2016
DOI: 10.1038/srep26625
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Degenerate seaweed to tilted dendrite transition and their growth dynamics in directional solidification of non-axially oriented crystals: a phase-field study

Abstract: We report the results of a phase-field study of degenerate seaweed to tilted dendrite transition and their growth dynamics during directional solidification of a binary alloy. Morphological selection maps in the planes of (G, Vp) and (ε4, Vp) show that lower pulling velocity, weaker anisotropic strength and higher thermal gradient can enhance the formation of the degenerate seaweed. The tip undercooling shows oscillations in seaweed growth, but it keeps at a constant value in dendritic growth. The M-S instabil… Show more

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Cited by 55 publications
(8 citation statements)
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“…Xing et al [17] revealed a degenerated seaweed growth in directional solidification of SCN-0.24 wt-% camphor alloy when the misorientation angle between the preferred crystal direction and temperature gradient is π/4; the results are qualitatively consistent with the numerical simulation of directionally solidified Mg-0.5 wt-% Al alloy by Amoorezaei et al [18] and the directionally solidified Mg-6wt-% Gd alloy by Wang et al [19]. Also, by means of the phase-field study of the directional solidification of Al-3 wt pct Cu alloy, they revealed that a higher thermal gradient is favourable for the morphology transition from tilted dendrite to degenerated seaweed [20].…”
Section: Introductionsupporting
confidence: 87%
See 1 more Smart Citation
“…Xing et al [17] revealed a degenerated seaweed growth in directional solidification of SCN-0.24 wt-% camphor alloy when the misorientation angle between the preferred crystal direction and temperature gradient is π/4; the results are qualitatively consistent with the numerical simulation of directionally solidified Mg-0.5 wt-% Al alloy by Amoorezaei et al [18] and the directionally solidified Mg-6wt-% Gd alloy by Wang et al [19]. Also, by means of the phase-field study of the directional solidification of Al-3 wt pct Cu alloy, they revealed that a higher thermal gradient is favourable for the morphology transition from tilted dendrite to degenerated seaweed [20].…”
Section: Introductionsupporting
confidence: 87%
“…Figure 7 shows the microstructural morphologies of Co- (20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32) at.-% Sn alloys directionally solidified at a temperature gradient of 300 K/cm and different withdrawal velocities. It can be seen that the alloy with eutectic composition can obtain complete regular lamellar eutectic structure at all withdrawal velocities, while the alloy with composition between 22-30 at.-% Sn can obtain a complete eutectic structure when the withdrawal velocities are relatively small.…”
Section: Microstructural Morphologies Of Co-sn Alloysmentioning
confidence: 99%
“…4D is the growth model of silver dendrites. In most cases of metal solidification and nano-synthesis, the formation of symmetric dendrites follows the classic crystallization in which atoms are the main building blocks for the growth of dendrites (Xing H. et al, 2016). If the silver dendrites are formed by a classic crystallization, a change on the reduction rate is expected to switch the classic crystallization to the non-classic mode, on the basis of the assumption in Fig.…”
Section: Resultsmentioning
confidence: 99%
“…This model in combination with a cubic anisotropy function was applied by Choudhury et al [27] to emulate the solidification in Fe-C. Due to a common idea that the driving force for a phase transformation is the difference in the grand potentials between phases, Choudhury and Nestler reformulated a multi-phasefield model based on the grand-potential functional [28] . Moreover, the anomalous interface effects were observed in several numerical investigations by using the phase-field model, when the interface width was extended artificially and the solute has unequal diffusivities between phases [29][30][31] . In order to eliminate these abnormal effects, an anti-trapping current was proposed into the diffusion equation by Karma [32] .…”
Section: Introductionmentioning
confidence: 98%