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At least 1,027 records · Page 57

Radiation-Induced Plutonium Redox Chemistry

Plutonium plays a key role in global actinide research and nuclear fuel cycle technologies, and yet, our fundamental understanding of its inherent radiation-induced chemical behavior is limited. These radiation-induced processes cannot simply be switched off, as they are as fundamentally inherent to plutonium as the impact of relativistic effects on its f-electrons. In less chemically complex actinide systems, such as aqueous solutions of neptunium and americium, , radiolysis products play a significant role in the redox cycling of their oxidation states. However, plutonium's multiple, coexisting, and chemically active oxidation states, which comprise of bare ions and dioxo cations, provide additional redox pathways that complicate radiation-induced processes. Oxidation state control is critical for the manipulation of plutonium, especially in used nuclear fuel reprocessing technologies, where oxidation specific states are successfully extracted, and others rejected. Consequently, mechanistically understanding the behavior of plutonium’s multiple oxidation states in the presence of intense ionizing radiation fields is essential for predicting the behavior of this element under multiple conditions that support the development and innovation of nuclear fuel cycle technologies. Here, we present recent advances in our understanding of plutonium radiation chemistry, including the first-ever multiscale model for predicting gamma radiation-induced plutonium redox chemistry, and new chemical kinetics for the reaction of plutonium and its complexes of tributyl phosphate (TBP), N,N-di-(2-ethylhexyl)butyramide (DEHBA), and N,N-di-(2-ethylhexyl)isobutyramide (DEHiBA) with transients radiolysis products, a measured using electron pulse radiolysis.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Integrated ab initio modelling of atomic ordering and magnetic anisotropy for design of FeNi-based magnets

We describe an integrated modelling approach to accelerate the search for novel, single-phase, multicomponent materials with high magnetocrystalline anisotropy (MCA). For a given system we predict the nature of atomic ordering, its dependence on the magnetic state, and then proceed to describe the consequent MCA, magnetisation, and magnetic critical temperature (Curie temperature). Crucially, within our modelling framework, the same ab initio description of a material’s electronic structure determines all aspects. We demonstrate this holistic method by studying the effects of alloying additions in FeNi, examining systems with the general stoichiometries Fe 4 Ni 3 X and Fe 3 Ni 4 X, for additives including X = Pt, Pd, Al, and Co. The atomic ordering behaviour predicted on adding these elements, fundamental for determining a material’s MCA, is rich and varied. Equiatomic FeNi has been reported to require ferromagnetic order to establish the tetragonal L1 0 order suited for significant MCA. Our results show that when alloying additions are included in this material, annealing in an applied magnetic field and/or below a material’s Curie temperature may also promote tetragonal order, along with an appreciable effect on the predicted hard magnetic properties.

36 MATERIALS SCIENCE↗

Data for "Integrated ab initio modelling of atomic order and magnetic anisotropy for rare-earth-free magnet design: effects of alloying additions in L1 0 FeNi."

We describe an integrated modelling approach to accelerate the search for novel, single-phase, multicomponent materials with high magnetocrystalline anisotropy (MCA). For a given system we predict the nature of atomic ordering, its dependence on the magnetic state, and then proceed to describe the consequent MCA, magnetisation, and magnetic critical temperature (Curie temperature). Crucially, within our modelling framework, the same ab initio description of a material’s electronic structure determines all aspects. We demonstrate this holistic method by studying the effects of alloying additions in FeNi, examining systems with the general stoichiometries Fe 4 Ni 3 X and Fe 3 Ni 4 X, for additives including X = Pt, Pd, Al, and Co. The atomic ordering behaviour predicted on adding these elements, fundamental for determining a material’s MCA, is rich and varied. Equiatomic FeNi has been reported to require ferromagnetic order to establish the tetragonal L1 0 order suited for significant MCA. Our results show that when alloying additions are included in this material, annealing in an applied magnetic field and/or below a material’s Curie temperature may also promote tetragonal order, along with an appreciable effect on the predicted hard magnetic properties.

36 MATERIALS SCIENCE↗

Enhanced accuracy through ensembling of randomly initialized auto-regressive models for dynamical systems

Computational mechanics simulations using traditional finite element methods (FEM) require prohibitively expensive computational resources for real-time engineering applications, design optimization, and digital twin implementations. While machine learning (ML) surrogate models offer significant computational speedups, autoregressive ML models for time-dependent mechanical systems suffer from error accumulation that compromises long-term prediction reliability - a critical concern for engineering applications where accuracy over extended time horizons is essential for safety and performance assessments. Here, we propose a deep ensemble framework specifically designed to address this challenge in computational mechanics applications, where multiple ML surrogate models with random weight initializations are trained in parallel and their predictions aggregated during inference. This approach leverages statistical diversity to maximize information gain from a fixed set of training data and to mitigate error propagation, while maintaining the computational efficiency that makes ML surrogates attractive for engineering practice. We validate the framework on three representative problems spanning critical areas of computational mechanics: stress field evolution in heterogeneous microstructures under complex loading (relevant to advanced materials design and composite analysis), planetary-scale shallow water dynamics (applicable to environmental and geotechnical engineering), and Gray-Scott reaction-diffusion systems (relevant to mass transport and chemical process engineering). Across all test cases, the ensemble approach demonstrates consistent error reduction of 15-33% compared to individual models. The codes for this work are available on GitHub (https://github.com/Graham-Brady-Research-Group/AutoregressiveEnsemble_SpatioTemporal_Evolution).

autoregressive prediction↗

A gene desert required for regulatory control of pleiotropic Shox2 expression and embryonic survival

ABSTRACT The Shox2 homeodomain transcriptional regulator is known for its critical functions during mouse embryogenesis, enabling accurate development of limbs, craniofacial structures, neural populations and the cardiac conduction system. At the genomic level, the Shox2 gene is flanked by an extensive gene desert, a continuous non-coding genomic region spanning over 500 kilobases that contains a multitude of evolutionarily conserved elements with predicted cis -regulatory activities. However, the transcriptional enhancer potential of the vast majority of these elements in combination with the biological necessity of the gene desert have not yet been explored. Using transgenic reporter assays in mouse embryos to validate an extensive set of stringent epigenomic enhancer predictions, we identify several novel gene desert enhancers with distinct tissue-specific activities in Shox2 expressing tissues. 4C-seq chromatin conformation capture further uncovers a repertoire of gene desert enhancers with overlapping activities in the proximal limb, in a compartment essential for Shox2 -mediated stylopod formation. Leveraging CRISPR/Cas9 to delete the gene desert region contained in the Shox2 topologically associated domain (TAD), we demonstrate that this complex cis -regulatory platform is essential for embryonic survival and required for control of region-specific Shox2 expression in multiple developing tissues. While transcription of Shox2 in the embryonic limb is only moderately affected by gene desert loss, Shox2 expression in craniofacial and cardiac domains is nearly abolished. In particular, Shox2 transcripts in the sinus venosus (SV) encompassing the sinoatrial node (SAN) were depleted in embryos lacking the gene desert, likely accounting for the embryonic lethality due to Shox2 -dependency of the SAN pacemaker. Finally, we discover a 1.5kb SV enhancer within the deleted gene desert region, which may act as a genomic module controlling the development of the cardiac conduction system. In summary, our results identify a gene desert indispensable for pleiotropic patterning and highlight the importance of these extensive regulatory landscapes for embryonic development and viability.

Abassah-Oppong, Samuel↗

Perturbative instability of nonergodic phases in non-Abelian quantum chains

An important challenge in the field of many-body quantum dynamics is to identify nonergodic states of matter beyond many-body localization (MBL). Strongly disordered spin chains with non-Abelian symmetry and chains of non-Abelian anyons are natural candidates, as they are incompatible with standard MBL. In such chains, real space renormalization group methods predict a partially localized, nonergodic regime known as a quantum critical glass (a critical variant of MBL). Here, this regime features a treelike hierarchy of integrals of motion and symmetric eigenstates with entanglement entropy that scales as a logarithmically enhanced area law. We argue that such tentative nonergodic states are perturbatively unstable using an analytic computation of the scaling of off-diagonal matrix elements and accessible level spacing of local perturbations. Our results indicate that strongly disordered chains with non-Abelian symmetry display either spontaneous symmetry breaking or ergodic thermal behavior at long times. We identify the relevant length and timescales for thermalization: Even if such chains eventually thermalize, they can exhibit nonergodic dynamics up to parametrically long timescales with a nonanalytic dependence on disorder strength.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Analysis of hydrogen and lithium isotopes using Laser-Induced Breakdown Spectroscopy

The detection and quantification of hydrogen (1,2,3H) and lithium (6,7Li) isotopes are critical to several energy and defense application areas, including hydrogen storage, nuclear forensics, and safeguards/non-proliferation. In this context, laser-induced breakdown spectroscopy (LIBS) is very promising and it comes with certain advantages such as rapid detection, and standoff capability. Although LIBS provides experimental simplicity and is capable of detecting all elements in the periodic table in any phase (solid, liquid, or gas), there exist certain challenges for isotopic analyses of H and Li due to spectral broadening, the presence of closely spaced fine and hyperfine structures, and line distortion effects (e.g., self-absorption and self-reversal) present in laser-produced plasmas. This article reports recent developments in H and Li isotopic analysis using LIBS, and existing challenges.

(020.3260) Isotope shifts, (140.3440) Laser-induce↗

Towards exascale for wind energy simulations

We examine large-eddy-simulation modeling approaches and computational performance of two open-source computational fluid dynamics codes for the simulation of atmospheric boundary layer flows that are of direct relevance to wind energy production. The first code, NekRS, is a high-order, unstructured-grid, spectral element code. The second code, AMR-Wind, is a second-order, block-structured, finite-volume code with adaptive mesh refinement capabilities. The objective of this study is to co-develop these codes in order to improve model fidelity and performance for each. These features will be critical for running ABL-based applications such as wind farm analysis on advanced computing architectures. To this end, we investigate the performance of NekRS and AMR-Wind on the Oak Ridge Leadership Facility supercomputers Summit, using 4 to 800 nodes (24 to 4,800 NVIDIA V100 GPUs), and Crusher, the testbed for the Frontier exascale system, using 18 to 384 Graphics Compute Dies on AMD MI250X GPUs. We compare strong- and weak-scaling capabilities, linear solver performance, and time to solution. We also identify leading inhibitors to parallel scaling.

17 WIND ENERGY↗

Simulation Tools for Characterizing Stress Distribution in Laser Welded Dissimilar Joints

This project focuses on developing a thermo-metallurgical-mechanical modeling method to accurately predict the microstructural evolution and residual stress in laser welding between dissimilar metals, such as HSLA steel and high carbon equivalent (CE) gear steel. The method leverages a comprehensive material database to model the temperature and rate dependent phase transformations, along with their associated effects on material properties, such as thermal expansion and flow stress, throughout the welding process. A key innovation is the incorporation of phase transformation and phase-specific properties, which enhances the accuracy of residual stress predictions. The mixture material in the fusion zone due to the dissimilar metals will also be addressed in the numerical model. This is especially critical in scenarios involving phase transformations in the fusion zone and heat-affected zone (HAZ), where the phase changes can induce substantial residual stress variations. The material database has been generated using JMatPro. The modeling approach is implemented through a custom User Material (UMAT) subroutine, executed with the commercial finite element software Abaqus.

36 MATERIALS SCIENCE↗

Simulation Tools for Characterizing Stress Distribution in Laser Welded Dissimilar Joints

This project focuses on developing a thermo-metallurgical-mechanical modeling method to accurately predict the microstructural evolution and residual stress in laser welding between dissimilar metals, such as HSLA steel and high carbon equivalent (CE) gear steel. The method leverages a comprehensive material database to model the temperature and rate dependent phase transformations, along with their associated effects on material properties, such as thermal expansion and flow stress, throughout the welding process. A key innovation is the incorporation of phase transformation and phase-specific properties, which enhances the accuracy of residual stress predictions. The mixture material in the fusion zone due to the dissimilar metals will also be addressed in the numerical model. This is especially critical in scenarios involving phase transformations in the fusion zone and heat-affected zone (HAZ), where the phase changes can induce substantial residual stress variations. The material database has been generated using JMatPro. The modeling approach is implemented through a custom User Material (UMAT) subroutine, executed with the commercial finite element software Abaqus.

36 MATERIALS SCIENCE↗

A Comprehensive Review of Selected Major Categories of Lithium Isotope Separation Techniques

The ability to generate materials with an enriched isotopic abundance, that is one that differs from natural abundance, is critical in terms of technology. Isotopes are used in a wide range of applications, including radioactive tracers, nondestructive tests, radiotherapy in human medicine, nuclear fuels, and isotope‐substituted compounds for chemistry and biology research, as well as environmental geochemical signature tracers. A commonly discussed research topic is the isotopic separation of various elements—uranium, hydrogen, lithium, and iodine, among many others. Among these isotopes, lithium isotopes are especially important in various applications including strategic areas. These isotopes are light and hence their separation techniques are not very obvious. Herein, all the main categories of Li isotope separation are reviewed in depth with a focus on electrochemical technologies for stable lithium isotope separation.

Murali, Arun↗

Bayesian sequential optimal experimental design for nonlinear models using policy gradient reinforcement learning

We present a mathematical framework and computational methods for optimally designing a finite sequence of experiments. This sequential optimal experimental design (sOED) problem is formulated as a finite-horizon partially observable Markov decision process (POMDP) under a Bayesian setting and with information-theoretic utilities. The formulation is general and may accommodate continuous random variables, non-Gaussian posteriors, and nonlinear forward models. The sOED design policy incorporates elements of feedback and lookahead simultaneously, and we show it to generalize the commonly-used batch and greedy design strategies. We solve for the sOED policy using the policy gradient (PG) method from reinforcement learning, and provide a derivation for the PG expression in the sOED context. Adopting an actor-critic approach, the policy and value functions are parameterized using deep neural networks and improved via PG estimates produced from simulated episodes of designs and observations. The new PG-sOED algorithm is first validated on a linear-Gaussian benchmark, and then compared against other design baselines on a sensor movement problem for contaminant source inversion in a convection-diffusion field. As a result, we provide explanation for the policy behaviors using knowledge of the underlying physical process.

97 MATHEMATICS AND COMPUTING↗

Unveiling damage mechanisms of chromium-coated zirconium-based fuel claddings at LWR operating temperature by in-situ digital image correlation

Here, we investigate the coupled thermomechanical fracture mechanisms of coated nuclear fuel claddings at Light Water Reactor (LWR) operating temperatures. These coated claddings are a highly attractive, near-term solution, which addresses the demands for accident-tolerant fuel systems and provide greater oxidation resistance. However, the fracture mechanisms of these coatings, which may create channels for oxidation ingression, must be fully understood prior to implementation. Thus, high-temperature expanding plug experiments were conducted on coated cladding specimens at a temperature of 315 °C, consistent with the operating environment of LWRs. Furthermore, in-situ thermomechanical deformation was measured with stereo digital image correlation during heating and mechanical testing to separately resolve contributions of thermal and mechanical strain. Digital image correlation, supported by acoustic emissions (AE) detection, was also leveraged to track cracking activity during loading. Coating fracture was found to initiate at total hoop strains of 0.34%. The thermal deformation of the coated claddings was investigated via finite element simulations, revealing a bidirectional stress-state within the coating with axial and circumferential strains of 0.026 and 0.031%. This bidirectional stress-state was attributed with the generation of off-axis fracture pattern within the coating as identified via post-experiment scanning electron microscopy. Thus, this study unveiled critical, coupled thermomechanical mechanisms governing the coating fracture of coated claddings at LWR temperatures.

36 MATERIALS SCIENCE↗

Tailoring the Structure of Carbon Molecular Sieves Derived from an Aromatic Polyamide

Energy-efficient and selective separation technologies are required to reclaim aqueous waste streams for reuse. Carbon molecular sieves (CMS) are one material capable of separating organic solvent and gaseous mixtures due to the presence of permanent, rigid, and molecular sieving pores and could potentially be used in aqueous separations. Here, a novel CMS material is derived from an aromatic polyamide precursor with tailored fabrication techniques. Structural characteristics of this CMS have been probed with various analyses and are potentially ideal for selective separations as adsorbents. In this work, elemental analyses provide insight about the potential chemical structures of CMS materials that result from degradation mechanisms. Gravimetric sorption data is used to estimate sorption, diffusion, and permeability selectivity with water and N, N-dimethylformamide. While challenges to the development and implementation of such carbonaceous materials remain, highly selective materials are critical starting points for enabling ultra-challenging separation processes of the future.

36 MATERIALS SCIENCE↗

Challenges and Gaps in the Development of Pulsed Power for Fusion Applications: A Preroadmapping Perspective From Industry, Academia, and National Laboratory Experts

Fusion energy meets the twenty-first century World Grand Challenge of sustainable, ubiquitous, and safer energy sources. However, harnessing the promise of fusion energy has proven elusive. The competing approaches to fusion power plant design include inertial confinement fusion, National Ignition Facility (ICF-NIF, Z machine, etc.,) magnetic confinement fusion (MCF-Tokamak, stellarators, etc.), and other approaches that show promise in small- (flow stabilized Z pinches) or large-scale applications. These approaches are being accelerated with private and public funding and seek to demonstrate the feasibility of different approaches to fusion-based power plants. Yet, how can the necessary pulsed power technologies for these disruptive technology bases be accelerated with no clear “Dominant Design?” Roadmapping holds the promise to identify and develop common critical pulsed power components for laboratory, prototype, and commercial fusion, and can accelerate the commercialization of fusion reactor designs. A preroadmapping Workshop on Pulsed Power for Fusion was held at the IEEE International Pulsed Power Conference in San Antonio, TX, USA, in June 2023. The workshop had 177 attendees. Here, the common elements for many of the ICF technologies vying for dominant design were identified. The advancement of these technologies through roadmapping will enhance commercial expectations that require their rapid and innovative development in the next five years, as well as the next five to ten years. The key technologies identified that underpin and limit the advancement of fusion power include pulsed power technologies such as energy storage, high-voltage switching, additive manufacturing, and modular pulsed power circuit topologies. In conclusion, they are the focus of our effort in the following roadmap scenario, which will delineate potential paths to technology development.

Curry, Randy D. [I-Pulse Group, Albuquerque, NM (U↗

High-Power Electric Vehicle Charging Hub Integration Platform (eCHIP): Site Energy Management System Platform Development

A site energy management system is a critical component of future high-power EV charging hubs. It monitors and supervises all inter-hub operations, coordinates grid interactions, and implements energy management strategies and load-sharing controls at various levels and time scales. This report provides a comprehensive high-level overview and guidelines on the essential elements of such energy management systems. These elements primarily focus on the core functions, architecture, and monitoring aspects of site energy management. The core functions define the grid services and operational objectives that a charging hub is expected to provide and achieve. The architectural section investigates the coordination between hub assets, different control schemes, and their potential benefits and drawbacks. Lastly, the report discusses the needs, types, and functionalities of a monitoring and visualization system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Computational Modeling of Graphite Degradation due to Molten Salt Infiltration and Wear

Molten-salt reactors (MSRs) represent a promising next-generation reactor design, with graphite serving as a moderator and/or reflector in several designs. However, due to limited experimental data and operational experience, a technical understanding of the structural integrity of graphite in molten salt environments remains incomplete. This report presents a modeling-based evaluation of graphite degradation in MSR environments, focusing on the effects of salt infiltration in fuel salt-based designs and surface wear in pebble bed reactor designs. The objective of this study is to enhance understanding of the structural integrity challenges posed by these degradation mechanisms and to provide a framework for assessing graphite behavior in MSRs. The first part of the report investigates the phenomenon of molten salt infiltration into graphite. This infiltration occurs when molten salt permeates the interconnected pore structure of the graphite moderator, driven by factors such as pressure differentials and the physical properties of both the salt and graphite. The infiltration process is influenced by characteristics of the pore structure, viscosity of the molten salt, and the interfacial energies between the graphite, salt, and the atmosphere within the graphite pore. Utilizing a coupled multiphysics modeling approach with Grizzly software, the study evaluates the stress induced by internal heat sources due to infiltration, which can lead to structural concerns. This evaluation is crucial for understanding how infiltration affects the mechanical integrity of graphite components in MSRs. The study considers the Molten-Salt Reactor Experiment (MSRE) graphite stringer geometry due to the availability of relevant data. Through detailed finite element analysis, the study examines stress distributions at varying infiltration percentages, revealing that stress levels increase with higher amounts of infiltration. Rare-event simulations, using the parallel subset simulation (PSS) framework, further quantify the failure probabilities under input uncertainties, with a user-specified failure metric. The PSS framework also identifies critical input parameters that significantly affect the stress values, including infiltration amount, thermal conductivity, and power density. Additionally, considering realistic reactor scenarios, the analysis was performed to account for the combined effects of radiation and infiltration, and modeling strategies on how to analyze new reactor designs or new graphite grades are discussed. The second part of the report focuses on wear mechanisms in pebble bed-based MSRs. As graphite fuel pebbles interact with the graphite reflector block, wear can result in material loss and the formation of surface defects, which may act as stress concentrators. A similar multiphysics modeling framework is employed to assess the impact of wear on the structural integrity of graphite components. This study considers a generic fluoride-cooled high-temperature reactor (gFHR) design due to the availability of comprehensive data. Worst-case scenario dimensions of the reflector blocks were analyzed under thermal and radiation conditions. Subsequently, wear in the form of idealized pits and grooves is modeled on the inner surface of the graphite block, with the maximum stress from previous simulations. The simulations show that groove-type defects are more detrimental than pits, leading to higher stress concentrations. Considering worst-case simulation scenarios and experimental wear rates, it was determined that the formation of a surface defect critical enough to affect the stress may not be possible in a gFHR design. Overall, the findings of this research contribute to the development of robust modeling tools for predicting graphite behavior under various operational conditions in MSRs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗