(Truly) Multiscale Simulations of Polymer Crystallization
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Understanding the crystallisation of polymers is crucial to improve their functional properties. For instance, the strength-to-weight ratio of Kevlar depends on its degree of crystallinity, which impacts its usage in composite materials such as F1 chassis. However, the current theoretical frameworks for the crystallisation kinetics of polymers suffer from severe limitations when dealing with non-isothermal conditions or the presence of nucleating agent. This project seeks to break new ground by using multi-scale simulations (from molecular dynamic simulations to lattice models) to build a machine learning model for predicting the non-isothermal crystallisation of heterogeneous polymer mixtures. |
Gabriele C. Sosso, Dr. Lukasz Figiel |
New foundations for electrochemical-mechanical coupling via multiscale simulations
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In-service performance of functional materials for energy storage-related applications depends on an intimate interplay between various physical-chemical processes, e.g. strain-dependent ionic transport in polymer electrolytes. Classical electrochemical-mechanical (ECM) models, used to predict the optimum performance of those materials, are based on ad hoc assumptions, omitting the origins of the ECM coupling at the nanoscale. Therefore, the ambition of this research project is to develop new foundations for a holistic computational modelling framework that rigorously captures the ECM coupling by bridging vastly different length scales via multiscale simulations of the material and machine learning. Particularly, the transport of charged species taking place in the presence of stress, electrostatic, and chemical potential gradients will be explored from nano to macro scale. |
Lukasz Figiel, Livia Bartok-Partay |
