Stress-dependence of generalized stacking fault energies

Abstract

The energy associated with shearing of planes of atoms in a crystal is the generalized stacking 10 fault energy (GSFE). It is a crucial material property for describing nanoscale plasticity phenomena in crystalline materials, such as dislocation dissociation, nucleation, and twinning. The dependence of the GSFE on applied stress normal to the stacking fault has been suggested to influence such phenomena. Here, the stacking fault stress dependence is analyzed through (i) the generalized stacking fault potential energy (GSFE) and (ii) the generalized stacking fault enthalpy (GSFH). At an 15 imposed shear displacement, there is also an associated inelastic inter-planar normal displacement around the fault. Extensive molecular statics simulations with interatomic potentials and/or first principle calculations in Ni, Cu, Al and Mg reveal that GSFE and inelastic normal displacement both increase with tensile stress. An increasing GSFE contradicts long-standing wisdom and previous studies. Positive inelastic normal displacement coupled to the applied normal stress decreases the 20 GSFH, but is not useful for general mechanics problems. The existence of the inelastic displacement can lead to incorrect measurements of the GSFE and GSFH in finite systems loaded by an applied strain. Application of the GSFE and the inelastic normal displacement to both fcc dissociation distance versus applied normal stress and crack tip dislocation emission under mixed Mode II/I loading show very good agreement with direct simulations. In general, "opening softening" effects 25 are not universal, and so the analysis of any particular nanomechanics problem requires precise implementation of the combination of GSFE and inelastic normal displacement rather than the GSFH.

Effects of Alloying Elements on the Stacking Fault Energies of Ni58Cr32Fe10 Alloys: A First-Principle Study

“…They reported that the addition of 1.4 at.% Ti (the solute construction on the doped plane is 8.3 at.%) only achieves a reduction of~19 mJm −2 [16]. We suggest that the SFE (61.0 mJm −2 ) of Alloy 690 reported by Jimy et al might be overestimated, because the experimental values of SFE might be influenced by residual stress, which arises from the sample preparation process [15].…”

“…Experimental measurements of SFE require delicate techniques. Moreover, the experimental values of SFEs might be influenced by residual stress, which arises from the sample preparation process [15]. Fortunately, first-principle studies based on density functional theory (DFT) have been considered as effective computational methods to calculate the SFE.…”

Effect of sub-surface hydrogen on intrinsic crack tip plasticity in aluminium

“…These 8 rows roughly correspond to the size of the core of the partial dislocation as seen on the slip distributions on Figure 3(b), which is coherent. In a recent paper [42], some crack simulations were done which show no effect of mode I in Cu and Ni. The data in Al (Figure 12 of [42], before emission occurs in a different plane than at low mode I) is coherent with Table 1, in the sense that a moderate decrease is observed, of the order of 10%, even if the crack tip has a different shape than the one considered here.…”

“…In a recent paper [42], some crack simulations were done which show no effect of mode I in Cu and Ni. The data in Al (Figure 12 of [42], before emission occurs in a different plane than at low mode I) is coherent with Table 1, in the sense that a moderate decrease is observed, of the order of 10%, even if the crack tip has a different shape than the one considered here. Concerning the absence of effect in Cu and Ni, their enthalpy calculations show indeed that the decrease in g enthalpy us due to a transverse traction is lower in Cu and Ni than in Al, so maybe this is the reason why the effect does not show up in the simulations in Cu and Ni.…”

Σ3 grain boundary dynamics studied by atomistic spherical bicrystal modeling

“…The atomic interactions of the aluminum atoms are modeled in LAMMPS [8], using the Mishin-Farkas embedded-atom method (EAM) interatomic potential [9]. The potential has been validated previously and found to be in excellent agreement with physical properties, including the generalized stacking fault energy curve [10]. The visualizations were generated using Ovito [11].…”