Abstract
Dislocations are the carriers of plasticity in crystalline materials. Their collective interaction behavior is dependent on the strain rate and sample size. In small specimens, details of the nucleation process are of particular importance. In the present work, discrete dislocation dynamics (DDD) simulations are performed to investigate the dominant yielding mechanisms in single crystalline copper pillars with diameters ranging from 100 to 800 nm. Based on our simulations with different strain rates and sample size, we observe a transition of the relevant nucleation mechanism from “dislocation multiplication” to “surface nucleation”. Two physics-based analytical models are established to quantitatively predict this transition, showing a good agreement for different strain rates with our DDD simulation data and with available experimental data. Therefore, the proposed analytical models help to understand the interplay between different physical parameters and nucleation mechanisms and are well suitable to estimate the material strength for different material properties and under given loading conditions.
Highlights
Dislocations are the carriers of plasticity in crystalline materials
This affects the dominant nucleation process when the sample dimensions decrease: in the case of low strain rates, both transmission electron microscopy (TEM) observations[12,13] and discrete dislocation dynamics (DDD)[14,15] revealed that for large micrometer-sized samples dislocations are mainly nucleated through Frank-Read source mechanisms, while for samples on the sub-micrometer scale nucleation happens rather by so- called “single-arm sources” (SAS), i.e. a dislocation segment which is pinned inside the sample that terminates on the sample surface
We started by performing DDD simulations to investigate the influence of sample size, strain rate and equilibrium dislocation density on the mechanisms responsible for the evolution of the dislocation microstructure in single crystalline sub-micrometer pillars
Summary
Dislocations are the carriers of plasticity in crystalline materials. Their collective interaction behavior is dependent on the strain rate and sample size. In this paper, based on DDD simulations of different sample sizes and strain rates, we propose and extend analytical models that can describe SAS and SN.
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