Issue 19, 2019, Issue in Progress

Temperature and initial composition dependence of pattern formation and dynamic behavior in phase separation under deep-quenched conditions

Abstract

Phase separation of SCN-H2O ([CH2CN]2–H2O) transparent solutions is simulated in two dimensions and the effects of quenching temperature and initial composition on the pattern formation and dynamic behavior of the second phase are examined via Minkowski functionals. The simulation is based on model H where the molar free energy of the SCN-H2O solution is obtained by the CALPHAD approach. We find that the composition and temperature do not affect the exponent in the domain growth law, where the average domain size with time yields R(t)–tn. However, they influence the pattern formation and dynamic behavior of the second phase in phase separation. Lower temperature leads to a finer bicontinuous structure in spinodal decomposition and promotes the nucleation rate, which accelerates the phase separation and results in more liquid droplets with smaller size. As the initial composition diverges from the critical value, the spatial patterns change gradually from bicontinuous into a droplet-like structure. When the initial composition is closer to the critical value, for spinodal decomposition, the diffusion-driven growth lasts for a longer time and the average domain size of liquid droplets is larger. For nucleation-driven growth, in contrast, the single phase separates more quickly and the average size of liquid droplets is smaller.

Graphical abstract: Temperature and initial composition dependence of pattern formation and dynamic behavior in phase separation under deep-quenched conditions

Article information

Article type
Paper
Submitted
13 Feb 2019
Accepted
23 Mar 2019
First published
05 Apr 2019
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2019,9, 10670-10678

Temperature and initial composition dependence of pattern formation and dynamic behavior in phase separation under deep-quenched conditions

L. Zhang, Y. Peng, L. Zhang, X. Lei, W. Yao and N. Wang, RSC Adv., 2019, 9, 10670 DOI: 10.1039/C9RA01118H

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