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At least 37 records · Page 2

Dielectric-Engineered Monolayer MoS 2 Memtransistors for Brain-Inspired Computing with High Recognition Accuracy

Two-dimensional transition metal dichalcogenides (2D-TMDs)-based memtransistors have emerged as promising candidates for neuromorphic hardware due to their exceptional ability to emulate synaptic behavior. However, many existing 2D-TMDs memtransistors rely on polycrystalline channels with grain boundaries or defects introduced through postgrowth treatments, raising concerns about material integrity and the preservation of intrinsic properties. Here, in this work, we demonstrate a monocrystalline monolayer MoS 2 memtransistor fabricated on a silicon nitride (SiN X ) substrate, achieving a large resistive switching ratio of 10 4 , a dynamic range exceeding 90, along with highly linear and symmetric weight updates, minimal cycle-to-cycle variability, and low device-to-device variability. These attributes are critical for enabling high-performance neuromorphic hardware. Based on experimental data, we further show that these artificial synapses enable a recognition accuracy of more than 97% on the MNIST handwritten digits data set. Our findings present a straightforward approach to realizing 2D-TMDs memtransistors through dielectric engineering, offering a promising platform for next-generation neuromorphic computing systems.

2D TMDs

Deuterium trapping mechanisms in reduced activation ferritic martensitic steels and their correlation with mechanical strengthening

Development of high-strength materials often involves introduction of additional strengthening microstructures that also serve as tritium trapping sites. Such additions in fusion material development could degrade the fuel efficiency in fusion reactors and raise radiological concerns. The contribution of individual microstructure features in hydrogen trapping must be evaluated to ensure fuel efficiency and radiological safety. This study explores the mechanistic origins of deuterium trapping in reduced-activation ferritic–martensitic steels and its correlation to mechanical strengthening. A series of model alloys and engineering steels were fabricated and subjected to different heat treatments to control deuterium trapping site density. Deuterium retention was evaluated using D 2 gas charging and thermal desorption spectroscopy, focusing on the role of grain boundary, dislocation, M 23 C 6 precipitates, and TiC precipitates. Multiscale microstructure characterization and synchrotron X-ray diffraction were performed to characterize microstructure, which was correlated to the deuterium retention property. Results show that TiC precipitates exhibit the highest deuterium trapping capacity, followed by M 23 C 6 precipitates. Dislocation and grain boundary demonstrate the lowest and similar efficiencies. Furthermore, the relationship of trapping quantity and mechanical strengthening of these microstructure features was quantified, demonstrating that TiC precipitates offer highest deuterium trapping per unit of mechanical strengthening.

Retention

A mechanistic, multiscale model for predicting Pd penetration in TRISO fuels using BISON

TRistructural ISOtropic (TRISO) particles use silicon carbide (SiC) as the primary structural member and barrier against metallic fission product (FP) release. palladiums (PDs), produced by fission in the fuel kernel, can diffuse to and chemically interact with the SiC layer, degrading its structural integrity and ability to contain radioactive FPs. Existing temperature-dependent correlations for predicting Pd penetration rely on experimental data with significant scatter due to varying conditions, potentially complicating ongoing fuel qualification and licensing efforts for advanced reactors that would subject TRISO fuels to operating conditions outside of those examined in the experiments. A mechanistic model of Pd production, transport, and reaction is developed in this work to better understand and predict PD attack of SiC in TRISO particles. molecular dynamicss (MDs) simulations are utilized to calculate the Pd diffusivity in SiC grain bulk and grain boundaries. A mesoscale phase-field diffusion model, informed by the MD diffusivities, is used to develop a reduced order model (ROM) for the effect of SiC microstructure on the Pd penetration rate. The engineering scale BISON model calculates Pd production and transport, utilizing the ROM to predict penetration rates consistent with experimental data. This novel mechanistic ROM captures the effect of temperature, microstructure, and irradiation history on Pd penetration. In conclusion, these new capabilities are expected to support ongoing qualification and licensing efforts associated with near-term TRISO-fueled reactor applications.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS

Interdisciplinary research and development on the effects of the nature and properties of ceramic materials in the design of advanced structural components

An educational development and supportive research program on ceramic materials established to advance design methodology, improve materials, and develop engineers knowledgable in design with and use of high performance ceramic materials is described. Emphasis is on the structures and related materials problems in a ceramic turbine engine, but applications in coal gasification, solar conversion, and magnetohydrodynamic technologies are considered. Progress of various research projects in the areas of new materials, processing, characterization, and nondestructive testing is reported. Fracture toughness determination, extended X-ray absorption fine structure measurements, and grain boundary effects in beta-alumina are among the topics covered.

Source record

Accelerating effects of galvanic corrosion and dissimilar materials on the corrosion of 316H in NaCl-MgCl2 salt

Corrosion of materials presents a significant challenge for the long-term operation of molten salt reactors. This study aims to identify the most effective techniques for evaluating the corrosion performance of materials in molten salts, with a focus on the effects of galvanic corrosion and dissimilar materials. A reliable testing methodology for assessing material corrosion in molten chloride salts has been successfully developed. The corrosion of Alloy 316H in molten NaCl-MgCl2 salt was found to be significantly accelerated by galvanic corrosion. Additionally, the presence of dissimilar materials resulted in a slight increase in the corrosion rate of Alloy 316H in NaCl-MgCl2 salt. Microstructural characterization was utilized to understand the corrosion behavior of test samples under different conditions. Common trends observed across samples include chromium depletion and iron enrichment near corroded surfaces. Molybdenum enrichment along grain boundaries and corrosion surfaces was also frequently noted.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS

Chromium-doped uranium dioxide fuels: A review

UO 2 doped with parts per million CR 2 O 3 powder is considered a potential near term accident tolerant fuel candidate. Here, the results of decades of industry and academic research into Cr-doped UO 2 are analyzed and their shortcomings are critiqued. Focusing on the incorporation mechanisms of Cr into the fuel matrix, we explore a mechanistic understanding of the characteristic properties of Cr-doped UO 2 , notably, enhanced fission gas retention attributed to enlarged grain sizes following sintering, along with marginal improvements in the thermophysical properties. The findings of recent X-ray Adsorption Near Edge Spectroscopy studies were compared and put into conversation with historic data regarding the incorporation of Cr in UO 2 . On the basis of defect mechanisms, the case is made for the substitutional incorporation of Cr governing the lattice solubility but not the enhanced U diffusivity. Instead, Cr/CR 2 O 3 redox chemistry in a well-defined oxygen potential explains the differences in the U diffusivity and O/M ratio. The primary mechanism of doping enhanced grain growth is found to be liquid assisted sintering due to a CRO (1) eutectic phase at the grain boundaries. The role of inhomogeneities in Cr concentration in UO 2 at various length scales across the materials microstructure is highlighted and connected to promising experimental and modeling work to fill in the gaps in the current understanding of Cr-doped UO 2 . The review considers both the open scientific questions and engineering applications to illustrate the deep connections between the practice and theory in the design of accident tolerant nuclear fuels. In conclusion, the review ends with an outline of future works that combine meticulous irradiation studies and high resolution experiments with next generation modeling and simulations techniques empowered by machine learning advances to accelerate the fabrication and adoption of Cr-doped UO 2 light water reactors.

Cleveland, Mack Wesley [Massachusetts Inst. of Tec

Machine Learning Aided Modeling of Granular Materials: A Review

Artificial intelligence (AI) has become a buzzy word since Google’s AlphaGo beat a world champion in 2017. In the past five years, machine learning as a subset of the broader category of AI has obtained considerable attention in the research community of granular materials. This work offers a detailed review of the recent advances in machine learning-aided studies of granular materials from the particle-particle interaction at the grain level to the macroscopic simulations of granular flow. This work will start with the application of machine learning in the microscopic particle-particle interaction and associated contact models. Then, different neural networks for learning the constitutive behaviour of granular materials will be reviewed and compared. Finally, the macroscopic simulations of practical engineering or boundary value problems based on the combination of neural networks and numerical methods are discussed. We hope readers will have a clear idea of the development of machine learning-aided modelling of granular materials via this comprehensive review work.

42 ENGINEERING

Development of Predictive Model for Accurate Rupture Time from Multi-Axial Creep in Alloy 709 with Physics-Based Simulations

A physics-based model is developed to predict multiaxial creep behavior in Alloy 709 (A709), an advanced austenitic stainless steel intended for high-temperature applications such as Sodium Fast Reactors (SFRs). Compared to conventional stainless steels like 316H, A709 offers superior high-temperature performance; however, comprehensive data on its multiaxial creep response remain limited. To address this gap, a crystal plasticity finite element (CPFE) framework is used to simulate the deformation and failure mechanisms of A709 under multiaxial loading conditions. The model incorporates an extended Hu-Cocks dislocation creep formulation that accounts for precipitation effects, along with the Sham–Needleman model to capture grain boundary cavitation-driven failure. These advanced constitutive models enable a detailed understanding of the interplay between microstructural evolution and macroscopic creep response. Furthermore, the study evaluates the predictive accuracy of various effective stress measures in estimating creep rupture life, leveraging simulated multiaxial creep data. The findings provide critical insights into the applicability of different stress measures for engineering design and life prediction of A709 components operating under complex loading conditions. This work contributes to improving the reliability of high-temperature structural components by advancing predictive modeling capabilities for advanced austenitic steels.

Alloy 709

Micromechanical Surrogate Machine Learning Model for Creep Deformation Modeling

Process variability during the manufacture of gas turbine engine hot section components can significantly affect the material’s resulting microstructure. In casting, for instance, geometric variation within a component (thin sections versus thick sections, radial location) influences cooling rates and the resulting grain size. The high temperature creep response is known to be sensitive to grain size owing to a diffusional creep mechanism which occurs more readily along grain boundaries. Microstructural variation correspondingly drives mechanical behavior which propagates into component scale performance uncertainty. These factors are essential when planning inspection, maintenance, and repair strategies within a reliability framework. These benefits provide opportunities to increase overall energy efficiency through refined margins. Critically, there is an opportunity to bolster existing data-driven reliability models using physics-driven process-structure-property relations. Here we present recent work establishing a framework for evaluating the probabilistic creep performance of high-temperature materials. A novel microstructure-sensitive crystal plasticity finite element model is established that captures both grain boundary and crystallographic deformation effects. The computationally expensive physics model is calibrated using a statistical approach and this high-fidelity model is subsequently used to train a computationally efficient machine learning surrogate model. The surrogate model is essential for sampling a large ensemble of simulated structure-property pair results. The ensemble data are then mined to extract salient trends to be incorporated into a microstructure-sensitive reliability model. The proposed approach represents a novel way to capture microstructure-sensitive trends from physics-based models within a modern reliability framework.

Fernandez-Zelaia, Patxi [ORNL]

Diffusion bonding and its application to manufacturing

In its simplest form diffusion bonding is accomplished by placing clean metal surfaces together under a sufficient load and heating. The natural interatomic attractive force between atoms transforms the interface into a natural grain boundary. Therefore, in principle, the properties of the bond area are identical to those of the parent metal. Other advantages of diffusion bonding over conventional methods of bonding include freedom from residual stresses, excessive deformation, foreign metals, or changed crystal structures. Stainless steels, nickel-base superalloys, and aluminum alloys have all been successfully joined. Complex hardware, including integrated flueric devices, jet engine servovalves, and porous woven structures have been fabricated. The processing involved is discussed, along with such theoretical considerations as the role of metal surfaces, the formation of metal contact junctions, and the mechanisms of material transport in diffusion bonding.

Spurgeon, W. M.

Computational materials reliability assessment of hydrogen fueled gas turbine power generation engines

The use of blended fuel sources in land based gas turbine engines drives variations in the resulting operational profile (temperatures and pressures) which can impact engine reliability. Furthermore, variability in the manufacture of components affects the resulting microstructure which directly impacts material performance and reliability. Currently, data-driven models are typically used for maintaining and inspecting fleets of engines. Without explicitly capturing material and operational sources of variability conservatism must be used in developing component-level reliability models. Therefore, there exists an opportunity to use information from materials-scale physics models to better inform reliability modeling and reduce conservatism; the impact is more cost-efficient operation and maintenance of current and future fleets. Specifically, this work establishes a computational framework for evaluating the probabilistic high temperature creep performance of hot-section Ni-based superalloys where uncertainty comes from both microstructural and operational variability. A novel high-fidelity physics model which phenomenologically captures grain-boundary sensitive phenomena has been established. A probabilistic calibration procedure was used to calibrate the model and capture uncertainty in the parameterized model coefficients. A design of experiments methodology was established for identifying informative microstructural digital representations for suitable for forward model evaluation. Results show that training a machine-learning surrogate using this design criteria outperforms random selection of microstructural representations. Finally, two surrogate models were developed: (1) a deterministic surrogate model which predicts the local field response given microstructure, constitutive model parameters, and operating conditions (stress, temperature) and (2) a probabilistic model, where uncertainty comes from constitutive law uncertainty, built using denoising diffusion probabilistic models which samples responses given (1) microstructure and (2) operating conditions. These surrogate models enable partner Siemens Energy to rapidly perform UQ analysis specific to creep deformation across a range of microstructures and operating conditions. The impact is that these ML and physics codes can be used to establish more advanced reliability models for the inspection, servicing, and maintenance of land based gas turbine engines.

36 MATERIALS SCIENCE

Hierarchical microstructure of Yb-filled skutterudites through ultrasonically atomized spherical powders for enhanced thermoelectric performance

Hierarchical microstructures are widely explored as a strategy to reduce lattice thermal conductivity in thermoelectric materials while preserving favorable electronic transport. Here we demonstrate that ultrasonic atomization of precursor powders provides an intrinsic pathway to generate such architectures in n-type Yb0.3Co4Sb12 skutterudites. Materials were synthesized by both conventional sealed-ampoule and ultrasonic atomization routes, each yielding essentially single-phase skutterudite after densification. However, the atomized spherical powders undergo a distinct reaction-driven microstructural evolution during thermal treatment prior to densification. Electron microscopy reveals that the skutterudite phase within the particles induces swelling, cracking, and fragmentation of the droplets before consolidation. Multimodal structural and microstructural characterizations show that densification of these fragmented powders produces a hierarchical microstructure consisting of submicron grains, micrometer-scale faceted crystallites, and powder-derived domains separated by oxide-decorated boundaries. Comprehensive thermoelectric transport measurements evidence that this multiscale architecture lowers the lattice thermal conductivity while maintaining favorable electronic transport, leading to an average ~10% enhancement in the thermoelectric figure of merit. Complementary 121Sb Mössbauer spectroscopy further indicates lattice softening in the atomized material. These results demonstrate that ultrasonic atomization provides an effective route to engineer hierarchical microstructures in skutterudite thermoelectrics and offers a promising strategy for tailoring thermal transport in energy-conversion materials.

Bouteiller, Hugo [ORNL] (ORCID:0009000421322962)

Dynamic Atomistic Polar Structure Underpins Ultrahigh Linear Electro-Optic Coefficient in Transparent Ferroelectric Ceramics

Transparent ferroelectrics with high linear electro-optic (EO) coefficients are critical for advanced electro-optical devices. However, achieving optical transparency in ferroelectric ceramics remains challenging due to visible light scattering caused by defects such as domain walls, grain boundaries, and pores. Here, we report the successful fabrication of transparent ferroelectric ceramics through innovative chemical composition design and an advanced two-step sintering process in the La-doped Pb(Mg 1/3 Nb 2/3 )O 3 –PbTiO 3 system. The optical transparency, which is near the theoretical upper limit, can be attributed to the wide band gap and the minimization of light scattering of defects. By minimizing porosity and engineering grain/domain sizes to differ significantly from the wavelengths of visible light, we suppress scattering, achieving optical transparency near the theoretical upper limit. Strikingly, these ceramics exhibit an ultrahigh linear EO coefficient of ∼1417 pm/V, over 65 times greater than that of LiNbO 3 single crystals, the current industry standard. We attribute this exceptional performance to dynamic atomistic polar structures within switchable, thermally stable domains, which enhance electronic polarization sensitivity. This mechanism is corroborated by dielectric spectroscopy, high-resolution transmission electron microscopy and simulation. Our findings offer insights into the design of cost-effective transparent materials with exceptional EO properties, paving the way for next-generation electro-optical devices.

36 MATERIALS SCIENCE

Σ3(111) Grain Boundaries Accelerate Hydrogen Insertion into Palladium Nanostructures

Grain boundaries (GBs) are frequently implicated as key defect structures facilitating metal hydride formation, yet their specific role remains poorly understood due to their structural complexity. Here, we investigate hydrogen insertion in Pd nanostructures enriched with well-defined Σ3(111) GBs (Pd GB ) synthesized via electrolysis-driven nanoparticle assembly. In situ synchrotron X-ray diffraction reveals that Pd GB exhibits dramatically accelerated hydriding and dehydriding kinetics compared with ligand-free and ligand-capped Pd nanoparticles with similar crystallite sizes. Strain mapping using environmental transmission electron microscopy shows that strain is highly localized at GBs and intensifies upon hydrogen exposure, indicating preferential hydrogen insertion along GB sites. Density functional theory calculations provide mechanistic insight supporting these findings, showing that hydrogen insertion near Σ3(111) GBs is energetically more favorable and that tensile strain lowers insertion barriers. Furthermore, these results provide atomic-level insights into the role of GBs in hydride formation and suggest new design strategies for GB-engineered Pd-based functional materials.

Anions

PtCoO 2 for Scaled Interconnects

Copper (Cu) interconnects are an increasingly important bottleneck in integrated circuits due to energy consumption and latency caused by the notable increase in Cu resistivity as dimensions decrease, primarily due to electron scattering at surfaces. Herein, the potential of a directional conductor, PtCoO 2 , which has a low bulk resistivity and a distinctive anisotropic structure that mitigates electron surface scattering is showcased. Thin films of PtCoO 2 of various thicknesses are synthesized by molecular beam epitaxy (MBE) coupled with a postdeposition annealing process and the superior quality of PtCoO 2 films is demonstrated by multiple characterization techniques. The thickness‐dependent resistivity curve illustrates that PtCoO 2 significantly outperforms effective Cu (Cu with TaN barriers) and Ru in resistivity below 20.0 nm with a more than 6x reduction compared to effective Cu below 6.0 nm, having a value of only 6.32 μΩ cm at 3.3 nm. It is determined that grain boundary scattering can still be improved for even lower resistivities in this material system through a combination of experiments and theoretical simulations. PtCoO 2 is therefore a highly promising alternative material for future interconnect technologies promising lower resistivities, better stability, and significant improvements in energy efficiency and latency for advanced integrated circuits.

Li, Yansong [Department of Electrical Engineering

Crack‐Free Single‐Crystalline LiNiO 2 for High Energy Density All‐Solid‐State Batteries

Abstract Single‐crystalline layered oxide (LiNi 1‐ x ‐ y Mn x Co y O 2 ) cathodes have been found to exhibit exceptional electrochemical properties when coupled with various inorganic solid electrolytes (ISEs) in all‐solid‐state batteries (ASSBs). Their advantages stem from the robust morphological integrity with the absence of grain boundaries and the high electrochemical oxidative stability. Here, ASSBs featuring single‐crystalline LiNiO 2 (LNO) with the highest Ni content are reported, offering a high theoretical specific capacity of 275 mAh g ‐1 alongside a high average discharge voltage (3.7 V vs Li + /Li). Through a careful investigation, it is demonstrated that micron‐sized single‐crystalline LNO (µSC‐LNO) composite cathodes with a halide ISE exhibit a high initial discharge capacity of 205 mAh g ‐1 with an outstanding cycle performance over 200 cycles in room‐temperature ASSBs. The significance of engineering parameters is emphasized, such as particle size and specific density, in promoting a homogeneous and fast Li + transport within the composite cathodes. Furthermore, the formation of undesirable interphase between the halide ISE in the cathode and sulfide ISE separator is elucidated, which may be a critical factor impeding long‐term cyclability of ASSBs. This work provides insights into the design of composite cathodes for high‐energy‐density ASSBs.

Chemistry

Ambipolar Transport in Polycrystalline GeSn Transistors for Complementary Metal-Oxide-Semiconductor Applications

Group-IV alloy GeSn is a promising material for electronic and optoelectronic applications due to its compatibility with both Si substrates and established Si fabrication processes. This study focuses on polycrystalline GeSn (10% Sn), which offers a cost-effective, large-area, and versatile alternative to epitaxial GeSn. We demonstrate ambipolar transport behavior in polycrystalline GeSn thin film transistors, achieving electron and hole field-effect mobilities reaching up to 0.05 cm 2 /Vs and 2.05 cm 2 /Vs, respectively. Through temperature-dependent analysis, we elucidate the underlying mechanism of this phenomenon, which we attribute to quantum tunneling between the Schottky barrier contact and the channel, as well as potential barriers between the grain boundaries of this polycrystalline film, thereby advancing the understanding of polycrystalline GeSn's electrical properties. Furthermore, this work highlights the potential of ambipolar transport as a technique to employ towards the development of GeSn complementary metal-oxide-semiconductor field-effect transistors, promising to simplify and reduce the cost of GeSn manufacturing processes for edge computing and sensing applications.

42 ENGINEERING

Fundamental Study of Fatigue Crack Initiation at Grain and Twin Boundaries in Austentic Stainless Steel (Final Technical Report)

The overarching goal of this project was to understand the dislocation-based mechanisms driving fatigue crack initiation at grain and twin boundaries. The hypothesis of the work is that dislocation structures equivalent to persistent slip bands (PSBs) form in the boundaries, leading to local stress concentrations and fatigue crack initiation. The sub-goals associated with this work include: • Understanding the evolution of the dynamic stress state and dislocation density surrounding PSB/grain boundary interactions. This will require the development of new techniques that couple high resolution electron backscatter diffraction (HREBSD) with in situ scanning electron microscopy (SEM) deformation. • Uncover the mechanisms by which dislocations are accommodated in grain and twin boundaries during fatigue. The proposed approach here is to conduct in situ transmission electron microscopy (TEM) deformation experiments on fatigued samples. • Establish correlations between microstructure, deformation accommodation, and crack initiation across time and length scales. This work primarily focuses on understanding fatigue crack initiation in austenitic stainless steels, though promising work by an undergraduate researcher extended the work to high purity Al.

42 ENGINEERING