Dynamic heterogeneity in polydisperse systems: a comparative study of the role of local structural order parameter and particle size
Title | Dynamic heterogeneity in polydisperse systems: a comparative study of the role of local structural order parameter and particle size |
Publication Type | Journal Article |
Year of Publication | 2023 |
Authors | Patel, P, Sharma, M, Bhattacharyya, SMaitra |
Journal | Journal of Chemical Physics |
Volume | 159 |
Issue | 4 |
Pagination | 044501 |
Date Published | JUL |
Type of Article | Article |
ISSN | 0021-9606 |
Abstract | In polydisperse systems, describing the structure and any structural order parameter (SOP) is not trivial as it varies with the number of species we use to describe the system, M. Depending on the degree of polydispersity, there is an optimum value of M = M-0 where we show that the mutual information of the system increases. However, surprisingly, the correlation between a recently proposed SOP and the dynamics is highest for M = 1. This effect increases with polydispersity. We find that the SOP at M = 1 is coupled with the particle size, s, and this coupling increases with polydispersity and decreases with an increase in M. Careful analysis shows that at lower polydispersities, the SOP is a good predictor of the dynamics. However, at higher polydispersity, the dynamics is strongly dependent on s. Since the coupling between the SOP and s is higher for M = 1, it appears to be a better predictor of the dynamics. We also study the Vibrality, an order parameter independent of structural information. Compared to SOP, at high polydispersity, we find Vibrality to be a marginally better predictor of the dynamics. However, this high predictive power of Vibrality, which is not there at lower polydispersity, appears to be due to its stronger coupling with s. Therefore, our study suggests that for systems with high polydispersity, the correlation of any order parameter and s will affect the correlation between the order parameter and dynamics and need not project a generic predictive power of the order parameter. |
DOI | 10.1063/5.0156794 |
Type of Journal (Indian or Foreign) | Foreign |
Impact Factor (IF) | 4.4 |
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