| Details: |
Soft matter systems include a wide variety of materials such as amorphous materials, polymers, glass-forming liquids, colloids, organic polymorphs, liquid crystals etc. Their properties are largely governed by the interplay between the entropic and enthalpic contributions. In this talk I will first discuss the structure-dynamics relationship in a model glass-forming liquid, precisely, the role of entropy and structural correlations in determining the dynamics [1]. Next, I will focus on the theoretical approaches to predict crystal polymorphism. Similar to the glasses, organic molecules with multiple polymorphs — stable crystalline phases — also exhibit complex structure-property relationships. Depending on the processing conditions (e.g., rate of cooling, nature of solvent, pressure and temperature), different polymorphs of a specific system could be stabilised experimentally. However, understanding the mechanism of solid-solid phase transformation among different polymorphs is challenging. Rapid developments have been made to understand the pathways for polymorphic transitions of small organic molecules using advanced computational techniques [2], however, detailed studies on polymer crystal polymorphism are still limited. Enhanced sampling methods often need prior knowledge of order parameters that can resolve the relevant transition pathways, typically identified through physical or chemical expertise [3]. Lastly, I will focus on my recent research on applying data-driven methods to characterise polymer crystals and study glass transition. Recently, data-driven methods have attracted considerable attention for learning the order parameters without significant a priori insights. We used different dimensionality reduction methods to project the complex high dimensional landscape of polymer crystal phases to a lower-dimensional embedding [4]. We also applied data-driven methods to predict the glass transition temperatures for polymer melts [5]. One of the advantages of using these data-driven methods is that they do not require the incorporation of excessive system-specific intuition and therefore demonstrate good transferability properties.
[1] A Banerjee, S Sengupta, S Sastry, SM Bhattacharyya, Phys. Rev. Lett. 113, 225701(2014)
[2] A. Banerjee, D. Jasrasaria, S. P. Niblett, and D. J. Wales, J. Phys. Chem. A,125, 3776 (2021)
[3] C. Liu, J. G. Brandenburg, O. Valsson, K. Kremer,, T. Bereau, Soft Matter 16, 9683 (2020)
[4] A. Banerjee, Y Varolgüneş ,T Bereau, J F Rudzinski (manuscript in preparation)
[5] A. Banerjee, H.-P. Hsu, K. Kremer, O. Kukharenko (manuscript in-preparation)
|