report is to provide preliminary thermal-hydraulic and mechanical analyses of the hydrodynamic effects in the NBSR Design Demonstration Element (DDE) under conservative approximations for the plate power distribution. This report provides details on the modeling approach and the simulation results obtained, including pressure, flow velocity, temperature, and oxide layer over the design demonstration experiment for the irradiation cycles in the Belgian Reactor (BR)-2.

42 ENGINEERING↗

Autonomous Intelligence Measurements and Sensor Systems (AIMS): Gaussian Processes in Remote Sensing: Literature Review

Power grid resilience and reliability is crucial to supporting critical infrastructure. Service interruptions can have devastating consequences to communication, emergency, and transportation services, just to name a few. In addition to infrastructure, power services are crucial to everyday life. Nearly every element of modern-day living relies on a stable and functioning power grid - heating and cooling systems to lighting, refrigeration, telecommunications, and internet access. Interruptions in the power supply can range from minor inconveniences, such as the temporary loss of internet or television services, to more significant problems, like the inability to access medical equipment or emergency services during critical situations. As climate conditions worsen, the reliability of the power grid becomes even more significant. Extreme weather events, such as hurricanes, wildfires, or severe storms, can cause serious damage to power infrastructure, leading to prolonged power outages. Rising temperatures and changing weather patterns can strain the grid, resulting in increased demand for electricity, stressing transmission and distribution systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Strong and ductile FeNiCoAl-based high-entropy alloys for cryogenic to elevated temperature multifunctional applications

The highly tunable properties of multi-principal element alloys, commonly known as high-entropy alloys (HEAs), provide a remarkable potential for the development of superior materials for critical structural applications that involve extreme conditions. However, the optimization of the properties of HEAs has been primarily limited to behavior at either low or high temperatures. We report on a non-equiatomic, heterostructured, high-entropy alloy FeNiCoAlTaB which possesses remarkable combinations of mechanical properties across a wide range of temperatures from 77 K to 1073 K. The current metastable alloy presents good ductility and superior engineering tensile strengths of 2.2 GPa, 1.4 GPa, 800 MPa, and 500 MPa at 77 K, 298 K, 873 K, and 1073 K, respectively. This behavior is achieved by a synergic sequence of individual mechanisms that are activated at different temperatures. The alloy even displays pseudoelasticity at 77 K with an applied load up to 2 GPa. This work provides a methodology for tailoring structural heterogeneity and metastability in the design and fabrication of multifunctional HEAs that will outperform known metals and alloys over a wide range of temperatures.

36 MATERIALS SCIENCE↗

Solving the “Coloring Problem” in InPd 3– x Ag x ( x = 0–0.7) by Phase Diagrams Modeling and Diffraction Experiments

Here, a series of InPd 3–x Ag x (x = 0–1) compositions were synthesized by conventional high-temperature synthesis, and as-synthesized samples were characterized by powder X-ray diffraction experiments. Up to x = 0.7, InPd 3–x Ag x adopts the ternary substitutional variant of the InPd 3 structure (TiAl 3 -type), when x > 0.7, elemental Ag starts to segregate along with the main phase. Accurate structural characterization in InPd 3–x Ag x faces a critical challenge due to the narrow X-ray scattering contrast among constituents In, Pd, and Ag and nearly identical neutron scattering lengths of Pd and Ag. To overcome this “coloring problem”, a combination of calculation of phase diagrams modeling (CALPHAD) and diffraction techniques (X-ray and neutron) was employed. In the compositional range 0 ≤ x ≤ 0.7, InPd 3–x Ag x presents a ternary variant of the TiAl 3 -type structure, where Ag atoms selectively substitute one (the 2b Wyckoff site) of the two Pd sites in InPd 3 . Notably, in contrast to the isologous InPd 3–x Cu x (x = 0–1) system, Ag substitution does not form an ordered VRh 2 Sn-type structure at the limiting composition. The distinct site preference in InPd 3–x Ag x is elucidated by charge population analysis, electronic structure calculations, and orbital-resolved chemical bonding investigations, and the extent of substitution is supported by formation free energy calculations.

36 MATERIALS SCIENCE↗

An Atom-Precise Approach to Damp First-Order Phase Transitions and Its Implications for Neuromorphic Signal Processing

Neuromorphic computing inspired by mammalian intelligence aims to emulate the nonlinear dynamics of biological neurons and synapses to achieve fast, low-energy, and highly efficient information processing. Brain-inspired computing relies on the design and discovery of materials exhibiting nonlinear current–voltage profiles, frequently underpinned by electronic state transitions, to achieve spiking neurons and dynamically tunable synapses. A signature challenge in the design of artificial neurons is controlling the steepness of first-order transitions in active elements, as abrupt transitions are at risk of driving unstable voltage and temperature oscillations, which result in catastrophic device failure. A critical knowledge gap is the lack of structure–function correlations mapping the composition and atomistic structure of crystalline solids to nonlinear dynamical response characteristics. Here, we address the key question of how modification of atomistic structure correlates with alteration of neuron-like functionality. Constructing oscillator circuits from millimeter-scale single crystals enables high-resolution atomic structure solutions, which we use to demonstrate that the selective positioning of Pb cations modifies charge ordering along a one-dimensional CuxV2O5 framework even at low insertion stoichiometries, thereby providing an atom-precise design parameter for damping first-order transitions. We use temperature-variant X-ray diffraction and X-ray spectroscopy to elucidate the suppression of Cu-ion shuttling based on the precise positioning of Pb ions in seven-coordinated tunnel interstitial sites as the mechanistic basis for transition broadening, thus bridging a critical gap between statistical mechanics and quantum chemical descriptions of phase transitions. Such mechanistic understanding thus paves the way to site-selective modification strategies for modulating the sharpness of first-order transitions, with an exemplary demonstration here in tuning neuronal signal processing.

Crystal structure↗

RNA-Puzzles Round V: blind predictions of 23 RNA structures

RNA-Puzzles is a collective endeavor dedicated to the advancement and improvement of RNA three-dimensional structure prediction. With agreement from structural biologists, RNA structures are predicted by modeling groups before publication of the experimental structures. We report a large-scale set of predictions by 18 groups for 23 RNA-Puzzles: 4 RNA elements, 2 Aptamers, 4 Viral elements, 5 Ribozymes and 8 Riboswitches. We describe automatic assessment protocols for comparisons between prediction and experiment. Our analyses reveal some critical steps to be overcome to achieve good accuracy in modeling RNA structures: identification of helix-forming pairs and of non-Watson–Crick modules, correct coaxial stacking between helices and avoidance of entanglements. Three of the top four modeling groups in this round also ranked among the top four in the CASP15 contest.

59 BASIC BIOLOGICAL SCIENCES↗

Description of the Fission Process: Nuclear Models for Fission Dynamics

Nuclear fission is the splitting of a heavy nucleus into two or more fragments, a process that releases a substantial amount of energy. It is ubiquitous in modern applications, critical for national security, energy generation and reactor safeguards. Fission also plays an important role in understanding the astrophysical formation of elements in the universe. Eighty years after the discovery of the fission process, its theoretical understanding from first principles remains a great challenge. In this paper, we present promising new approaches to make more accurate predictions of fission observables.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Binding profiles for 961 Drosophila and C. elegans transcription factors reveal tissue-specific regulatory relationships

A catalog of transcription factor (TF) binding sites in the genome is critical for deciphering regulatory relationships. Here, we present the culmination of the efforts of the modENCODE (model organism Encyclopedia of DNA Elements) and modERN (model organism Encyclopedia of Regulatory Networks) consortia to systematically assay TF binding events in vivo in two major model organisms,Drosophila melanogaster(fly) andCaenorhabditis elegans(worm). These data sets comprise 605 TFs identifying 3.6 M sites in the fly and 356 TFs identifying 0.9 M sites in the worm, and represent the majority of the regulatory space in each genome. We demonstrate that TFs associate with chromatin in clusters termed “metapeaks,” that larger metapeaks have characteristics of high-occupancy target (HOT) regions, and that the importance of consensus sequence motifs bound by TFs depends on metapeak size and complexity. Combining ChIP-seq data with single-cell RNA-seq data in a machine-learning model identifies TFs with a prominent role in promoting target gene expression in specific cell types, even differentiating between parent–daughter cells during embryogenesis. These data are a rich resource for the community that should fuel and guide future investigations into TF function. To facilitate data accessibility and utility, all strains expressing green fluorescent protein (GFP)-tagged TFs are available at the stock centers for each organism. The chromatin immunoprecipitation sequencing data are available through the ENCODE Data Coordinating Center, GEO, and through a direct interface that provides rapid access to processed data sets and summary analyses, as well as widgets to probe the cell-type-specific TF–target relationships.

Biochemistry & Molecular Biology↗

PID-Regulated Heating System for PIP-II Reference Line

The Proton Improvement Project-2 centers on building a new superconducting linear particle accelerator (Linac) at Fermilab. At the heart of the accelerator is the reference line, a critical system that defines the ideal path for the particle beam as it passes through magnets, RF cavities, and other beamline elements. Temperature stability is crucial for the reliable operation of RF components, such as mixers and filters. Fluctuations affect key performance parameters like conversion loss, isolation, and linearity. To mitigate any drift caused by ambient temperature changes, a heating plate assembly is utilized to maintain key components at a controlled temperature of 40°C. The system utilizes an aluminum 36”x36”x0.5” heat plate powered by a MOSFET-based control circuit, delivering approximately 460 W of thermal energy through a resistor array. Real-time temperature feedback is provided by a PT100 Resistance Temperature Detector (RTD), which interfaces with a Proportional–Integral–Derivative (PID) control algorithm to maintain closed-loop temperature regulation. The control signal actively modulates the gate voltage of an N channel MOSFET, dynamically adjusting power delivery in response to deviations from the temperature setpoint. Simulations and LTspice models validate the functionality and responsiveness of the circuit under varying conditions. The prototype has successfully demonstrated stable thermal control, paving the way for integration into the PIP-II infrastructure. The final design will feature an expanded resistor array, as well as communication with a PLC for continuous data acquisition and diagnostics. This work directly supports Fermilab’s broader mission by contributing to the stability and reliability of core accelerator systems, enhancing the precision of particle beam delivery for future physics experiments.

Mosher, Alexander [Fermilab]↗

Health Physics Research Reactor Criticality Accident Alarm System Benchmark Overview

From the countless critical experiments performed in the world during the past century, high-quality integral benchmarks experiments have been collected and gathered into the International Handbook of Evaluated Criticality Safety Benchmark Experiments (ICSBEP Handbook), managed by the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Working Group. This information preservation and dissemination effort is crucial for reactor licensing as well as criticality and radiation transport modeling validation. This summary reports on the status of a tentative benchmark addition to the ICSBEP Handbook. The proposed benchmark arises from legacy operation data of the Oak Ridge National Laboratory (ORNL) Health Physics Research Reactor (HPRR). The HPRR was a small, unmoderated, unshielded fast burst reactor that was used for research in health physics and radiobiology as well as teaching and training. As part of a comprehensive investigation of the available HPRR operation data and characteristics, different possibilities for use of the valuable results were studied. A critical experiment benchmark evaluation was performed, analyzing data coming from sub-critical and critical operation of the HPRR during operator training, steady-state irradiation of samples and before critical bursts. The results of the evaluation do not satisfy for the ICSBEP standards as the benchmark relative standard uncertainty is of about 4% for k eff , and the relative difference between sample calculations and expected k eff results is of about 1.5%. Due to those unsatisfactory results, it was decided not to pursue critical experiments evaluation of the HPRR presently and to focus instead on shielding type data for the creation of a criticality accident alarm system (CAAS) and shielding category benchmark, which is currently very scarce in the ICSBEP handbook—especially concerning critical, pulsed assembly, or reactor operation data. Several dosimetry and shielding experiments from HPRR burst operation were evaluated, with different benchmark metrics as sulfur fluence, Element 57 dose, or neutron fluence at different distances and under different shield materials conditions. An evaluation focusing on the Element 57 neutron dose as a benchmark metric was submitted to the ICSBEP Technical Review Group (TRG) meeting in October 2021, and the inclusion of the evaluation in the ICSBEP Handbook was deferred. The main change proposed by the international experiment evaluation experts is to use the neutron fluence measured by Bonner spheres as a benchmark metric. This represents a quantity closer to that actually measured by the experimentalists of the HPRR compared to the Element 57 dose, which adds another step of data transformation, thus potentially adding uncertainty to the benchmark. The evaluation has been updated and will be submitted to the 2022 ICSBEP TRG meeting for inclusion in the 2023 edition of the ICSBEP Handbook. The evaluation is performed using the KENO and MAVRIC combination from the SCALE 6.2.4 code suite which was previously used in similar CAAS benchmarks to allow for the use of variance reduction techniques.

61 RADIATION PROTECTION AND DOSIMETRY↗

Stress field and interaction forces between dislocations and precipitate distributions

A computational method is developed for calculation of the stress field and interaction forces between dislocations and precipitates of arbitrary shape and distribution. The internal stress generated by precipitates due to coherency strain is implemented within the discrete dislocation dynamics (DDD) framework. The s-version finite element method (s-FEM), which models a precipitate of arbitrary shape using a local mesh is used to calculate coherency stress fields. The method facilitates meshing precipitate volumes of arbitrary geometry, and multiple local meshes can be superimposed at various positions of the global mesh. Accuracy and convergence conditions of the method are established. For a single precipiate, the method is shown to be 3.5 times faster than a standard FEM calculation for the same accuracy, and the gain in speed increases with the number of precipitates. The CRSS of spherical precipitates is found to be higher than disk-shaped precipitates of the same volume fraction.

42 ENGINEERING↗

Critical Materials Supply Chain White Paper (April 2020)

The DOE Office of Energy Efficiency and Renewable Energy (EERE) Advanced Manufacturing Office (AMO) partners with industry, small business, universities, and other stakeholders to identify and invest in emerging technologies with the potential to create high-quality domestic manufacturing jobs and enhance the global competitiveness of the United States

Advanced Manufacturing Office↗

Generalist multimodal AI: A review of architectures, challenges and opportunities

Multimodal models are expected to be a critical component to future advances in artificial intelligence. Here, this field is starting to grow rapidly with a surge of new design elements motivated by the success of foundation models in natural language processing (NLP) and vision. It is widely hoped that further extending the foundation models to multiple modalities (e.g., text, image, video, sensor, time series, graph, etc.) will ultimately lead to generalist multimodal models, i.e. one model across different data modalities and tasks. However, there is little research that systematically analyzes recent multimodal models (particularly the ones that work beyond text and vision) with respect to the underling architecture proposed. Therefore, this work provides a fresh perspective on generalist multimodal models (GMMs) via a novel architecture and training configuration specific taxonomy. This includes factors such as Unifiability, Modularity, and Adaptability that are pertinent and essential to the wide adoption and application of GMMs. The review further highlights key challenges and prospects for the field and guide the researchers into the new advancements.

Artificial intelligence (AI)↗

Characterization of Lanthanum Monazite Surface Chemistry and Crystal Morphology through Density Functional Theory and Experimental Approaches

Monazite is a rare earth element (REE)-containing mineral that consists of (REE)PO 4 formal units and is one of the most important sources of these critical materials. The concentration of REEs from mined monazite ore often involves froth flotation, which is a beneficiation process that enhances the efficiency of downstream processing. The effectiveness of froth flotation is largely governed by the ability of collector agents to selectively bind to monazite particles. Thus, a molecular-level understanding of monazite interfacial chemistry is integral to the design of effective collector agents. To address this need, we performed density functional theory (DFT) calculations and a variety of experimental techniques to characterize La-monazite and elucidate its crystal morphology. Interestingly, we find minimal differences in the predicted morphologies of La-monazite for hydrous and anhydrous environments, which are largely dominated by low-index facets (e.g., {110}, {100}, and {010}). Indexing of synthesized La-monazite crystals via X-ray diffraction also uncovers {110} and {100} as the predominant facets. The average surface energies of 0% and 100% water coverage La-monazite crystals were predicted to be 0.87 and 0.76 J/m 2 , respectively, while calorimetry suggests values of 1.30 and 1.15 J/m 2 , respectively. The apparent discrepancies between the theoretical and experimental values are expected and attributed to defects present in physical crystals, in contrast to the perfect mineral surfaces in simulations. The difference in surface energy between the 0% and 100% water coverage morphologies predicted by theory is consistent with the value measured via calorimetry. DFT reveals a wide range of adsorption energies for water across the studied facets, but in all cases, water is predicted to strongly bind to monazite surfaces with an average adsorption energy of -92.7 kJ/mol for a La-monazite single crystal. Finally, this study provides the groundwork necessary for the rational design of froth flotation collector agents by granting molecular-level insight into the predominant facets of monazite.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Highly dense atomic Fe–Ni dual metal sites for efficient CO 2 to CO electrolyzers at industrial current densities

Carbon-supported, atomically dispersed, nitrogen-coordinated metal sites (e.g., Fe and Ni) are arguably the most promising catalysts for the electrochemical reduction of CO 2 to CO due to their unique catalytic properties and the use of earth-abundant elements. However, conventional single metal sites are constrained by their structural simplicity, causing either too weak or too strong absorption/desorption of multiple critical intermediates (e.g., *COOH and *CO). Current catalysts also suffer from ultra-low loadings (<1.0 wt%) of atomic metal active sites in catalysts, leading to inadequate performance for CO 2 -to-CO conversion. Here, we develop dual Ni/Fe metal site catalysts with significantly increased atomically dispersed metal loadings (up to 4.8 wt%). A gas-phase chemical vapor deposition (CVD) approach to introducing single Ni sites was integrated with Fe 2 O 3 /ZIF-8 precursors, followed by an optimal thermal activation. The optimized CVD-Ni/Fe–N–C catalyst exhibited remarkable electrocatalytic performance for the CO 2 reduction to CO in a continuous membrane-electrode-assembly electrolyzer, achieving a maximum CO faradaic efficiency (FE CO ) of 96% at a current density of 700 mA cm −2 in a near-neutral electrolyte. Furthermore, a desirable but challenging acidic flow-cell electrolyzer was designed using this dual metal site catalyst to improve CO 2 utilization, accomplishing a FE CO of up to 95% at a CO partial current density close to 600 mA cm −2 . Density functional theory (DFT) calculations suggest a synergetic effect between Fe–Ni pairs facilitating *COOH intermediate formation and *CO desorption simultaneously during CO 2 to CO conversion. This is key to breaking the linear scaling relationship of conventional single-metal site catalysts during the CO 2 reduction reaction.

36 MATERIALS SCIENCE↗

Data-driven electrolyte design for lithium metal anodes

Improving Coulombic efficiency (CE) is key to the adoption of high energy density lithium metal batteries. Liquid electrolyte engineering has emerged as a promising strategy for improving the CE of lithium metal batteries, but its complexity renders the performance prediction and design of electrolytes challenging. Here, we develop machine learning (ML) models that assist and accelerate the design of high-performance electrolytes. Using the elemental composition of electrolytes as the features of our models, we apply linear regression, random forest, and bagging models to identify the critical features for predicting CE. Our models reveal that a reduction in the solvent oxygen content is critical for superior CE. We use the ML models to design electrolyte formulations with fluorine-free solvents that achieve a high CE of 99.70%. This work highlights the promise of data-driven approaches that can accelerate the design of high-performance electrolytes for lithium metal batteries.

25 ENERGY STORAGE↗