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At least 73 records · Page 4

Application of electron backscatter diffraction techniques to quantify effects of aging on sub-grain and spatial heterogeneity in NMC cathodes

Identification and evaluation of structural heterogeneity in spent cathode materials is crucial to developing appropriate remediation strategies for novel recycling processes. Native heterogeneities may be exacerbated during the cell's operational lifetime, as sub-particle-scale variations induce anisotropic expansion and contraction upon cycling. Structural transformations resulting from repeated cycling and calendar aging predominantly occur at the secondary particle surface and at the grain boundaries (GBs) between primary particles. However, the diffusion and stress build up around and across GBs are poorly understood. In this study, electron backscatter diffraction (EBSD) is employed to track sub-grain lattice structure across a statistically relevant number of Li(Ni0.33Mn0.33Co0.33)O2 (NMC-111) particles. Specifically, differences in lattice misorientation – measured as the deviation from the grain's average orientation – are tracked as a function of position within the electrode (near current collector, middle, and near separator) and as a function of electrochemical cycling. Further, a novel method of structural analysis is developed, offering insight into sub-grain diffusion behavior by comparing lattice misorientation near the grain boundary versus in the grain bulk. The present results suggest that electrode-scale spatial heterogeneity in lattice structure is induced by initial manufacturing conditions, and that radial gradients in lattice misorientation evolve at the primary particle scale with repeated electrochemical cycling.

25 ENERGY STORAGE↗

Optimizing fluvial flood mitigation strategies: A multi-objective approach for cost-effective and socially-aware infrastructure feasibility analysis

Effective levee planning must balance capital cost, risk reduction, and community priorities. These objectives are rarely optimized together. This study presents a feasibility phase, simulationin-the-loop framework that couples terrain-based flood modeling with a socially aware multiobjective optimizer. Flood risk is measured as Expected Annual Exposed Population (EAEP), obtained by integrating exposure over Annual Exceedance Probability (AEP) nodes, mirroring the Hydrologic Engineering Center's Flood Damage Reduction Analysis (HEC-FDA) expected-annual formulation but with people rather than dollars. Exposure per scenario is computed by overlaying binary inundation masks with a population surface at the tract level. Distributional fairness is encoded through a Group Benefit Share (GBS) constraint that requires high-SVI tracts to receive at least a baseline share of annualized benefits. Capital cost is represented by a height-dependent unit-cost model suitable for screening. This study addresses the two-objective problem, minimize cost and expected annual exposure subject to the GBS constraint, using Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and leveraging Pareto front for feasibility phase decision making. Implemented with terrain-based flood modeling, GeoFlood, for rapid scenario evaluation, the framework is demonstrated in Southeast Texas. The results reveal clear trade-offs among cost, risk, and social benefits and identify non-dominated levee height configurations that satisfy the benefit-share floor. The contributions are a scalable decision support method that operationalizes expected annual population-based risk, embeds enforceable benefit-sharing guarantees, and uses lightweight simulation to explore large design spaces before higher fidelity design stages.

Flood mitigation↗

Mechanistic calculation of the effective silver diffusion coefficient in polycrystalline silicon carbide: Application to silver release in AGR-1 TRISO particles

The silicon carbide (SiC) layer in tristructural isotropic (TRISO) fuel particles serves as a barrier to prevent the escape of fission products produced and not retained in the fuel kernel. The release of silver (Ag) is a concern due to the long half-life of the 110m Ag isotope. However, accurately determining the fission gas release rate requires knowing the diffusion coefficient through the SiC layer. In this study, we leverage atomistic calculations of Ag diffusivity in SiC bulk and grain boundaries (GBs) to develop a mesoscale effective Ag diffusion coefficient (D eff ) in SiC. Since GBs serve as pathways for Ag diffusion, D eff is defined as a function of temperature and microstructure variables. In particular, the size of SiC grains in the direction perpendicular to diffusion is shown to significantly affect Ag diffusion. The prediction of the mechanistic, mesoscale approach falls within one order of magnitude of empirical values. The temperature and microstructure-dependent effective Ag diffusivity in SiC is implemented in the fuel performance code Bison with a correction factor to predict Ag release from AGR-1 TRISO fuel particles. We hereby quantify the impact of SiC grain size on Ag release and improve Bison’s predictions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Methods development towards automated, physics-informed, quantitative quality control of TRISO-SiC

Tristructural-isotropic (TRISO) fuel particles have been developed as a high-performance fuel for use in high-temperature gas-cooled reactor (HTGR) systems due to their high efficiency and stability under both normal and off-normal conditions. Broader deployment of this technology in advanced nuclear applications may benefit from quantitative quality assurance and quality control (QA/QC) methods that directly link TRISO properties to downstream performance. A key TRISO property is the SiC layer microstructure, which influences fission product retention during irradiation. However, existing QA/QC for the TRISO-SiC microstructure comprises only a qualitative visual inspection; therefore, there is a clear opportunity for the development of quantitative methods for TRISO QA/QC. Here, to this end, previous work has demonstrated an image processing approach to grain boundary (GB) identification and subsequent extraction of microstructural metrics; however, extensive twinning within the SiC layer complicates such analyses because twin GBs significantly influence microstructural metrics but are not expected to contribute to fission product transport. This study presents the initial development, training, and testing of an ML-based image segmentation algorithm designed to identify and remove twin GBs from standard backscattered electron micrographs, providing an industrially applicable, quantitative, and physically meaningful QA/QC approach for the TRISO-SiC microstructure. Although pixel-wise performance metrics for the twin predictions are low, the change in grain area and the number of GB pixels after twin removal predicted by the ML workflow are within 1% of the true values calculated using crystallographic data. This suggests that the model is well capable of predicting overall twin boundary structures and grain morphology, and continued advancement of this approach could enable automated, scalable, and physics-informed QA/QC for TRISO-SiC microstructures, supporting the reliable qualification of coated particle fuels for next-generation reactor systems.

Computer vision↗

Grain boundary metastability controls irradiation resistance in nanocrystalline metals

Grain boundaries (GBs) in polycrystalline materials are powerful sinks for irradiation defects. While standard theories assume that a GB’s efficiency as a sink is defined solely by its character before irradiation, recent evidence conclusively shows that the irradiation sink efficiency is a highly dynamic property controlled by the intrinsic metastability of GBs under far-from-equilibrium irradiation conditions. In this paper, we reveal that the denuded (i.e., defect-free) zone, typically the signature of a strong sink, can collapse as irradiation damage accumulates. We propose a radiation damage evolution model that captures this behavior based on the emergence of a series of irradiation defect-enabled metastable GB microstate changes that dynamically alter the ability of the GB to absorb further damage. We show that these microstate changes control further defect absorption and give rise to the formation of a defect network that manifests itself as a net Nye-tensor signal detectable via lattice curvature experiments.

36 MATERIALS SCIENCE↗

Atom probe tomography of segregation at grain boundaries and gas bubbles in neutron irradiated U-10 wt% Mo fuel

During neutron irradiation to fission densities > 5.2 × 10 21 fiss/cm 3 , Xe agglomerates forming gas bubbles of varying size within the U-Mo fuel matrix. Herein, segregation of fission products to Xe bubbles and grain boundaries (GB) were studied using atom probe tomography (APT). Segregation behavior was found to vary among GBs, small bubbles (<10 nm), and larger bubbles (>10 nm). Solid fission products were enriched at GBs and larger bubbles, but not at small bubbles. Finally, a denuded zone was identified adjacent to a > 10 nm Xe gas bubble and a GB.

36 MATERIALS SCIENCE↗

Measurement of grain boundary strength of Inconel X-750 superalloy using in-situ micro-tensile testing techniques in FIB/SEM system

Grain boundaries (GBs), known as two-dimensional defects, are omnipresent in polycrystalline metallic alloys and thus influence a wide range of mechanical properties under different environmental conditions like irradiation and corrosion. Therefore, quantifying the strength of individual GBs is critical for understanding the degradation of mechanical properties of materials under different conditions. In this study we developed an efficient approach for the fabrication of micro-tensile specimens with a GB almost perpendicular to the tensile direction, which is expected to advance the development of individual GB tensile testing at micro or nanoscale in a wide scope of materials. Further, an in-situ cantilever micro-tensile testing method was developed and used to quantify the strength of a Σ3 GB in Inconel X-750 with the combination of finite element modeling. The average ultimate tensile strength (UTS) of a non-irradiated Σ3 GB is estimated at around 1.4 GPa, comparable to that of a neutron-irradiated Σ3 GB with a dose of ~1.5 dpa (1.3 GPa). Moreover, the in-situ push-to-pull micro-tensile testing technique developed in this work provides valuable insights into the high-angle GB deformation and fracture behavior. This method generates qualitatively similar ductility behavior before and after neutron irradiation as the bulk material testing. However, the ductility and UTS values obtained from this method are different from bulk measurements due to vastly different specimen dimensions.

36 MATERIALS SCIENCE↗

Atomistic and phase field simulations of three dimensional interactions of {$10\bar12$} twins with grain boundaries in Mg: twin transmission and dislocation emission

In polycrystals, the interaction of dislocations and twins with grain boundaries (GBs) plays a role in hardening and formability during plastic deformation. While dislocation-GB interactions are relatively well-understood, twin-GB interactions remain mostly unknown. In this work, an approach using molecular dynamics and phase-field simulations is followed to study the forward and lateral interactions between {$10\bar12$} twins and tilt grain boundaries in Mg. Molecular dynamics results show that the resolved shear stress on slip/twinning modes of the neighboring grain, not the geometric alignment, is the dominant factor in determining the outcome of the twin-GB interactions. For some lateral interaction configurations, as the misorientation angle increases, the resolved shear stress on the same {$10\bar12$} twin variant of the neighboring grain reduces while it increases for slip or I 2 stacking fault emissions or other twin modes such as {$11\bar12$} and {$10\bar11$}, explaining why twin transmission is not seen at high misorientation angles. Furthermore, lateral and forward interactions of the twin with tilt grain boundaries whose misorientation axes are normal to the coherent twin boundary show significantly different outcomes. For the forward interaction, the twin is absorbed and stacking faults are emitted when interacting for low misorientation angles (up to 30°) while the lateral interaction results in twin transmission, nucleation of a {$11\bar12$} twin, and emission of I 2 stacking faults. Finally, comparisons between twin interactions with symmetric and asymmetric tilt GBs with different GB structures show similar outcomes.

36 MATERIALS SCIENCE↗

Prediction of dislocation - grain boundary interactions in FCC aluminum bicrystals using a modified continuum criterion and machine learning methods

Mechanical properties of metals such as strength and toughness are strongly correlated to complex interactions between various defects in the crystalline structure. While elementary interactions between these defects have been investigated using recent micro- and nano-characterization techniques, understanding of the detailed interaction mechanisms has hardly been obtained. To understand defect-driven plasticity at various time and length scales, it is necessary to formulate a general guideline to predict both the interaction type (transmission or reflection) and the dislocation's subsequent slip system after the interaction. Many criteria based on the geometric alignment of the defects have been developed to predict this phenomenon, but these have yet to be found to be accurate when applied to general data sets of grain boundaries (GBs). With this motivation, we conduct a systematic study using molecular dynamics (MD) models of bicrystals to analyze defect interaction process between a prismatic dislocation loop and eleven different grain boundaries of the following character: three tilt, three twist, and five mixed. Based on the MD observations, two new prediction methods are developed: the first is a new data-driven parametric score function based on the classical geometric criteria, and the second is by applying Gaussian process machine learning methods to find the probability distribution of a hidden function. In conclusion, the proposed data-driven prediction methods could pave a new way to predict the unit interaction of dislocations with various GBs, which could show much higher accuracy compared to pre-existing geometric criteria.

36 MATERIALS SCIENCE↗

A Universal Machine Learning Model for Elemental Grain Boundary Energies

The grain boundary (GB) energy has a profound influence on the grain growth and properties of polycrystalline metals. Here, we show that the energy of a GB, normalized by the bulk cohesive energy, can be described purely by four geometric features. By machine learning on a large computed database of 361 small Σ (Σ<10) GBs of more than 50 metals, we develop a model that can predict the grain boundary energies to within a mean absolute error of 0.13 J m –2 . More importantly, this universal GB energy model can be extrapolated to the energies of high Σ GBs without loss in accuracy. These results highlight the importance of capturing fundamental scaling physics and domain knowledge in the design of interpretable, extrapolatable machine learning models for materials science.

36 MATERIALS SCIENCE↗

Reduction of vanadium diffusivity within copper grain boundaries due to enhanced binding

We investigate permeation of vanadium (V) through copper (Cu) layers in V/Cu/niobium (Nb) and molybdenum (Mo)/Cu/V tri-layer composites and compare it with the permeation behavior of Nb. Despite their low solubility in single-crystal Cu, both V and Nb permeate readily due to short-circuit transport through Cu grain boundaries (GBs). However, Nb permeates preferentially to V. Atomistic simulations suggest that this difference is due to lower V diffusivity at general GBs in Cu, compared to Nb. Here, the lower V diffusivity, in turn, arises from stronger V binding to the boundary, which manifests as a greater equilibrium GB concentration as well as a higher activation energy for GB diffusion.

36 MATERIALS SCIENCE↗

Significant improvement of conversion efficiency by passivation of low-angle grain boundaries in flexible low-cost single-crystal-like GaAs thin-film solar cells directly deposited on metal tape

We develop an easily implementable yet effective process to achieve high power conversion efficiency in newly-developed flexible single-crystal-like GaAs thin-film photovoltaic solar cells on cheap metal tape. We study various techniques on the fabricated devices to passivate the defect states associated with dangling bonds at low-angle grain boundaries (LA-GBs) existing in the single-crystal-like GaAs material. We report that sulfur by trioctylphosphine sulfide (TOP:S) solution treatment can partially but effectively passivate the defect states at the LA-GBs to increase all the solar cell performance parameters of open-circuit voltage VOC (33.2%), short-circuit current JSC (19.5%), and fill factor FF (25.8%), resulting in the improvement of the power conversion efficiency more than double. The material and device characterizations and numerical modeling are performed to propose a mechanism, also suggesting that the power conversion efficiency higher than 20%, which is an important target milestone in emerging solar cell technologies, can be achieved. This work presents the first effective passivation of the bulk defects in GaAs at the device level and can also offer a solution for other photonic and electronic devices using non-single-crystalline GaAs films for flexible electronics.

36 MATERIALS SCIENCE↗

Unraveling the Early-Stage Ordering of Krypton Solid Bubbles in Molybdenum: A Multimodal Study

Self-organization of defects such as fission gas bubbles in materials can lead to high inventory capacity for fission gas storage and help mitigate swelling caused by fission gases in nuclear fuel materials under radiation in nuclear reactors. Here, we report the physical mechanism of self-organization of krypton (Kr) gas bubbles in molybdenum (Mo) under ion implantation. The ion fluence and temperature-dependent formation of Kr solid bubble superlattice (SBS) in Mo were investigated by using both synchrotron-based small-angle X-ray scattering (SAXS) and transmission electron microscopy (TEM). Early stage self-organization of gas bubbles is observed at a fluence of 2.5 × 10 16 ions/cm 2 at temperatures of 300–400 °C. The bubble lattice constant increases with increasing implantation temperature from 300 to 400 °C. Both experiments and atomic kinetic Monte Carlo modeling indicate that the Kr solid bubbles are weakly ordered in comparison to previously studied helium (He) gas bubble superlattice (GBS) while the lattice constant are relatively smaller for Kr SBS compared to that of He GBS. The irradiation conditions suggest that spinodal decomposition, which is a form of phase separation, probably precedes gas bubble ordering in Mo. Altogether, our work sheds light on the formation mechanism of noble gas superlattice toward the development of radiation-tolerant materials which are important for the design of advanced nuclear reactors.

36 MATERIALS SCIENCE↗

Electronic and Geometric Contributors to Hydrogen Binding in Uranium Oxide Grain Boundaries

Hydrogen induced corrosion of uranium, which leads to the formation of toxic and pyrophoric UH 3 , raises significant safety concerns for long-term storage of nuclear materials. Previous work suggests hydrogen diffuses through the grain boundaries (GBs) of the passivating oxide layer to initiate hydriding reactions. However, the atomistic mechanisms underlying this phenomenon and the structural factors that control its initiation are not well understood. To address this knowledge gap, here we use a high-throughput density functional theory (DFT) workflow to investigate the adsorption of H and H 2 in the defective bulk UO 2 . Specifically, we have exhaustively investigated the adsorption of H (107 sites) and H 2 (26 sites) in three different coincident site lattice (CSL) GBs: Σ3, Σ5, and Σ9. Compared to the binding energies in pristine UO 2 , we observe significantly stronger hydrogen adsorption at these GB sites. Interestingly, we find that the trends in H and H 2 adsorption vary considerably across the three GB models. In particular, while a small number of sites in Σ5 and Σ9 show exothermic adsorption of H and H 2 , respectively, no such sites are found in Σ3. These results provide fundamental atomistic insights that could guide the development of future corrosion mitigation strategies for the storage of nuclear materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Disentangling Electronic Transport and Hysteresis at Individual Grain Boundaries in Hybrid Perovskites via Automated Scanning Probe Microscopy

Underlying the rapidly increasing photovoltaic efficiency and stability of metal halide perovskites (MHPs) is the advancement in the understanding of the microstructure of polycrystalline MHP thin film. Over the past decade, intense efforts have been aimed at understanding the effect of microstructures on MHP properties, including chemical heterogeneity, strain disorder, phase impurity, etc. It has been found that grain and grain boundary (GB) are tightly related to lots of microscale and nanoscale behavior in MHP thin films. Atomic force microscopy (AFM) is widely used to observe grain and boundary structures in topography and subsequently to study the correlative surface potential and conductivity of these structures. For now, most AFM measurements have been performed in imaging mode to study the static behavior; in contrast, AFM spectroscopy mode allows us to investigate the dynamic behavior of materials, e.g., conductivity under sweeping voltage. However, a major limitation of AFM spectroscopy measurements is that they require manual operation by human operators, and as such only limited data can be obtained, hindering systematic investigations of these microstructures. Here, we designed a workflow combining the conductive AFM measurement with a machine learning (ML) algorithm to systematically investigate grain boundaries in MHPs. The trained ML model can extract GBs locations from the topography image, and the workflow drives the AFM probe to each GB location to perform a current–voltage (IV) curve automatically. Then, we are able to have IV curves at all GB locations, allowing us to systematically understand the property of GBs. Using this method, we discovered that the GB junction points are less conductive, potentially more photoactive, and can play critical roles in MHP stability, while most previous works only focused on the difference between GB and grains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Terahertz Nanoimaging of Perovskite Solar Cell Materials

Direct visualization and quantitative evaluation of charge filling in grain boundary (GB) traps of hybrid metal halide perovskites require dynamic conductivity imaging simultaneously at the terahertz (THz) frequency and nanometer (nm) spatial scales not accessible by conventional transport and imaging methods used thus far. Here, in this study, we apply a THz near-field nanoconductivity mapping to the archetypal metal halide perovskite photovoltaic films and demonstrate that it is a powerful tool to reveal distinct dielectric heterogeneity due to charge trapping and degradation at the single GB level. Our approach visualizes the filled defect ion traps by local THz charge conductivity and allows for extracting a quantitative profile of trapping density in the vicinity of GBs with sub-20 nm resolution. Furthermore, imaging material degradation by tracking local nanodefect distributions overtime identifies a distinct degradation pathway that starts from the GBs and propagates inside the grains over time. The single GB, nano-THz conductivity imaging demonstrated here can be extended to benchmark various perovskite materials and devices for their global photoenergy conversion performance and local charge transfer proprieties of absorbers and interfaces.

14 SOLAR ENERGY↗

Grand canonically optimized grain boundary phases in hexagonal close-packed titanium

Grain boundaries (GBs) profoundly influence the properties and performance of materials, emphasizing the importance of understanding the GB structure and phase behavior. As recent computational studies have demonstrated the existence of multiple GB phases associated with varying the atomic density at the interface, we introduce a validated, open-source GRand canonical Interface Predictor (GRIP) tool that automates high-throughput, grand canonical optimization of GB structures. While previous studies of GB phases have almost exclusively focused on cubic systems, we demonstrate the utility of GRIP in an application to hexagonal close-packed titanium. We perform a systematic high-throughput exploration of tilt GBs in titanium and discover previously unreported structures and phase transitions. In low-angle boundaries, we demonstrate a coupling between point defect absorption and the change in the GB dislocation network topology due to GB phase transformations, which has important implications for the accommodation of radiation-induced defects.

36 MATERIALS SCIENCE↗

Molecular dynamics study of grain boundaries as defect sinks under irradiation in LiAlO 2 and LiAl 5 O 8

Lithium aluminate ceramics, LiAlO 2 and LiAl 5 O 8 , show promise in nuclear environments due to their excellent radiation tolerance. Molecular dynamics simulations investigate grain boundaries (GB) and their role in defect evolution. Results reveal that GBs act as efficient defect sinks, with Li and Al atoms exhibiting distinct behaviors during displacement cascades. Tritium migration in LiAlO 2 is also studied, showing rapid diffusion and stable configurations with oxygen, corroborated by ab initio simulations from the literature. The calculated tritium diffusion coefficient of 1.33 × 10 - ¹⁴ m²/s aligns with the literature, validating the model. LiAl 5 O 8 demonstrates superior defect healing compared to LiAlO 2 , attributed to enhanced atomic transfer between grains and GBs. These findings reveal key insights into defect dynamics, providing essential insights for their application in tritium-producing burnable absorber rods (TPBARs).

36 MATERIALS SCIENCE↗