DYNAMIC MODELLING OF COMPLEX SYSTEMS AT NANOSCALE
Computer modelling represent fast and reliable tool for predicting the behaviour of complex systems and provides an indicative information for experimentalists during design and testing period. Nevertheless, complex systems contain large number of degrees of freedom that can span several length and time scales. This hamper the application of well-established models and modelling methods such as Monte Carlo or molecular dynamics. Instead, complex systems must be first coarse-grained and mapped to models on larger scales that contains phenomena of interest, fits nowadays methodologies and hardware sources. The aim of this thesis is to demonstrate the applicability of dynamic modelling on predicting the behaviour of complex systems which are here represented by composite materials that contain polymers, nanoparticles or gels and undergoes self-assembly or aggregation. Complex systems considered in this thesis are used many technological applications such as soft lithography, drug design or design of smart surfaces. Beside dynamic modelling methods, thesis shows importance of coarse-grained and mapping techniques for transforming the real system into computer model. Finally, achieved results shows usefulness of modelling when tailoring macroscopic behaviour of simulated systems with their microscopic structure, predicting their phase behaviour in multivariable space or under non-equilibrium conditions and in confined geometries.