Mechanics and Materials
AREAS
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.