2019
DOI: 10.3390/ma12091548
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Generalized Stacking Fault Energy of {10-11}<11-23> Slip System in Mg-Based Binary Alloys: A First Principles Study

Abstract: In this work, the generalized stacking fault energies (GSFEs) of {10-11}<11-23> slip system in a wide range of Mg-X (X = Ag, Al, Bi, Ca, Dy, Er, Gd, Ho, Li, Lu, Mn, Nd, Pb, Sc, Sm, Sn, Y, Yb, Zn and Zr) binary alloys has been studied. The doping concentration in the doping plane and the Mg-X system is 12.5 at.% and 1.79 at.%, respectively. Two slip modes (slip mode I and II) were considered. For pure magnesium, these two slip modes are equivalent to each other. However, substituting a solute atom into th… Show more

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Cited by 9 publications
(3 citation statements)
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“…[ 16–18 ] Many studies on the GSFE of binary alloys have used the density functional theory (DFT). [ 19–21 ] Ding et al [ 1,19 ] studied the GSFE of basal < a >, prismatic (prism) < a >, pyramidal I (Py‐I) < a >, Py‐I < c + a >, and pyramidal II (Py‐II) < c + a > slip systems. The results showed that the activation of Py‐II slip had a significant role in plasticity.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…[ 16–18 ] Many studies on the GSFE of binary alloys have used the density functional theory (DFT). [ 19–21 ] Ding et al [ 1,19 ] studied the GSFE of basal < a >, prismatic (prism) < a >, pyramidal I (Py‐I) < a >, Py‐I < c + a >, and pyramidal II (Py‐II) < c + a > slip systems. The results showed that the activation of Py‐II slip had a significant role in plasticity.…”
Section: Introductionmentioning
confidence: 99%
“…(DFT). [19][20][21] Ding et al [1,19] studied the GSFE of basal <a>, prismatic (prism) <a>, pyramidal I (Py-I) <a>, Py-I <c þ a>, and pyramidal II (Py-II) <c þ a> slip systems. The results showed that the activation of Py-II slip had a significant role in plasticity.…”
Section: Introductionmentioning
confidence: 99%
“…It is worth mentioning that it is beyond the scope of the present work to build a predictive ML model to calculate stacking fault energy as a function of composition. However, the presently suggested descriptors are one of the fundamentals to build this ML model in addition to collecting and analyzing the values of stacking fault energy in the present work and especially in the literature, for example [35,[41][42][43][44][45][46][47][48][49][50].…”
Section: Introductionmentioning
confidence: 99%