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Invited speakers

Hartmut Löwen (University of Düsseldorf) (13:35-14:05)
Inertial active soft matter
Active particles which are self-propelled by converting energy into mechanical motion represent an expanding research realm in physics and chemistry. For micron-sized particles moving in a liquid (``microswimmers'), most of the basic features have been described by using the model of overdamped active Brownian motion. However, for macroscopic particles or microparticles moving in a gas, inertial effects become relevant such that the dynamics is underdamped. Therefore, recently, active particles with inertia have been described by extending the active Brownian motion model to active Langevin dynamics which includes inertia. In this talk, recent developments of active particles with inertia (``microflyers', ``hoppers' or ``runners') are summarized including: inertial delay effects between particle velocity and self-propulsion direction, the influence of inertia on motility-induced phase separation and the cluster growth exponent, Langevin rockets and the formation of active micelles (“rotelles”) by using inertial active surfactants.
Lisa Tran (Utrecht University) (14.55-15.20)
The geometrical control of topological defects in synthetic and bio-derived liquid crystals
Liquid crystals are everywhere around us – in our screens but also in the natural world. They are a phase of matter most famous for their application in the display industry, a testament to their utility. They can be manipulated with electric fields, can alter light, and are elastic – all characteristics necessary for engineering a pixel. Despite these technological advances, the structures formed by liquid crystals and their influence on macroscopic properties remain to be elucidated.

Since liquid crystal molecules order with one another, they respond to the system geometry. Geometrical constraints can generate patterns and defects – localized, “melted” areas of disorder that can lower the overall distortion in the system. I will present recent work where defects in synthetic liquid crystals are controlled using microfluidics to generate liquid crystal double emulsions – confining the liquid crystal into spherical shells. Defect types and their configurations are tunable with the system geometry and by varying the molecular alignment. These tools can be applied to pattern nanoparticles at the liquid crystal interface. I will end by discussing future research directions, where geometrical confinement and controlled alignment can be leveraged to design bio-inspired materials.

Mehdi Habibi (Wageningen University) (15.20-15.45)
Material design, from ordered to disordered structures
Ordered structures designed by repeating a unit-cell in a lattice of specific symmetry have recently attracted much interest for designing materials with peculiar mechanical properties. The ordered lattice structure provides opportunities for bottom-up programming mechanical responses that are very hard to tune in conventional materials. However, ordered structures are often constrained by strict geometric relationships, which can be violated due to defects and strongly hindering their mechanical functionality in real-world applications. In contrast to ordered structures, crumpled structures are inherently insensitive to imperfection and defect in their disordered morphology. Crumpled systems also exhibit interesting properties that can be used to tailor their mechanical response. In my talk, first I start with two ordered meta-structures studied in my research group and explain how we can program the normal force response or curvature in those ordered meta-structures. Then I introduce crumpling-based metamaterials and crumpled Origami structures with low sensitivity to defects and imperfection as robust methods of material design for real-world applications. I will address how to tailor the mechanical properties and morphology of the random crumpled structure by the dimensionality of the confinement, friction and ductility of the material.
Tristan Bereau (University of Amsterdam) (16.15-16.40)
Data-driven multiscale simulations of soft matter
Advanced statistical methods are rapidly impregnating many scientific fields, offering new perspectives on long-standing problems. Machine learning, but more broadly data-intensive methodologies help develop computer simulations into new avenues. I will outline two research areas where data-driven methods link closely to molecular simulations: Motivated by the recent acceleration of materials discovery in hard condensed matter by high-throughput quantum calculations, we are developing analogous methods for soft materials, targeting nano and mesoscales. To this end, we make use of multiscale molecular simulations to screen compounds at high throughput. In particular, we take advantage of the transferability of coarse-grained models to reduce the size of chemical compound space. Applications on drug-membrane permeability will be presented. The second research area links to statistical reweighting of computer simulations. Statistical reweighting techniques offer the means to predict static and dynamical properties to different equilibrium state points. I will present an extension of these methods to nonequilibrium steady states. We use a maximum path entropy formalism, subject to physical constraints, including relations from stochastic thermodynamics.