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At least 55 records · Page 3

Probing the limits of metal plasticity with molecular dynamics simulations

Ordinarily, the strength and plasticity properties of a metal are defined by dislocations—line defects in the crystal lattice whose motion results in material slippage along lattice planes. Dislocation dynamics models are usually used as mesoscale proxies for true atomistic dynamics, which are computationally expensive to perform routinely. However, atomistic simulations accurately capture every possible mechanism of material response, resolving every “jiggle and wiggle” of atomic motion, whereas dislocation dynamics models do not. We present fully dynamic atomistic simulations of bulk single-crystal plasticity in the body-centred-cubic metal tantalum. Our goal is to quantify the conditions under which the limits of dislocation-mediated plasticity are reached and to understand what happens to the metal beyond any such limit. In our simulations, the metal is compressed at ultrahigh strain rates along its [001] crystal axis under conditions of constant pressure, temperature and strain rate. To address the complexity of crystal plasticity processes on the length scales (85–340 nm) and timescales (1 ns–1μs) that we examine, we use recently developed methods of in situ computational microscopy to recast the enormous amount of transient trajectory data generated in our simulations into a form that can be analysed by a human. Our simulations predict that, on reaching certain limiting conditions of strain, dislocations alone can no longer relieve mechanical loads; instead, another mechanism, known as deformation twinning (the sudden re-orientation of the crystal lattice), takes over as the dominant mode of dynamic response. Below this limit, the metal assumes a strain-path-independent steady state of plastic flow in which the flow stress and the dislocation density remain constant as long as the conditions of straining thereafter remain unchanged. In this distinct state, tantalum flows like a viscous fluid while retaining its crystal lattice and remaining a strong and stiff metal.

36 MATERIALS SCIENCE↗

Exascale Dislocation Simulator

ExaDiS, or Exascale Dislocation Simulator, is a set of software modules written to enable numerical simulations of large groups of moving and interacting dislocations, line defects in crystals responsible for crystal plasticity. By tracking time evolution of sufficiently large dislocation ensembles, ExaDiS predicts plasticity response and plastic strength of crystalline materials. ExaDiS is built around a library of core functions for Discrete Dislocation Dynamics method specifically written to perform efficient computations on GPUs.

Bertin, Nicolas↗

Precipitation of binary quasicrystals along dislocations

Dislocations in crystals naturally break the symmetry of the bulk, introducing local atomic configurations with symmetries such as fivefold rings. But dislocations do not usually nucleate aperiodic structure along their length. Here we demonstrate the formation of extended binary quasicrystalline precipitates with Penrose-like random-tiling structures, beginning with chemical ordering within the pentagonal structure at cores of prismatic dislocations in Mg–Zn alloys. Atomic resolution observations indicate that icosahedral chains centered along [0001] pillars of Zn interstitial atoms are formed templated by the fivefold rings at dislocation cores. They subsequently form columns of rhombic and elongated hexagonal tiles parallel to the dislocation lines. Quasicrystalline precipitates are formed by random tiling of these rhombic and hexagonal tiles. Such precipitation may impact dislocation glide and alloy strength.

36 MATERIALS SCIENCE↗

Atomistic calculations of dislocation core energy in aluminium

A robust molecular-dynamics simulation method for calculating dislocation core energies has been developed. This method has unique advantages: It does not require artificial boundary conditions, is applicable for mixed dislocations, and can yield converged results regardless of the atomistic system size. Utilizing a high-fidelity bond order potential, we have applied this method in aluminium to calculate the dislocation core energy as a function of the angle β between the dislocation line and the Burgers vector. These calculations show that, for the face-centered-cubic aluminium explored, the dislocation core energy follows the same functional dependence on β as the dislocation elastic energy: E c = Asin 2 β + Bcos 2 β, and this dependence is independent of temperature between 100 and 300 K. By further analyzing the energetics of an extended dislocation core, we elucidate the relationship between the core energy and the core radius of a perfect versus an extended dislocation. As a result, with our methodology, the dislocation core energy can accurately be accounted for in models of dislocation-mediated plasticity.

36 MATERIALS SCIENCE↗

Quantifying dislocation-type defects in post irradiation examination via transfer learning

The quantitative analysis of dislocation-type defects in irradiated materials is critical to materials characterization in the nuclear energy industry. The conventional approach of an instrument scientist manually identifying any dislocation defects is both time-consuming and subjective, thereby potentially introducing inconsistencies in the quantification. This work approaches dislocation-type defect identification and segmentation using a standard open-source computer vision model, YOLO11, that leverages transfer learning to create a highly effective dislocation defect quantification tool while using only a minimal number of annotated micrographs for training. This model demonstrates the ability to segment both dislocation lines and loops concurrently in micrographs with high pixel noise levels and on two alloys not represented in the training set. Inference of dislocation defects using transmission electron microscopy on three different irradiated alloys relevant to the nuclear energy industry are examined in this work with widely varying pixel noise levels and with completely unrelated composition and dislocation formations for practical post irradiation examination analysis. Code and models are available at https://github.com/idaholab/PANDA.

36 MATERIALS SCIENCE↗

Linear Complexions: Metastable Phase Formation and Coexistence at Dislocations

The unique three-phase coexistence of metastable B2–FeNi with stable L1 0 –FeNi and L1 2 –FeNi 3 is discovered near edge dislocations in body-centered cubic Fe-Ni alloys using atomistic simulations. Stable nanoscale precipitate arrays, formed along the compression side of dislocation lines and defined as linear complexions, were observed for a wide range of compositions and temperatures. Here, by analyzing the thermodynamics associated with these phase transitions, we are able to explain the metastable phase formation and coexistence, in the process defining new research avenues for theoretical and experimental investigations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Discrete dislocation dynamics for crystal RVEs. Part 1: Periodic network kinematics

A novel implementation of the dislocation flux boundary condition in discrete dislocation dynamics is presented. The continuity of the individual dislocation loops in a periodic representative crystal volume (RVE) is enforced across the boundary of the RVE with the help of a dual topological description for representing dislocation line kinematics in two equivalent spaces representing the deforming crystal, the RVE and the unbounded crystal spaces. The former describes the motion of the dislocations in the simulated crystal RVE whereas the latter represents the motion of dislocations in an infinite space containing all replicas of the RVE. A mapping between the two spaces forms the basis of the implementation of flux boundary condition. The implementation details are discussed in the context of statistical homogeneity of bulk crystals undergoing macroscopically homogeneous plastic deformation. In this case, the boundary nodes associated with dislocation segments bear no relevance in the motion of the dislocations. Finally, some test cases are presented and discussed to establish the proposed approach.

42 ENGINEERING↗

Identification of dislocation etch pits in n-type GaAs by NIR transmission microscopy

An optical method is described for identifying dislocation etch pits in n-type GaAS, using near-IR brightfield transmission microscopy. Dislocations are revealed in a nondestructive manner through contrasts that are likely due to impurity decoration of the dislocation lines. By subjecting the same wafers to a photoetching technique, it was established that each etch pit on the surface is associated with a dislocation and that the termination of each (decorated) dislocation is an etch pit.

Cao, X. Z.↗

Nanocompression of 20 nm Silver Nanoparticles: In situ Aberration‐Corrected TEM and Atomistic Simulations

Single‐crystalline nanoparticles play an increasingly important role in a wide variety of fields including pharmaceuticals, advanced materials, catalysts for fuel cells, energy materials, as well as environmental detection and monitoring. Yet, the deformation mechanisms of very small nanoparticles are still poorly understood, in particular the role played by single dislocations and their interaction with surfaces. Here, in this work, silver nanoparticles with particularly small dimensions (≈20 nanometers in diameter) are compressed in situ in an aberration‐corrected transmission electron microscopy (TEM) and molecular dynamics (MD) simulations. During compression, the emergence of both dislocations and nanotwins are observed. However, these defects prove to be unstable and disappear upon removal of the indenter. Atomistic simulations confirm the role played by image stresses associated with the nearby surfaces and the reduction in dislocation line length as it approaches the free surface, thereby supporting the experimental observations. These results provide justification for the frequent observation of the absence of dislocations in nanoparticles of a few nanometers in size during in situ experiments, even after significant deformation. This phenomenon contributes to the self‐healing of samples through dislocation ejection toward the surfaces.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The effect of frictional stress on the calculation of critical thickness in epitaxy

A model is developed for lattice-mismatched epitaxial layers, which makes it possible to calculate both the equilibrium critical thickness as well as the kinetic rate of misfit accommodations. The technique for calculating the equilibrium critical thickness is similar to that of Matthews (1966) in that it uses the force balance approach and the Volterra description of the dislocation line. For the kinetic component of misfit accommodation, the model uses a dynamic frictional force. A simple criterion is proposed for determining whether the generation of misfit dislocations will be controlled by the equilibrium or the kinetic factors.

Fox, Bradley A.↗

Sweep-tracing algorithm: in silico slip crystallography and tension-compression asymmetry in BCC metals

Abstract Direct Molecular Dynamics (MD) simulations are being increasingly employed to model dislocation-mediated crystal plasticity with atomic resolution. Thanks to the dislocation extraction algorithm (DXA), dislocation lines can be now accurately detected and positioned in space and their Burgers vector unambiguously identified in silico, while the simulation is being performed. However, DXA extracts static snapshots of dislocation configurations that by themselves present no information on dislocation motion. Referred to as a sweep-tracing algorithm (STA), here we introduce a practical computational method to observe dislocation motion and to accurately quantify its important characteristics such as preferential slip planes (slip crystallography). STA reconnects pairs of successive snapshots extracted by DXA and computes elementary slip facets thus precisely tracing the motion of dislocation segments from one snapshot to the next. As a testbed for our new method, we apply STA to the analysis of dislocation motion in large-scale MD simulations of single crystal plasticity in BCC metals. We observe that, when the crystal is subjected to uniaxial deformation along its [001] axis, dislocation slip predominantly occurs on the {112} maximum resolved shear stress plane under tension, while in compression slip is non-crystallographic (pencil) resulting in asymmetric mechanical response. The marked contrast in the observed slip crystallography is attributed to the twinning/anti-twinning asymmetry of shears in the {112} planes relatively favoring dislocation motion in the twinning sense while hindering dislocations from moving in the anti-twinning directions.

36 MATERIALS SCIENCE↗

Development of Mechanistic Fission Gas Release and Swelling Models for UN Fuels in BISON

This report describes the work in NEAMS (Nuclear Energy Advanced Modeling and Simulation) to develop a mechanistic fission gas model for uranium nitride fuels in BISON. The existing Sifgrs (Simple integrated fission gas release and swelling) model tracks the average properties of two bubble populations in the bulk and at the grain boundaries. It was recognized that dislocations play a crucial role in the fission gas swelling of UN, and an irradiation-induced dislocation density model was needed, as well as a model describing how fission gas interacts with dislocations creating a third population of bubbles along dislocations. A mechanistic model that tracks dislocation bubbles was implemented in Sifgrs. This model was used to simulate fission gas swelling and release in UN. Lower-length-scale calculations and experimental observations from carbide fuel were leveraged to help populate the model with essential parameters. As a placeholder, an empirical function was formulated for the evolution of the dislocation network. Because of the difference in evolution of this network at different temperatures, the dislocation bubbles are able to capture behavior that the bulk intragranular bubbles cannot. It was found that the bulk bubbles dominate microscopic swelling at low temperatures, and the dislocation bubbles dominate at higher temperatures. Based on this model, the transition between the two bubble types is the main factor behind the breakaway swelling phenomenon in UN. In order to test the model, a couple of assessments were run. For the lower temperature JOYO pins, the model produces reasonable fission gas release and swelling values. For the higher temperature SP1 pin, the model dramatically underestimates the fission gas release. This issue is attributed to the gas being trapped inside dislocation bubbles, unable to escape to grain boundaries to cause fission gas release, and could be remedied by a mechanistic dislocation model that allows the dislocation density to decrease at very high temperatures. A preliminary mechanistic dislocation model was developed supported by first-principle calculations. These calculations provided valuable insight into how interstitial defects cluster in UN in the {110} orientation, and may eventually form dislocation loops, leading to the conclusion that dislocation loops may nucleate from these clusters. An estimate of the dislocation line energy in UN was obtained and will be improved in future work. The free-energy cluster dynamics code Centipede was used to track interstitial and vacancy absorption at dislocation loops and calculate their growth. In addition, improvements to Centipede were made including new convergence criteria for transient simulations and sink driving force updates.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Defect-Seeded Atomic Layer Deposition of Metal Oxides on the Basal Plane of 2D Layered Materials

Atomic layer deposition (ALD) on mechanically exfoliated 2D layered materials spontaneously produces network patterns of metal oxide nanoparticles in triangular and linear deposits on the basal surface. The network patterns formed under a range of ALD conditions and were independent of the orientation of the substrate in the ALD reactor. The patterns were produced on MoS 2 or HOPG when either tetrakis(dimethylamido)titanium or bis(ethylcyclopentadienyl)manganese were used as precursors, suggesting that the phenomenon is general for 2D materials. Transmission electron microscopy revealed the presence, prior to deposition, of dislocation networks along the basal plane of mechanically exfoliated 2D flakes, indicating that periodical basal plane defects related to disruptions in the van der Waals stacking of layers, such as perfect line dislocations and triangular extended stacking faults networks, introduce a surface reactivity landscape that leads to the emergence of patterned deposition.

36 MATERIALS SCIENCE↗

Hydrostatic pressure effect on mechanical behavior and texture evolution of Al and Brass

The effect of hydrostatic pressure on shear strength and microstructural evolution of polycrystalline FCC metals was investigated. Hydrostatic pressure of up to 5 GPa was imposed on commercial purity aluminum and 70/30 brass samples using a modified opposed-anvil apparatus (tri-anvil) that allows for measurement of shear strength in thin foil specimens. Similar to the previous investigations made in BCC metals (Ta and Mo), the shear strength of FCC metals increases significantly as the pressure rises. At 5 GPa, the shear strength of aluminum increased to 8 times its value at atmospheric pressure and 70/30 brass increased by a factor of 2.7. Here, EBSD analysis reveals an evident accumulation of dislocations in all sheared samples, with an approximately 50% decrease in grain diameter. Texture analysis suggests that, in addition to helping form selectively oriented dislocation walls, hydrostatic pressure also serves as a threshold to select certain favorable orientations in sheared metals. We propose that these hydrostatic pressure effects are intrinsically due to the excess volume associated with the cylindrical strain field of dislocation lines.

36 MATERIALS SCIENCE↗

Application of Weak-Beam Dark-Field STEM for Dislocation Loop Analysis

Nanoscale dislocation loops formed by irradiation can significantly contribute to both irradiation hardening and embrittlement of materials when subjected to extreme nuclear reactor environments. Here, this study explores the application of weak-beam dark-field (WBDF) scanning transmission electron microscopy (STEM) methods for quantitative irradiation-induced defect analysis in crystalline materials, with a specific focus on dislocation loop imaging and analysis. A high-purity Fe-5 wt% Cr model alloy was irradiated with 8 MeV Fe 2+ ions at 450°C to a fluence of 8.8 × 10 19 m -2 , inducing dislocation loops for analysis. While transmission electron microscopy (TEM) has traditionally been the primary tool for dislocation imaging, recent advancements in STEM technology have reignited interest in using STEM for defect imaging. This study introduces and compares three WBDF STEM methods, demonstrating their effectiveness in suppressing background contrasts, isolating defect information for dislocation loop type classification, providing finer dislocation line images for small loop analysis, and presenting inside–outside contrast for identifying loop nature. Experimental findings indicate that WBDF STEM methods surpass traditional TEM approaches, yielding clearer and more detailed images of dislocation loops. The study concludes by discussing the potential applications of WBDF STEM techniques in defect analysis, emphasizing their adaptability across various material systems beyond nuclear materials.

36 MATERIALS SCIENCE↗

Deep Learning for Semantic Segmentation of Defects in Advanced STEM Images of Steels

Crystalline materials exhibit long-range ordered lattice unit, within which resides nonperiodic structural features called defects. These crystallographic defects play a vital role in determining the physical and mechanical properties of a wide range of material systems. While computer vision has demonstrated success in recognizing feature patterns in images with well defined contrast, automated identification of nanometer scale crystallographic defects in electron micrographs governed by complex contrast mechanism is still a challenging task. Here, building upon an advanced defect imaging mode that offers high feature clarity, we introduce DefectSegNet - a new convolutional neural network (CNN) architecture that performs semantic segmentation of three common crystallographic defects in structural alloys: dislocation lines, precipitates and voids. Results from supervised training of a small set of high-quality defect images of steels show high pixel-wise accuracy across all three types of defects: 91.60 ± 1.77% on dislocations, 93.39 ± 1.00% on precipitates, and 98.85 ± 0.56% on voids. We discuss the sources of uncertainties in CNN prediction, and the training data in terms of feature density, representation and homogeneity and their effects on deep learning performance. Further defect quantification using DefectSegNet prediction outperforms human expert average, presenting a promising new workflow for fast and statistically meaningful quantification of materials defects.

36 MATERIALS SCIENCE↗

In-Situ Visualization of Long-Range Defect Interactions at the Edge of Melting

Connecting a bulk material’s microscopic defects to its macroscopic properties is an age-old problem in materials science. Long-range interactions between dislocations (line defects) are known to play a key role in how materials deform or melt, but we lack the tools to connect these dynamics to the macroscopic properties. We introduce time-resolved dark-field X-ray microscopy to directly visualize how dislocations move and interact over hundreds of micrometers, deep inside bulk aluminum. With real-time movies, we reveal the thermally activated motion and interactions of dislocations that comprise a boundary, and show how weakened binding forces inhomogeneously destabilize the structure at 99% of the melting temperature. Connecting dynamics of the microstructure to its stability, we provide important opportunities to guide and validate multiscale models that are yet untested.

36 MATERIALS SCIENCE↗