Öffentliche Seminare

Gels with thermoreversible physical crosslinks show great promise for designing materials with tuneable rheology and self-healing properties. However, many questions remain to be answered before the goal of tailoring a gel’s macroscopic properties by controlling molecular scale parameters, can be achieved. We show that considerable progress in this direction can be made by examining the behaviour of physical gels near the gel transition with the help of Brownian dynamics simulations. Due to the scale-free and semidilute character of critical gels, fully capturing their structure and dynamics requires the inclusion of associative interactions between sticky monomers, solvent-mediated hydrodynamic interactions between all the monomers in a large simulation volume, and time scales spanning several orders of magnitude. We have adapted Jim Swans’ algorithm for the efficient computation of hydrodynamic interactions in colloids to polymer chains, making the simulation of the dynamics of physical gels at the transition point tractable for the first time. Rheological properties such as the zero-shear viscosity and relaxation modulus are investigated systematically as functions of polymer concentration and binding energy between associative sites. We show the structural emergence of a gel as a power law distribution of chain cluster sizes, indicating a divergence of the average cluster size. It is shown that a system-spanning network can form regardless of binding energy at sufficiently high concentration. However, the contribution to the stress sustained by this physical network can decay faster than other relaxation processes, even single chain relaxations. If the polymer relaxation time scales overlap with short-lived associations, the mechanical response of a gel becomes “evanescent”, decaying before it can be rheologically observed, even though the network is instantaneously mechanically rigid. In our simulations, the concentration of elastically active chains and the dynamic moduli are computed independently. This makes it possible to combine structural and rheological information to identify the concentration at which the sol-gel transition occurs as a function of binding energy. Further, it is shown that the competition of scales between the sticker dissociation time and the single-polymer relaxation time determines if the gel is in the evanescent regime. Finally, we compare the prediction of the concentration at the sol-gel transition by a variety of different static and dynamic signatures of gelation. [mehr]

I will present techniques to find reaction coordinates to be used in conjunction with free energy biasing techniques such as the adaptive biasing force method. This allows for instance to improve the sampling of configurations of complex proteins. However, reaction coordinates are often based on an intuitive understanding of the system, and one would like to complement this intuition or even replace it with automated tools. One appealing tool is autoencoders, for which the bottleneck layer provides a low dimensional representation of high dimensional atomistic systems. I will discuss some mathematical foundations of this method, and present illustrative applications including alanine dipeptide. Some on-going extensions to more demanding systems, namely HSP90, will also be mentioned by Zineb Belkacemi, the PhD student working on this project. [mehr]

Parallel computing has developed as a central tool in scientific computing to solve large scale problems involving huge number of degrees of freedom, complex geometries or coupled applications. The parallel efficiency is key for estimating to which degree the computational resources are used, or whether there is still potential to speed up an application by organising data or workflow in a different way across processors. To reduce the wall clock time of an application, a goal might be to use as many processors of a parallel architecture as possible. However, scalability of a parallel application depends on a number of characteristics, among which is efficient communication, equal distribution of work or efficient data layout.Many parallel applications, especially particle or mesh based algorithms like Molecular Dynamics or Lattice Boltzmann methods, are implemented by domain decomposition techniques, where processors administrate certain geometrical regions of a physical system. In such cases, unequal work load in the processor network is to be expected when particles are not distributed homogeneously or the computation cost of particle interactions is not equal in each part of the system. Also in the case where heterogeneous architecture components are coupled together in a complex cluster network (e.g. CPU-GPU, different types of CPUs or different network speeds) wall clock times for solving a problem with the same number of degrees of freedom will vary across the parallel application. For these scenarios the code has to decide how to redistribute the work among processes according to a work sharing protocol or to dynamically adjust computational domains, to balance the workload.In the seminar, I will give an introduction to the problem of load balancing and discuss various methods to redistribute data or re-organise the domain decomposition to improve and optimise the work load and to improve parallel efficiency and scalability. As an outlook I will discuss developments from the European Centre of Excellence E-CAM, where different methods have been implemented into a library, which can be used in community codes. [mehr]