Predicting twinning stress in fcc metals: Linking twin-energy pathways to twin nucleation

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Understanding martensite and twin formation in austenitic steels: A model describing TRIP and TWIP effects (2017, neutral): “…1(b)); the thickness t i of a stacking fault is typically 100 nm [3,12]. iii ) A number of stacking faults n i ( n (cid:15) = 1 [24] and n t = 3 [8]) overlap in adjacent { 111 } planes to form an embryo with a critical width r ∗ i and length l ∗ i ; this process aids in reducing the excess…”
Physically informed artificial neural networks for atomistic modeling of materials (2018, neutral): “[69] S.”
Probing deformation mechanisms of a FeCoCrNi high-entropy alloy at 293 and 77 K using in situ neutron diffraction (2018, background): “creates an intrinsic stacking fault, and continuous passage of the partial dislocations on 234 successive (111) planes creates multi-layer faults forming twin nucleuses; in the end 235 larger twins can be formed by passage of more partials on neighbouring (111) planes 236 [43].”
Ab initio modeling of dislocation core properties in metals and semiconductors (2017, neutral): “Sources for DFT data are: a [48], b [101], c [102], d [36], e [103], f [104], g [105], h [106], i [107], j [108], k [100].”
Slip nucleation in single crystal FeNiCoCrMn high entropy alloy (2016, methodology): “A relaxation scheme utilized in our previous work (atoms are allowed to adjust their positions normal to the fault plane [24]) ensured correct energy values aswell.”