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At least 973 records · Page 54

Melting, reentrant ordering and peak effect for Wigner crystals with quenched and thermal disorder

Abstract We consider simulations of Wigner crystals in solid state systems interacting with random quenched disorder in the presence of thermal fluctuations. When quenched disorder is absent, there is a well defined melting temperature determined by the proliferation of topological defects, while for zero temperature, there is a critical quenched disorder strength above which topological defects proliferate. When both thermal and quenched disorder are present, these effects compete, and the thermal fluctuations can reduce the effectiveness of the quenched disorder, leading to a reentrant ordered phase in agreement with the predictions of Nelson (1983 Phys. Rev. B 27 2902–14). There are two competing theories for the low temperature behavior, and our simulations show that both capture aspects of the actual response. The critical disorder strength separating ordered from disordered states remains finite as the temperature goes to zero, as predicted by Cha and Fertig (1995 Phys. Rev. Lett. 74 4867–70), instead of dropping to zero as predicted by Nelson. At the same time, the critical disorder strength decreases with decreasing temperature, as predicted by Nelson, instead of remaining constant, as predicted by Cha and Fertig. The onset of the reentrant phase can be deduced based on changes in the transport response, where the reentrant ordering appears as an increase in the mobility or the occurrence of a depinning transition. We also find that when the system is in the ordered state and thermally melts, there is an increase in the effective damping or pinning. This produces a drop in the electron mobility that is similar to the peak effect phenomenon found in superconducting vortices, where thermal effects soften the lattice or break down its elasticity, allowing the particles to better adjust their positions to take full advantage of the quenched disorder.

36 MATERIALS SCIENCE↗

Generalization of Stoney’s equation for flexoelectric thin films on elastic substrates

When a thin film is deposited on an incompatible elastic substrate, the film develops an elastic mismatch strain, causing the film–substrate system to bend. Stoney’s equation relates the curvature of the bent film–substrate system with the residual stress developed in the film, and can be used to infer film properties from curvature measurements. Certain materials exhibit electromechanical coupling, such as piezoelectricity and flexoelectricity, which can alter the curvature and strains. In this work, we generalize Stoney’s equation to include flexoelectric and piezoelectric effects in the film. Considering both open and closed circuit configurations, as well as uniform and non-uniform film properties, we compare different cases of electromechanical coupling and discuss their influence on curvature, strains, and electric polarization in the film.

Ghosh, Swarnava [ORNL] (ORCID:0000000338005264)↗

Effects of N-Doping on Silicon Carbide

Silicon carbide (SiC) is a widely preferred material within many industries due to its favorable properties, most notably its low electrical resistivity at high temperatures, excellent thermal conductivity, and sturdy mechanical properties. Doping, particularly n-type doping, is shown to extremely reduce electrical resistivity, but due to structural changes within the lattice caused by interaction with thermal neutrons, it is possible that other attributes of SiC may also be affected. In addition to review of past literature and data, four-point probe testing, scanning electron microscopy, nanoindentation, strength tests, differential scanning calorimetry and laser flash analysis were used to investigate the effects of n-doping 3C ß-phase SiC. According to temperature dependent measurements, electric resistivity and thermal conductivity both declined as dopant levels increases. Dopant levels are shown to have a significant effect on the mechanical performance of SiC, with the highest dopant levels (4 x 1018 cm-3) providing a 40% decrease in elastic modulus from 420 GPa to 258 GPa and a 30% decrease in hardness from 40 GPa to 27.7 GPa. These values are still above average and doped SiC may prove valuable for nuclear applications.

36 MATERIALS SCIENCE↗

Non-dilute helium-related defect interactions in the near-surface region of plasma-exposed tungsten

We report a systematic energetic analysis of helium-related defect interactions that mediate helium (He) segregation on surfaces of plasma-exposed tungsten at different levels of He ion implantation. We focus on high He fluences that increase the He content in the plasma-exposed material well beyond the dilute limit of He concentration and employ atomic configurations generated by large-scale molecular dynamics simulations of He-implanted tungsten. We perform systematic molecular statics computations of cluster– defect interaction energetics in the highly defect-rich near-surface region of plasma-exposed tungsten for small mobile helium clusters as a function of the cluster distance from the surface. In this region, mobile clusters are also subjected to the stress fields generated by defects such as helium bubbles and other clusters, which govern cluster–defect interactions in addition to the cluster–surface interaction. Based on systematic investigation of individual cluster–defect interactions, we develop a mathematical framework to describe the interaction energy landscapes consisting of elastic interaction potential perturbations to finite-width square-well potentials, where the potential well accounts for cluster trapping by the defect at close range and subsequent coalescence and the perturbation potential is parameterized according to elastic inclusion theory. Superposition of all the relevant interaction potentials provides a comprehensive description of the interaction energy landscape that would be experienced by a small mobile cluster along its migration path toward the plasma-exposed surface at high He fluence. Such descriptions are particularly important for developing atomistically-informed, hierarchical multi-scale models of helium cluster dynamics in plasma-facing materials.

36 MATERIALS SCIENCE↗

A rheological model for loose sands with insights from DEM

A rheological model for loose granular media is developed to capture both solid-like and fluid-like responses during shearing. The proposed model is built by following the mathematical structure of an extended Kelvin–Voigt model, where an elastic spring and plastic slider act in parallel to a viscous damper. This arrangement requires the partition of the total stress into rate-independent and rate-dependent stress components. To model the solid-like behavior, a simple frictional plasticity model is adopted without modifications, thus contributing to the rate-independent stress. Instead, the fluid-like or rate-dependent stress is further decomposed into deviatoric and volumetric parts, by proposing a new formulation based on a combination of the μ(I) relation, originally developed under pressure-controlled shear, with a pressure-shear rate relation derived under volume-controlled shear. The proposed formulation allows the model to capture both the increase in the friction coefficient and the enhanced dilation at high shear rates. High-fidelity simulation data, obtained from discrete element method and multiscale modelling, are used to evaluate the performance of the proposed constitutive model. The model provides accurate results under both drained and undrained simple shear paths across a wide range of shear rates. Furthermore, it successfully reproduces at much lower computational cost the flowslide mobility computed through multiscale simulations, which is primarily regulated by the shear rate dependence of the material properties during the dynamic runout stage.

Elasticity↗

Phase-field modeling of dislocation–interstitial interactions

The mechanical behavior of body-centered cubic (BCC) materials can be dramatically affected by the presence of interstitial solute atoms. Here we present a new phase-field dislocation dynamics formulation to include the diffusion of interstitials. Short-range interactions are accounted for by a concentration-dependent lattice energy, and long-range interactions are accounted for by modifications to the elastic energy. The interstitial diffusion law introduces gradients that require methods for minimizing Gibbs oscillations, which is done via a modified Green’s function. The formulation is general to any solute-solvent system and is applied here to Nb-O as a model system, whose interstitial parameters are obtained from ab initio calculations. The effect of O on the core structures of Nb edge and screw dislocations is calculated. The diffusion of O to form interstitial atmospheres around dislocation cores is simulated, as well as the critical stresses required for dislocations to break away or cross slip from these atmospheres. Future applications of the method to simulate complex interstitial embrittlement mechanisms are discussed.

36 MATERIALS SCIENCE↗

Hierarchical Reinforcement Learning of a Short-Range Bond-Order Potential for Silica: Analytic Embedding of Coordination with Classical Efficiency

Reinforcement learning (RL) has recently emerged as a data-efficient strategy to parametrize short-range interatomic potentials. Building on our past RL optimization of pairwise silica models, we extend the framework to a bond-order (Tersoff-type) potential that provides an analytic embedding of local coordination through a three-body term. A hierarchical RL workflow combining continuous-action Monte Carlo Tree Search and property-based rewards efficiently explores the 26-dimensional parameter space, sequentially optimizing lattice parameters, densities, angles, and cohesive energies of 21 silica polymorphs. The resulting models, Q-Tersoff and ML-Tersoff, reproduce the energetic ordering of low-energy phases and capture the angular correlations and amorphous structure factors of silica with improved fidelity over pairwise force fields, while remaining orders of magnitude faster than high-dimensional machine-learned potentials. Both models underperform for elastic constants and high-energy frameworks, delineating the limits of the current analytic form. The approach establishes a general and interpretable route to angle-aware, short-range potentials that bridge physics-based and machine-learned descriptions of silicate materials.

36 MATERIALS SCIENCE↗

Tensile Deformation of DED Graded IN718-René41 Superalloy at 650°C by in-situ Neutron Diffraction and Digital Image Correlation

A compositionally graded material comprised IN718 (718, γ'/γ" strengthened superalloy) and René41 (R41, a medium γ' strengthened superalloy) was fabricated using laser blown-powder directed energy deposition (DED/LB-M). Hot gas path components that require high and low temperature capabilities at different locations may benefit from such graded superalloy, potentially eliminating the use of welded or mechanically joined components and reducing cost. In the present work, microstructure and 650°C tensile behavior of 718-R41 graded superalloy in as-built and heat-treated states are investigated by Digital Image Correlation (DIC), in-situ neutron diffraction, coupled with conventional characterization techniques. The applied heat treatment generates static recrystallization and equiaxed grains in 718 rich compositions, while R41 rich compositions remain partially or un-recrystallized. Yield strengths of 718 and R41 sections in heat-treated state are comparable to wrought forms but the graded compositions show weakness. From neutron experiment, diffraction elastic constants and single crystal elastic constants are calculated, which show small difference between the as-built and heat-treated states and between the γ and γ' phases. Grain-level load transfer from the (220) grains to (200) grains is found to be composition dependent, and qualitatively agrees with DIC measured macroscopic yield strength. Within the (200) grains, the γ/γ' phases deform elastically until the γ phase yields and afterwards the γ' phase takes load from γ phase.

digital image correlation↗

Mechanically tunable elastomer and cellulose nanocrystal composites as scaffolds for in vitro cell studies

Considering the range of properties that various materials offer for tissue engineering it has come clear that no one size fits all, as no one material can be fully effective for all types of cell and ensuing tissues. Scaffolds need to address the delicate balance between cell-scaffold interactions and the particular requirements of different cell types. To address the specific needs for the controlled growth of tissues it is imperative to match scaffold stiffness and elasticity to cells and tissues of interest to promote regeneration success. We here report an efficient method for creating scaffolds of tunable elasticity by generating a range of composites based on ε-caprolactone-D,L-lactide-based elastomer with cellulose nanocrystals (CNC). Two specific composites with different Young's modulus (E) values (~5 MPa and ~15 MPa) were selected and fully evaluated by tensile tests, Fourier Transform-Infrared (FT-IR), Scanning Electron Microscopy (SEM), contact angle measurements, and X-ray scattering. As a proof of concept this work studies how matching the scaffold's mechanical properties to neuroblastomas and fibroblasts cells affects cell behavior. Specifically, the composite with lower E, by design with less CNC content, is more suitable for neuroblastomas, whereas the one with higher E via higher CNC content is more suited for human dermal fibroblasts. The approach of matching cells with appropriate mechanical environments can provide important insights into fundamental cell behaviors.

36 MATERIALS SCIENCE↗

Ultra-fast interpretable machine-learning potentials

Abstract All-atom dynamics simulations are an indispensable quantitative tool in physics, chemistry, and materials science, but large systems and long simulation times remain challenging due to the trade-off between computational efficiency and predictive accuracy. To address this challenge, we combine effective two- and three-body potentials in a cubic B-spline basis with regularized linear regression to obtain machine-learning potentials that are physically interpretable, sufficiently accurate for applications, as fast as the fastest traditional empirical potentials, and two to four orders of magnitude faster than state-of-the-art machine-learning potentials. For data from empirical potentials, we demonstrate the exact retrieval of the potential. For data from density functional theory, the predicted energies, forces, and derived properties, including phonon spectra, elastic constants, and melting points, closely match those of the reference method. The introduced potentials might contribute towards accurate all-atom dynamics simulations of large atomistic systems over long-time scales.

36 MATERIALS SCIENCE↗

Deep reinforcement learning for predicting kinetic pathways to surface reconstruction in a ternary alloy

Abstract The majority of computational catalyst design focuses on the screening of material components and alloy composition to optimize selectivity and activity for a given reaction. However, predicting the metastability of the alloy catalyst surface at realistic operating conditions requires an extensive sampling of possible surface reconstructions and their associated kinetic pathways. We present CatGym, a deep reinforcement learning (DRL) environment for predicting the thermal surface reconstruction pathways and their associated kinetic barriers in crystalline solids under reaction conditions. The DRL agent iteratively changes the positions of atoms in the near-surface region to generate kinetic pathways to accessible local minima involving changes in the surface compositions. We showcase our agent by predicting the surface reconstruction pathways of a ternary Ni 3 Pd 3 Au 2 (111) alloy catalyst. Our results show that the DRL agent can not only explore more diverse surface compositions than the conventional minima hopping method, but also generate the kinetic surface reconstruction pathways. We further demonstrate that the kinetic pathway to a global minimum energy surface composition and its associated transition state predicted by our agent is in good agreement with the minimum energy path predicted by nudged elastic band calculations.

36 MATERIALS SCIENCE↗

Thermally driven phase transitions in freestanding low-buckled silicene, germanene, and stanene

Low-buckled silicene, germanene, and stanene are group-IV graphene allotropes. They form a honeycomb lattice out of two interpenetrating (A and B) triangular sublattices that are vertically separated by a small distance Δ z . The atomic numbers Z of silicon, germanium, and tin are larger than that of carbon (Z C = 6), making them the first experimentally viable two-dimensional topological insulators. Those materials have a twice-energy-degenerate atomistic structure characterized by the buckling direction of the B sublattice with respect to the A sublattice [whereby the B atom either protrudes above (Δ z > 0) or below (Δ z < 0) the A atoms], and the consequences of that energy degeneracy on their elastic and electronic properties have not been reported thus far. Here, we uncover ferroelastic, bistable behavior on silicene, which turns into an average planar structure at about 600 K. Furthermore, the creation of electron and hole puddles obfuscates the zero-temperature spin-orbit coupling (SOC)-induced band gaps at temperatures as low as 200 K, which may discard silicene as a viable two-dimensional topological insulator for room-temperature applications. Germanene, on the other hand, never undergoes a low-buckled-to-planar two-dimensional transformation, becoming amorphous at around 675 K instead, and preserving its SOC-induced band gap despite band broadening. Stanene undergoes a transition onto a crystalline three-dimensional structure at about 300 K, preserving its SOC-induced electronic band gap up to that temperature. Unlike what is observed in silicene and germanene, stanene readily develops a higher-coordinated structure with a high degree of structural order. Furthermore, the structural phenomena are shown to have far-reaching consequences for the electronic and vibrational properties of those two-dimensional topological insulators.

36 MATERIALS SCIENCE↗

A Comparative Study of Layer Heating and Continuous Heating Methods on Prediction Accuracy of Residual Stresses in Selective Laser Melted Tube Samples

Thermal distortion and residual stresses are two important factors that affect the quality and reliability of steel parts manufactured by laser powder bed fusion (LPBF) processes. A cost-effective model for evaluation of those heat effects is needed to refine the manufacturing process and provides insights into the product design and heat treatment. In this study, the layer heating method and sophisticated track-layer scanning method were applied to simulate the thermo-mechanical response of IN625 tube parts built by LPBF. Based on the similarity of temperature field in each layer deposit, a swept mesh was constructed to perform the thermal analysis for top layer, with the rest of layers referring to the temperature by node number offsetting. A novel explicit finite element analysis code accelerated by graphics processing unit was used for the massive-element numerical analysis. The computational accuracy and efficiency of the layer heating and track-layer scanning methods were compared in detail. It is shown that layer heating method can efficiently capture the pattern of stress distribution with reasonable accuracy in stress magnitude. The grouped track-layer scanning method can predict the residual stress and strain more accurately at a higher cost (5 ~ 10×). The elastic strain distribution was compared with the measurement by X-ray diffraction, confirming the accuracy of residual stress prediction.

36 MATERIALS SCIENCE↗

Modeling the interfacial failure and resulting mechanical properties of z-pinned additively manufactured composites

The mechanical properties of Fused Filament Fabrication (FFF) parts are limited in the build direction, albeit advantages such as design flexibility and in-house customization. Here, in this paper, a novel z-pinning approach that enhances mechanical properties in the build direction by depositing material across multiple layers within the part was investigated through numerical simulations and validated experimentally. A finite element model for z-pinned composite structures was developed by assigning fiber-orientation dependent material properties obtained using a micromechanics approach to beads and pins. The bead-to-bead and pin-to-pin adhesions within the z-pinned structures were modeled using a cohesive traction separation law. The properties of cohesive elements for carbon fiber-reinforced polylactic acid (CF-PLA) z-pinned composites were calibrated using tensile experiments. The elastic modulus and tensile strength of CF-PLA z-pinned composites in the build direction were predicted with the developed numerical model. The numerical investigation on various geometrical parameters revealed that the largest pin volume increases the stiffness and tensile strength by 40% and thus, has the greatest influence on the mechanical properties of the z-pinned composites. The effect of z-pin geometrical parameters on the mechanical properties was summarized to aid in the design of z-pinned additively manufactured composite structures.

36 MATERIALS SCIENCE↗

A fast Fourier transform-based solver for elastic micropolar composites

This work presents a spectral micromechanical formulation for obtaining the full-field and homogenized response of elastic micropolar composites. The algorithm relies on a coupled set of convolution integral equations for the micropolar strains, where periodic Green’s operators associated with a linear homogeneous reference medium are convolved with functions of the Cauchy and couple stress fields that encode the material’s heterogeneity, as well as any potential material nonlinearity. Such convolution integral equations take an algebraic form in the reciprocal Fourier space that can be solved iteratively. In this vein, the fast Fourier transform (FFT) algorithm is leveraged to accelerate the numerical solution, resulting in a mesh-free formulation in which the periodic unit cell representing the heterogeneous material can be discretized by a regular grid of pixels in two dimensions (or voxels in three dimensions). For verification, the numerical solutions obtained with the micropolar FFT solver are compared with analytical solutions for a matrix with a dilute circular inclusion subjected to plane strain loading. The developed computational framework is then used to study length-scale effects and effective (micropolar) moduli of composites with various topological configurations.

97 MATHEMATICS AND COMPUTING↗

Response of 304L stainless steel and 6061-T651 aluminum alloy at -40 °C

The objective of this work is to extend the thermal-mechanical, elastic-plastic calibrations for 304L stainless steel [1] and and 6061-T651 aluminum alloy [2] to the regime between room temperature and -40 °C. The basis to extend the calibration consisted of new uniaxial tension tests conducted at -40 °C using the same plate material stocks, circular cylindrical specimen geometries and testing apparatus as previously, followed by attempts to fit power-law hardening functions to replicate the response observed in the specimens and then extend the yield, hardening constant, hardening exponent and rate constant functions in the calibrations to cover the new temperature regime.

36 MATERIALS SCIENCE↗