• Funding boost for Soft Matter Simulation Centre
    Multiscale methods can be used to track and understand the formation of complex network structures during phase separation of macromolecules in solution. Credit: Burkhard Dünweg (MPI-P) and Maria Lukacova (JGU)

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Funding boost for Soft Matter Simulation Centre

The German Research Foundation (DFG) has approved a further four-years of funding for the joint Collaborative Research Center/Transregio 146 on Multiscale Simulation Methods for Soft Matter Systems, overseen by Johannes Gutenberg University Mainz (JGU), TU Darmstadt, and the Max Planck Institute for Polymer Research. Established in 2014, researchers from multi-discipline backgrounds will continue developing fundamental methods for computer-aided simulation of soft matter, ranging from plastics, rubber, paper, oils and liquid crystals to biological membranes and proteins.

Professor Friederike Schmid of the Institute of Physics at Mainz University said: "If we want to better understand the behavior of these materials, this will only be practicable with the help of multiscale approaches, meaning we need to look at what is happening on a range of different scales simultaneously."

He emphasized that the properties of many materials cannot be understood by studying their structure and dynamics at just one size and time scale; for example, materials can eventually fail after years because of what happens on the atomic scale. Soft matter is therefore an ideal testing ground for developing new multiscale algorithms and analysing properties from a mathematical perspective.

"The JGU Institute of Mathematics has made important contributions to our fundamental understanding here, while computer science is fostering the development of computer simulations with the help of machine learning methods," Schmid pointed out, highlighting the advantages of interdisciplinary collaboration with a clearly established basis in physics and mathematics.

Three main goals have been set for this third and final funding period. Firstly, the researchers intend to further improve their fundamental techniques, which are now focused in particular on non-equilibrium and inhomogeneous systems. Secondly, they aim to consolidate results to date by testing the new algorithms in a broader class of model systems. And thirdly, they will apply the new methods to a series of challenging real-world problems they have identified.

"We have already achieved a lot, but we still have a long way to go", said Schmid. The long-term goal is to establish routine use of the multiscale techniques so that real-world applications for soft materials can be simulated. "We want to be able to make predictions on how the properties of materials will perform and suggestions on how to actually improve these. In the case of biological substances, we are interested in deciphering and precisely understanding the processes involved," Schmid concluded.

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