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At least 757 records · Page 42

Task-specific sensor optical designs

A method and system architecture for designing a compressive sensing matrix for machine learning includes receiving an image associated with a classification task and; generating a sensing matrix. The sensing matrix includes an array of nonzero elements of the image. A prism array of prism elements is in communication with the sensing matrix. A row of values corresponding with an input angle of the prism array is mapped to a respective column corresponding with a detector. Then the detector detects light refracted at an output angle dictated by the physical shape of the prism element. A physical model of the detector is fabricated and generates a compressed representation of the image. A machine learning classification algorithm is applied to the compressed representation of the image and generates an optimized non-invertible final determination of the image.

Birch, Gabriel Carlisle↗

External-Field-Induced Phase Transformation and Associated Properties in a Ni 50 Mn 34 Fe 3 In 13 Metamagnetic Shape Memory Wire

Metamagnetic shape memory alloys exhibit a series of intriguing multifunctional properties and have great potential for applications in magnetic actuation, sensing and magnetic refrigeration. However, the poor mechanical properties of these alloys with hardly any tensile deformability seriously limit their practical application. In the present work, we developed a Ni-Fe-Mn-In microwire that exhibits both a giant, tensile superelasticity and a magnetic-field-induced first-order phase transformation. The recoverable strain of superelasticity is more than 20% in the temperature range of 233–283 K, which is the highest recoverable strain reported heretofore in Ni-Mn-based shape memory alloys (SMAs). Moreover, the present microwire exhibits a large shape memory effect with a recoverable strain of up to 13.9% under the constant tensile stress of 225 MPa. As a result of the magnetic-field-induced first-order phase transformation, a large reversible magnetocaloric effect with an isothermal entropy change ΔS m of 15.1 J kg –1 K –1 for a field change from 0.2 T to 5 T was achieved in this microwire. The realization of both magnetic-field and tensile-stress-induced transformations confers on this microwire great potential for application in miniature multi-functional devices and provides an opportunity for multi-functional property optimization under coupled multiple fields.

36 MATERIALS SCIENCE↗

Transverse oscillating bubble enhanced laser-driven betatron X-ray radiation generation

Abstract Ultrafast high-brightness X-ray pulses have proven invaluable for a broad range of research. Such pulses are typically generated via synchrotron emission from relativistic electron bunches using large-scale facilities. Recently, significantly more compact X-ray sources based on laser-wakefield accelerated (LWFA) electron beams have been demonstrated. In particular, laser-driven sources, where the radiation is generated by transverse oscillations of electrons within the plasma accelerator structure (so-called betatron oscillations) can generate highly-brilliant ultrashort X-ray pulses using a comparably simple setup. Here, we experimentally demonstrate a method to markedly enhance the parameters of LWFA-driven betatron X-ray emission in a proof-of-principle experiment. We show a significant increase in the number of generated photons by specifically manipulating the amplitude of the betatron oscillations by using our novel Transverse Oscillating Bubble Enhanced Betatron Radiation scheme. We realize this through an orchestrated evolution of the temporal laser pulse shape and the accelerating plasma structure. This leads to controlled off-axis injection of electrons that perform large-amplitude collective transverse betatron oscillations, resulting in increased radiation emission. Our concept holds the promise for a method to optimize the X-ray parameters for specific applications, such as time-resolved investigations with spatial and temporal atomic resolution or advanced high-resolution imaging modalities, and the generation of X-ray beams with even higher peak and average brightness.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Liquid crystalline epoxy networks with exchangeable disulfide bonds

In this study, a liquid crystalline epoxy network (LCEN) with exchangeable disulfide bonds is synthesized by polymerizing a biphenyl-based epoxy monomer with an aliphatic dicarboxylic acid curing agent containing a disulfide bond. The effect of disulfide bonds on curing behavior and liquid crystalline (LC) phase formation of the LCEN is investigated. The presence of the disulfide bonds results in an increase in the reaction rate, leading to a reduction in liquid crystallinity of the LCEN. In order to promote LC phase formation and stabilize the self-assembled LC domains, a similar aliphatic dicarboxylic acid without the disulfide bond is used as a co-curing agent to reduce the amount of exchangeable disulfide bonds in the system. After optimizing the molar ratio of the two curing agents, the resulting LCEN exhibits improved reprocessability and recyclability because of the disulfide exchange reactions, while preserving LC properties, such as the reversible LC phase transition and macroscopic LC orientation, for shape memory applications.

36 MATERIALS SCIENCE↗

Carbide Particle Redistribution in U-10Mo Alloy during Hot and Cold Rolling Processes: Synthetic Microstructure-Based Finite-Element Approach

The influence of initial carbide particle distribution features on particle fracture and the evolution of stringer distribution within an alloy of uranium with 10 weight percent molybdenum during cold rolling was investigated in this study. This work will provide guidance to casting optimization work and identify actionable process changes to eliminate the surface features directly attributed to carbides. In a previous study, various synthetic microstructure-based finite-element (FE) models were generated with consideration of different parameters (i.e., particle shape, particle volume fraction, and particle distribution), and used to examine the effects of hot rolling on the microstructure evolution. In this study, microstructures after ~80% hot rolling were used as the initial microstructures for the subsequent cold rolling simulation. Plane-strain compression loading was employed in the FE models to simulate cold rolling with reductions from ~80% to ~94%. Stringer analyses with the consideration of particle fracture were then performed with the simulated cold rolling results. The results of void evolution analyses show that microstructures with elliptical particles incorporate a much larger (almost double) void volume fraction than those with circular particles, indicating that the elliptical particles are fractured more easily than the circular ones. The results from the fracture mode analyses show that, under the adopted simple compression loading assumption, almost all the particles (i.e., >99%) were fractured by tensile separation. The results of stringer analyses show that, during cold rolling, the stringer volume fractions increase substantially due to the particle fracture, especially for the microstructures with the elliptical particles, and that the stringer volume fractions from stringers comprising many particles tend to increase faster. The maximum stringer lengths for the microstructures with circular particles tend to remain constant or decrease during cold rolling, whereas those for elliptical particles tend to slightly increase after a slight decrease. The number of particles at the surface increases very rapidly due to particle fracture during cold rolling.

36 MATERIALS SCIENCE↗

Microstructure Alignment Effects from Engineered Cooling during Additive Manufacturing of Alnico Magnets from Prealloyed Powder

Alnico is a rare-earth free; permanent magnet (PM) which maintains its saturation magnetization while at temperatures up to 550°C but lacks the coercivity and energy product needed for a wide range of demanding applications. With an optimal set of processing and manufacturing techniques, Alnico could replace Dy-free Nd-Fe-B magnets in certain applications if the microstructure is textured in a $\langle$001$\rangle$ direction. Additive manufacturing (AM) of near-net-shape magnets may provide such texture. To investigate the possibility, directed-energy deposition (DED) in conjunction with an actively cooled substrate was used to build samples with a compositionally modified, gas-atomized, Alnico 8 alloy. The resulting samples were solutionized and quenched, followed by magnetic annealing and a heat treatment. Magnetic properties and microstructures are compared to previous work.

36 MATERIALS SCIENCE↗

Optimization of Fairing Geometry for ORPC Modular RivGen Power System: Cooperative Research and Development (Final Report)

The work will optimize the hydrodynamic performance and flow augmentation of Ocean Renewable Power Company's (ORPC) modular fairing for their cross-flow marine hydrokinetic (MHK) turbine, using a computational fluid dynamics study. The influence of the fairing cross-sectional shape and rotor-fairing spacing will be assessed, to maximize power production and minimize structural loads.

16 TIDAL AND WAVE POWER↗

Magnetic cores with high reluctance differences in flux paths

Embodiment of the present invention includes a magnetic structure and a magnetic structure used in a direct current (DC) to DC energy converter. The magnetic structure has an E-core and a plate, with the plate positioned in contact or in near contact with the post surfaces of the E-core. The E-core has a base, a no-winding leg, a transformer leg, and an inductor leg. The no-winding leg, the transformer leg, and the inductor leg are perpendicular and magnetically in contact with the base. The plate is a flat slab with lateral dimensions generally larger than its thickness. The plate has a plate nose that overlaps a top no-winding leg surface of the no-winding leg with a no-winding gap area to form a no-winding gap with a no-winding gap reluctance. The plate also has a plate end that overlaps a top inductor leg surface of the inductor leg with an inductor gap area to form an inductor gap with an inductor gap reluctance. In some embodiments, e.g., where the duty cycle is less than 50 percent, the inductor gap reluctance will be designed to be less than the no-winding gap reluctance. In these cases, the majority of the magnetic flux that passes through the transformer leg will return through the inductor leg, instead of through the no-winding leg. The inductor and no-winding gap reluctances can he adjusted, so that the electromotive force applied to a charge passing through the inductor will partially cancel the electromotive force applied by the transformer secondary. The gap reluctance ratio can be defined, so that the difference in secondary and inductor electromotive forces is equal to the output voltage defined by an optimal no-ripple duty cycle. In this way no changing current is required through the inductor to create a dI/dt inductive voltage drop across the output inductor. Zero output current ripple is achieved.Various embodiments of the plate, plate shape, and no-winding leg are disclosed. These embodiments allow achieving a high ratio of no-winding gap reluctance to inductor gap reluctance, for practical, affordable magnetic material structures and aspect ratios. A high gap reluctance ratio enables zero output current ripple for the high transformer turns ratios that are needed to achieve high input to output voltage ratios. The embodiments therefore allow achieving low output current ripple for 48 V or higher input voltages, 1 V or lower output voltages, and high output currents.

Yao, Yuan↗

PWR loading pattern optimization with reinforcement learning

The core loading pattern optimization problem belongs to the class of combinatorial optimization problem and has been studied since the dawn of commercial nuclear energy industry. It is characterized by multiple objectives and constraints, with a very high number of candidate patterns, which makes it impossible to solve explicitly. Stochastic optimization methodologies including Genetic Algorithms and Simulated Annealing are used by different nuclear utilities and vendors to perform fuel cycle reload design. Nevertheless, hand-designed solutions continue to be the prevalent method in the industry. To improve the state-of-the-art core reload patterns, we aim to create a method as scalable as possible, that agrees with the designer's goal of performance and safety. To help in this task Deep Reinforcement Learning (DRL), in particular Proximal Policy Optimization is leveraged. DRL has recently experienced a strong impetus from its successes applied to games, sometimes even reaching 'super-human' performances. This paper lays out the foundation of this method and proposes to study the behavior of several hyper-parameters that influence the DRL algorithm. The algorithm is highly dependent on multiple factors such as an exploration/exploitation trade-off that manifests through different parameters such as the number of loading patterns seen and the number of samples collected before a policy update, but also the shape of the objective function derived for the core design. Experimental results also demonstrate the effectiveness of the method in finding high-quality solutions from scratch within a reasonable amount of time. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Optimized manufacturing process for multilayer two-dimensional focusing mirrors in laboratory X-ray applications

Recent advances in laboratory X-ray applications require high-performance optical components that achieve exceptional imaging resolution and beam uniformity within compact experimental setups. Montel mirrors have become a preferred solution due to their unique dual-reflection focusing mechanism and a space-efficient design. Here, in this study, we present an effective manufacturing process for producing Montel mirrors tailored to focus laboratory X-ray beams. The mirrors were fabricated from single-crystal silicon substrates, chosen for their high mechanical stability and compatibility with precision polishing techniques. Our approach begins with the integration of a deterministic chemo-mechanical polishing (CMP)-based pre-shaping step followed by ion beam figuring (IBF), significantly improving manufacturing efficiency. Subsequently, our custom-developed advanced metrology and IBF techniques were employed for fabricating an off-axis, elliptical cylinder Montel mirror system with a 6-mrad total slope, with stringent optical specifications. While post-IBF processes, including multilayer coating, dicing, and gluing, introduced minor surface errors, yet their impact on performance remained negligible. The Montel mirrors manufactured with the optimized process exhibited significantly improved beam uniformity and a reduced focal spot size. These findings validate our approach as a viable solution for high-precision Montel mirror fabrication and facilitate further advancements in laboratory X-ray applications.

36 MATERIALS SCIENCE↗

The Convolutional Multiple Whole Profile (CMWP) Fitting Method, a Global Optimization Procedure for Microstructure Determination

The analysis of line broadening in X-ray and neutron diffraction patterns using profile functions constructed on the basis of well-established physical principles and TEM observations of lattice defects has proven to be a powerful tool for characterizing microstructures in crystalline materials. These principles are applied in the convolutional multiple-whole-profile (CMWP) procedure to determine dislocation densities, crystallite size, stacking fault and twin boundary densities, and intergranular strains. The different lattice defect contributions to line broadening are separated by considering the hkl dependence of strain anisotropy, planar defect broadening and peak shifts, and the defect dependent profile shapes. The Levenberg–Marquardt (LM) peak fitting procedure can be used successfully to determine crystal defect types and densities as long as the diffraction patterns are relatively simple. However, in more complicated cases like hexagonal materials or multiple-phase patterns, using the LM procedure alone may cause uncertainties. Here, we extended the CMWP procedure by including a Monte Carlo statistical method where the LM and a Monte Carlo algorithm were combined in an alternating manner. The updated CMWP procedure eliminated uncertainties and provided global optimized parameters of the microstructure in good correlation with electron microscopy methods.

36 MATERIALS SCIENCE↗

Burn propagation in magnetized high-yield inertial fusion

Recent experiments at the National Ignition Facility (NIF) have demonstrated ignition for the first time in an inertial confinement fusion (ICF) experiment, a major milestone allowing the possibility of high energy gain through burn propagation. Use of external magnetic fields, applied primarily to reduce thermal losses, could increase hotspot temperature and ease requirements for ignition, opening up the capsule design space for high energy gain. However, this same restriction of thermal transport has the potential to inhibit burn propagation, which is vital in the attainment of high gain. In this work, radiation-magnetohydrodynamics (MHD) simulations carried out using the code Chimera are used to investigate the effect of a pre-imposed magnetic field on ignition and burn propagation. This paper studies the propagation of burn using both an idealized planar model and in fully integrated 2D MHD simulations of an igniting NIF capsule. A study of magnetized burn propagation in the idealized planar model identifies three regimes of magnetized burn propagation: (1) thermal conduction driven; (2) alpha transport driven; and (3) fully suppressed burn. Simulations of NIF shot N210808 with an applied 40 T axial field show clear indication of burn suppression perpendicular to field lines, with rapid burn observed along field lines. Implosion shape is altered by the field, and anisotropic conduction causes significant modification to the rate of ablation during stagnation. These results highlight the fundamental changes to implosion dynamics in high-yield magnetized ICF and motivate further study to better optimize future magnetized target designs for high gain.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Design, fabrication, and testing of diamond axicons for X-ray microscopy applications

This work presents the design, fabrication, and experimental validation of a refractive diamond axicon for X-ray beam shaping. The diamond axicon was developed to overcome the limitations of polymer-based axicons particularly for application in Transmission X-ray Microscopy (TXM) systems, offering superior mechanical strength, thermal stability, and radiation resistance, making it ideal for synchrotron applications. The axicon was fabricated using femtosecond laser ablation and tested at 11 keV under various coherence conditions. Results demonstrated that the axicon efficiently transformed the X-ray beam into a ring-shaped profile with over 80% transmission. Simulations confirmed the experimental findings and highlighted the potential for further improvements. This work paves the way for the use of diamond axicons in next-generation synchrotron facilities, with future efforts focusing on optimizing fabrication and testing the axicon in full TXM systems.

Samadi, Nazanin↗

Learning error distribution kernel‐enhanced neural network methodology for multi‐intersection signal control optimization

Traffic congestion has substantially induced significant mobility and energy inefficiency. Many research challenges are identified in traffic signal control and management associated with artificial intelligence (AI)-based models. For example, developing AI-driven dynamic traffic system models that accurately capture high-resolution traffic attributes and formulate robust control algorithms for traffic signal optimization is difficult. Additionally, uncertainties in traffic system modeling and control processes can further complicate traffic signal system controllability. To partially address these challenges, this study presents a novel, hybrid neural network model enhanced with a probability density function kernel shaping technique to formulate traffic system dynamics better and improve comprehensive traffic network modeling and control. The numerical experimental tests were conducted, and the results demonstrate that the proposed control approach outperforms the baseline control strategies and reduces overall average delays by 11.64% on average. By leveraging the capabilities of this innovative model, this study aims to address major challenges related to traffic congestion and energy inefficiency toward more effective and adaptable AI-based traffic control systems.

Wang, Hong [Oak Ridge National Laboratory (ORNL), ↗

Mixed Material Scintillator Systems for Neutron Detection

Scintillators are a fundamental technology that enables radiation detection. Their use has historically enabled the detection of incoming gamma radiation, with recent advances in plastic scintillator development enabling detection and discrimination of neutron and gamma radiation through pulse shape discrimination. However, scintillators have so far consisted of a single material, typically one primary dye and one secondary dye embedded in a plastic matrix. Based on the simulation studies described previously, mixed material scintillator systems with multiple secondary dyes arranged in alternating, periodic micro-sized regions opens the door for scintillators with a wide variety of different capability, such as directional sensing, positional reconstruction, particle identification, and pulse shape discrimination. However, fabrication of a mixed material scintillator system by conventional manufacturing methods is difficult to manufacture and scale, creating a barrier to their wide spread implementation. On the other hand, additive manufacturing additive manufacturing presents itself as the optimal method for fabricating mixed material scintillator systems based on its flexibility, ability to fabricate fine features, and potential for multimaterial fabrication.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Rheo–Electric Foundations and Engineering of Carbon Slurry Flow Electrodes

Flowable carbon slurry electrodes promise continuous, scalable electrochemical desalination and energy storage when their rheology (flow and stability) and electronic connectivity are jointly optimized. This report integrates six complementary thrusts that we executed under the Laboratory Directed Research and Development (LDRD) project: (i) a fast, ex situ, centrifuge-compatible method to quantify pellet (packed slurry) electronic conductivity, with a validated cell constant (“shape factor”) and quantitative structure–property insights for carbon mixtures; (ii) a controlled circulation study showing that peristaltic pumping can irreversibly alter particle size and morphology over laboratory-relevant durations; (iii) development of a miniature jet pump that preserves particle integrity while achieving entrainment ratios of 2–4 at practical flow rates; (iv) a comprehensive mapping of how a representative non-ionic surfactant (Tween 20) collapses the carbon gel network, separating network-percolation losses from intrinsic particle contact resistance; (v) in-situ visualization revealing how gravitational settling and flow-driven mixing compete to control charge transport, with dynamic bed layers preventing saturation while achieving 30-fold local concentration enhancement; and (vi) a simple, widely adoptable fabrication route to structured, gas-nitrided titanium nitride (TiN) titanium current collectors that dramatically lower interfacial losses and enable geometry-driven performance gains. Together, these results provide a coherent toolchain and design rules to accelerate formulation screening, de-risk device prototyping, and standardize characterization for carbon slurry electrodes in flow-electrode capacitive deionization (FCDI), electrochemical flow capacitor (EFC), and related systems.

25 ENERGY STORAGE↗

Cross-sectoral impact of emerging technologies on U.S. manufacturing resilience and competitiveness

Introducing new technologies in one energy-intensive industry can affect how other industries operate and stay resilient, yet these cross-sector interactions are often underappreciated in conventional technology roadmaps. In practice, industrial systems do not evolve in isolation. They are linked through shared upstream and downstream dependencies, such as electricity and fuel supply, critical materials, transportation networks, and enabling infrastructure. As a result, large-scale technology deployment in one sector can reshape resource availability, infrastructure demand, and operational risk in others. These interdependencies mean that technology deployment decisions in one sector can create unintended bottlenecks or cascading benefits in others. Here, this article argues that a cross-sector, system-of-systems perspective is essential for evaluating and scaling emerging technologies in energy-intensive industries. By framing industrial transformation as an interconnected systems challenge rather than a set of isolated sectoral decisions, the study highlights how interdependence shapes technology feasibility, adoption pathways, and resilience outcomes. The article illustrates how cross-sector linkages can amplify both risks and benefits, and it emphasizes the importance of integrated planning approaches that account for shared dependencies, cascading impacts, and co-optimization opportunities. Adopting this broader perspective can support more robust technology roadmaps, improve strategic coordination across industries, and strengthen the long-term resilience of the industrial sector as a whole.

Nain, Preeti [Oak Ridge National Laboratory (ORNL)↗

The role of SAXS and molecular simulations in 3D structure elucidation of a DNA aptamer against lung cancer

Aptamers are short, single-stranded DNA or RNA oligonucleotide molecules that function as synthetic analogs of antibodies and bind to a target molecule with high specificity. Aptamer affinity entirely depends on its tertiary structure and charge distribution. Therefore, length and structure optimization are essential for increasing aptamer specificity and affinity. Here, we present a general optimization procedure for finding the most populated atomistic structures of DNA aptamers. Based on the existed aptamer LC-18 for lung adenocarcinoma, a new truncated LC-18 (LC-18t) aptamer LC-18t was developed. A three-dimensional (3D) shape of LC-18t was reported based on small-angle X-ray scattering (SAXS) experiments and molecular modeling by fragment molecular orbital or molecular dynamic methods. Molecular simulations revealed an ensemble of possible aptamer conformations in solution that were in close agreement with measured SAXS data. The aptamer LC-18t had stronger binding to cancerous cells in lung tumor tissues and shared the binding site with the original larger aptamer. The suggested approach reveals 3D shapes of aptamers and helps in designing better affinity probes.

59 BASIC BIOLOGICAL SCIENCES↗