Inherent structures of phase-separating binary mixtures: Nucleation, spinodal decomposition, and pattern formation

Abstract

An energy landscape view of phase separation and nonideality in binary mixtures is developed by exploring their potential energy landscape (PEL) as functions of temperature and composition. We employ molecular dynamics simulations to study a model that promotes structure breaking in the solute-solvent parent binary liquid, at low temperatures. The PEL of the system captures the potential energy distribution of the inherent structures (IS) of the system and is obtained by removing the kinetic energy (including that of intermolecular vibrations). The broader distribution of the inherent structure energy for structure breaking liquid than that of the structure making liquid demonstrates the larger role of entropy in stabilizing the parent liquid of the structure breaking type of binary mixtures. At high temperature, although the parent structure of the structure breaking binary mixture is homogenous, the corresponding inherent structure is found to be always phase separated, with a density pattern that exhibits marked correlation with the energy of its inherent structure. Over a broad range of intermediate inherent structure energy, bicontinuous phase separation prevails with interpenetrating stripes as signatures of spinodal decomposition. At low inherent structure energy, the structure is largely phase separated with one interface where as at high inherent structure energy we find nucleation type growth. Interestingly, at low temperature, the average inherent structure energy (<E{IS}>) exhibits a drop with temperature which signals the onset of crystallization in one of the phases while the other remains in the liquid state. The nonideal composition dependence of viscosity is anticorrelated with average inherent structure energy.

Composition dependent non-ideality in aqueous binary mixtures as a signature of avoided spinodal decomposition

“…41 We have reported several highly interesting results. We have found a correlation between the energy of the IS of the binary mixture and the microscopic mode of phase separation in the IS.…”

“…For model I, the average inherent structure energy (< E IS >) shows a minimum at solute composition x B 0.4. In our previous study, 41 we presented the calculation of viscosity with respect to mole fraction. The value of viscosity shows a maximum at the solute composition x B 0.4.…”

“…In a recent study 41 we have shown the variation of the order parameter [C(r)] with position. The difference in mole fractions between solvent and solute [C(r)] with respect to position has been shown to be oscillatory in nature to quantify the signature of spinodal decomposition in the same study.…”

Community detection for networks with unipartite and bipartite structure

“…We compare our algorithm with the label propagation algorithm for bipartite networks (LPAb) [11] and a spectral algorithm based on singular value decomposition [12]; both of which are state-of-the-art algorithms that can find community structure in bipartite networks. LPAb is based on a label propagation algorithm (LPA) [43], which assigns unique labels to nodes and repeatedly updates the label of each vertex by assigning the most frequent labels of its neighbors until it meets the terminal condition.…”

“…Community structure, or network modules, has become a fruitful topic in fields such as physics, mathematics, biology, and social science [1]. To date, most algorithms focusing on this problem operate on either unipartite [2][3][4][5][6][7] or bipartite networks [8][9][10] and some can handle both [11,12] (reviewed in [1,13]). A unipartite network consists of a vertex set and an edge set that join pairs of vertices.…”