Mechanics and Materials


Mesoscale & Continuum Modeling

Future research in Mesoscale and Continuum Modeling will focus on challenging problems in nanoscience and mathematical geophysics, mainly in the (a) Modeling and simulation for the generation and control of optical beams, with applications in particle manipulation, filamentation, micromachining, and propagation in turbulent environments, (b) Investigation of the valley degree of freedom in the dynamics of optical waves in photonic graphene and investigation of the interaction between multimodal behavior and nonlinearity in different systems which are important for nanotechnological applications, (c) Investigation of a variety of skyrmionic textures with the aim to show that rich and diverse static and dynamical behaviour can be supported by a single model for DM materials. Understanding dynamics in these models is important for the development of a single technology combining storage and transmission of information using magnetic materials, that could exceed the limitations of current information technologies, (d) Investigation of inverse scattering for the wave equations by employing Gaussian beams and other wave packets for the construction of dynamic NtD maps, and application to the near-boundary medium determination problems in seismology and acoustics (e) Study of the inverse problems for non-homogeneous acoustic and elastic waveguides with new imaging functionals such as quantum fidelity and Loschmidt echo, by exploiting aspects of chaotic ray dynamics.

Molecular Modeling

The team for Molecular Dynamics is working on the development of novel mathematical and computational methods for the study of molecular systems/materials across multiple length and time scales, and combines these methods with statistical analysis and data mining approaches.  The following research directions are pursued: (a) Development of mathematical methodologies for obtaining coarse-grained (CG) models for molecular systems at non-equilibrium conditions, e.g. under shear flow.  (b) Extension of variational inference path-space methods for obtaining CG models via data mining and machine learning methodologies and application of the new CG models in molecular systems at equilibrium and non-equilibrium conditions. (c) Study of polymer nanocomposites via hierarchical multi-scale simulation approaches. (d) Prediction of the properties of graphene sheets in graphene-based polymer nanocomposites. (e) Study biomolecular systems (peptides, proteins) via molecular dynamics simulations and bioinformatics approaches. It is a strategic Extend existing synergies with other groups from outside Greece, as well as with research teams at FORTH, for combining different simulation methods, and/or simulations with experiment, in order to provide a fundamental understanding of materials behaviour.