Coarse-Graining Strategies and Methodologies for Polymeric and Biomolecular Assemblies - Launching event of the CFCAM-RA Node
CFCAM-RA, Centre Blaise Pascal, Lyon, France
Over the past two decades, the study of complex fluids, exemplified here for the case of polymer or biomolecular solutions and melts, has attracted the interest of scientists across a broad spectrum of disciplines, in the experimental, theoretical and simulation contexts. Complex fluids present intriguing self-assembling properties, and therefore rich phase diagrams that are widely explored experimentally, e.g. in the case of diblock copolymers ; from a theoretical point of view, complex fluids are characterised by a high number of competing microscopic interactions, including many-body forces. In principle, to fully describe such systems, it is necessary to properly account for the elementary interactions between the constituent building blocks of the macromolecules. Numerical simulations that take into account all the microscopic forces, i.e. fully atomistic simulations will in principle provide accurate descriptions of the real systems. However, they are strongly limited by the computational resources available that usually do not allow to reach mesoscopically and macroscopically relevant size and time scales.
Out of the aforementioned limitations, the need arises to introduce simplified but efficient and accuratee descriptions, which allow us to reproduce the main features of the systems, circumventing the need of a full atomistic description that would be theoretically and computationally prohibitive. The workshop will give an overview of the state of the art of coarse-graining strategies by bringing together researchers from the different fields involved, from experimentalists to theoreticians.
Christos N. Likos ( University of Vienna ) - Organiser
Vincent Krakoviack ( Ecole normale supérieure de Lyon ) - Organiser
Barbara Capone ( Università degli Studi Roma Tre ) - Organiser & speaker
Jean-Pierre Hansen ( University of Cambridge ) - Organiser