Superplastic Creep of Metal Nanowires From Rate-Dependent Plasticity Transition

W. Tao, P. Cao and H.S. Park
ACS Nano 2018; 12:4984-4992

Abstract

Understanding the time-dependent mechanical behavior of nanomaterials such as nanowires is essential to predict their reliability in nanomechanical devices. This understanding is typically obtained using creep tests, which are the most fundamental loading mechanism by which the time-dependent deformation of materials is characterized. However, due to existing challenges facing both experimentalists and theorists, the time-dependent mechanical response of nanowires is not well-understood. Here, we use atomistic simulations that can access experimental time scales to examine the creep of single crystal FCC metal (Cu, Ag, Pt) nanowires. We report that both Cu and Ag nanowires show significantly increased ductility and a novel form of superplasticity under low creep stresses, where the superplasticity is driven by a rate-dependent transition in defect nucleation from twinning to trailing partial dislocations at the micro or millisecond timescale. The transition in deformation mechanism also governs a corresponding transition in the stress-dependent creep time at the microsecond (Ag) and millisecond (Cu) timescales. Overall, this work demonstrates the necessity of accessing timescales that far exceed those seen in conventional atomistic modeling for accurate insights into the time-dependent mechanical behavior and properties of nanomaterials.

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Nanomechanics of Slip Avalanches in Amorphous Plasticity

P. Cao, K.A. Dahmen, A. Kushima, W.J. Wright, H.S. Park, M.P. Short and S. Yip
Journal of the Mechanics and Physics of Solids 2018; 114:158-171

Abstract

Discrete stress relaxations (slip avalanches) in a model metallic glass under uniaxial compres- sion are studied using a metadynamics algorithm for molecular simulation at experimental strain rates. The onset of yielding is observed at the first major stress drop, accompanied, upon analysis, by the formation of a single localized shear band region spanning the entire system. During the elastic response prior to yielding, low concentrations of shear transformation deformation events appear intermittently and spatially uncorrelated. During serrated flow following yielding, small stress drops occur interspersed between large drops. The simulation results point to a threshold value of stress dissipation as a characteristic feature separating major and minor avalanches consistent with mean-field modeling analysis and mechanical testing experiments. We further interpret this behavior to be a consequence of a nonlinear interplay of two prevailing mechanisms of amorphous plasticity, thermally activated atomic diffusion and stress-induced shear transformations, originally proposed by Spaepen and Argon, respectively. Probing the atomistic processes at widely separate strain rates gives insight to different modes of shear band formation: percolation of shear transformations versus crack-like propagation. Additionally a focus on strain-rate dependence as a function of a crossover avalanche size has implications for nanomechanical modeling of spatially and temporally heterogeneous dynamics.

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Atomistic Simulation of the Rate-Dependent Ductile-to-Brittle Failure Transition in Bicrystalline Metal Nanowires

W. Tao, P. Cao and H.S. Park
Nano Letters 2018; 18:1296-1304

Abstract

The mechanical properties and plastic deformation mechanisms of metal nanowires have been studied intensely for many years. One of the important yet unresolved challenges in this field is to bridge the gap in properties and deformation mechanisms reported for slow strain rate experiments (10-2 s-1), and high strain rate molecular dynamics (MD) simulations (108 s-1) such that a complete understanding of strain rate effects on defect nucleation can be obtained. In this work, we use long time scale atomistic modeling based on potential energy surface exploration to elucidate the atomistic mechanisms governing a strain-rate-dependent incipient plasticity and yielding transition for face centered cubic (FCC) copper and silver nanowires. The transition occurs for both metals with both pristine and rough surfaces for all computationally accessible diameters (< 10 nm). We find that the yield transition is induced by a transition in the incipient plastic event from Shockley partials nucleated on primary slip systems at MD strain rates to the nucleation of planar defects on non-Schmid slip planes at experimental strain rates, where multiple twin boundaries and planar stacking faults appear in copper and silver, respectively. Finally, we demonstrate that at experimental strain rates, a ductile-to-brittle transition in failure mode similar to previous experimental studies on bicrystalline silver nanowires is observed, which is driven by differences in dislocation activity and grain boundary mobility as compared to the high strain rate case.

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Atomistic Modeling at Experimental Strain Rates and Time Scales

X. Yan, P. Cao, W. Tao, P. Sharma and H.S. Park
Journal of Physics D: Applied Physics (invited topical review) 2016; 49: 493002

Abstract

Modeling physical phenomena with atomistic fidelity and at laboratory time-scales is one of the holy grails of computational materials science. Conventional molecular dynamics (MD) simulations enable the elucidation of an astonishing array of phenomena inherent in the mechanical and chemical behavior of materials. However conventional MD, with our current computational modalities, is incapable of resolving time-scales longer than microseconds (at best). In this short perspective article, we briefly review a recently proposed approach---the so-called autonomous basin climbing (ABC) method--- that in certain instances can provide valuable information on slow-time-scale processes. We provide a general summary of the principles underlying the ABC approach, with emphasis on recent methodological developments enabling the study of mechanically-driven processes at slow (experimental) strain rates and time scales. Specifically, we show that by combining a strong physical understanding of the underlying phenomena, kinetic Monte Carlo, transition state theory and minimum energy pathway methods, the ABC method has been found to be useful in a variety of mechanically-driven problems ranging from prediction of creep-behavior in metals, constitutive laws for grain boundary sliding, void nucleation rates, diffusion in amorphous materials to protein unfolding. Aside from reviewing the basic ideas underlying this approach, we emphasize some of the key challenges encountered in our own personal research work and suggest future research avenues for exploration.

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Surface Shear Transformation Zones in Amorphous Solids

P. Cao, X. Lin and H.S. Park
Physical Review E 2014; 90:012311

Abstract

We perform a systematic study of the characteristics of shear transformation zones (STZs) that nucleate at free surfaces of two-dimensional amorphous solids subject to tensile loading using two different atomistic simulation methods, the standard athermal, quasistatic (AQ) approach and our recently developed self-learning metabasin escape (SLME) method to account for the finite temperature and strain-rate effects. In the AQ, or strain-driven limit, the nonaffine displacement fields of surface STZs decay exponentially away from their centers at similar decay rates as their bulk counterparts, though the direction of maximum nonaffine displacement is tilted away from the tensile axis due to surface effects. Using the SLME method at room temperature and at the high strain rates that are seen in classical molecular dynamics simulations, the characteristics for both bulk and surface STZs are found to be identical to those seen in the AQ simulations. However, using the SLME method at room temperature and experimentally-relevant strain rates, we find a transition in the surface STZ characteristics where a loss in the characteristic angular tensile-compression symmetry is observed. Finally, the thermally-activated surface STZs exhibit a slower decay rate in the nonaffine displacement field than do strain-driven surface STZs, which is characterized by a larger drop in potential energy resulting from STZ nucleation that is enabled by the relative compliance of the surface as compared to the bulk.

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Strain-Rate and Temperature Dependence of Yield Stress of Amorphous Solids via Self-Learning Metabasin Escape Algorithm

P. Cao, X. Lin and H.S. Park
Journal of the Mechanics and Physics of Solids 2014; 68:239-250

Abstract

A general self-learning metabasin escape (SLME) algorithm (Cao et al., 2012) is coupled in this work with continuous shear deformations to probe the yield stress as a function of strain rate and temperature for a binary Lennard-Jones (LJ) amorphous solid. The approach is shown to match the classical molecular dynamics (MD) results at high strain rates where the MD results are valid, but, importantly, is able to access experimental strain rates that are about ten orders of magnitude slower than MD. In doing so, we find in agreement with previous experimental studies that a substantial decrease in yield stress is observed with decreasing strain rate. At room temperature and laboratory strain rates, the activation volume associated with yield is found to contain about 10 LJ particles, while the yield stress is as sensitive to a 1.5Tg increase in temperature as it is to a one order of magnitude decrease in strain rate. Moreover, our SLME results suggest the SLME and extrapolated results from MD simulations follow distinctly different energetic pathways during the applied shear deformation at low temperatures and experimental strain rates, which implies that extrapolation of the governing deformation mechanisms from MD strain rates to experimental may not be valid.

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Strain-Rate and Temperature-Driven Transition in the Shear Transformation Zone for 2D Amorphous Solids

P. Cao, H.S. Park and X. Lin
Physical Review E 2013; 88:042404

Abstract

We couple the recently developed self-learning metabasin escape algorithm, which enables efficient exploration of the potential energy surface (PES), with shear deformation to elucidate strain-rate and temperature effects on the shear transformation zone (STZ) characteristics in two-dimensional amorphous solids. In doing so, we report a transition in the STZ characteristics that can be obtained either through increasing the temperature, or decreasing the strain rate. The transition separates regions having two distinct STZ characteristics. Specifically, at high temperatures and high strain rates, we show that the STZs have characteristics identical to those that emerge from purely strain-driven, athermal quasistatic atomistic calculations. At lower temperatures and experimentally-relevant strain rates, we use the newly coupled PES + shear deformation method to show that the STZs have characteristics identical to those that emerge from a purely thermally activated state. The specific changes in STZ characteristics that occur in moving from the strain-driven to thermally-activated STZ regime include a 33% increase in STZ size, faster spatial decay of the displacement field, a change in deformation mechanism inside the STZ from shear to tension, a reduction in the stress needed to nucleate the first STZ, and finally a notable loss in characteristic quadrupolar symmetry of the surrounding elastic matrix that has previously been seen in athermal, quasistatic shear studies of STZs.

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Self-Learning Metabasin Escape Algorithm for Supercooled Liquids

P. Cao, M. Li, R.J. Heugle, H.S. Park and X. Lin
Physical Review E 2012; 86:016710

Abstract

A generic history-penalized metabasin escape algorithm that contains no predetermined parameters is presented in this work. The spatial location and volume of imposed penalty functions in the configurational space are determined in self-learning processes as the 3N-dimensional potential energy surface is sampled. The computational efficiency is demonstrated using a binary Lennard-Jones liquid supercooled below the glass transition temperature, which shows an O(103) reduction in the quadratic scaling coefficient of the overall computational cost as compared to the previous algorithm implementation. Furthermore, the metabasin correlation lengths in these supercooled liquids are obtained as a natural consequence of determining the self-learned penalty function width distributions. In the case of a bulk binary Lennard-Jones liquid at a fixed density of 1.2, typical metabasins are found to contain about 148 particles while having a correlation length of 3.09 when the system temperature drops below the glass transition temperature.

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