Final Report Summary - NANOPOLY (Hybrid Models for Tailoring Nano-Architectures of polymers)
NANOPOLY’s research training thus was focussed on the creation of a new generation of researchers that are trained in mathematical modelling and software design, as well as polymer process design. NANOPOLY gave its fellows vital training in complementary research fields: The training was composed out of a mix of competences in mathematical modelling, software engineering, polymer chemistry and process design that in each segment came from experts in these disciplines and provided insight into the most recent research in this disciplines while at the same time being tailored to the overall project goals and industrial needs. NANOPOLY’s success in this regard should be measured by the outcome: The early stage researchers (ESRs) trained in the network on average already published three articles in international high-quality science journals; almost a dozen PhD theses have already been or will soon be submitted by the ESRs of the network, their presentation at international polymer conferences earned several student prizes, and the graduates of NANOPOLY have advanced their careers and found distinguished postdoc positions, assistant professorships, or permanent positions in research and development in European polymer industry. This new generation of researchers will carry the momentum build-up in the network into the future.
The network’s research was focussed on the creation of novel stochastic-deterministic hybrid models and associated efficient software tools for in silico studies of effects of nano-architectures on polymerisation processes and polymeric materials. Resulting advanced simulation tools now permit to understand branching/crosslinking statistics in polymer networks including, for example, cyclization effects and material properties of gels etc and how to influence such properties by rational production process design.
In the initial phase the network concentrated on benchmarking new models and simulation tools using experimental results for the model system Styrene/Divinyl Benzene. By continued benchmarking advanced hybrid models for network formation for advanced materials have been developed, associated algorithms have partially been integrated into the commercial software platform PREDICI while obtained results were validated with newly gathered experimental data. The new tools will be further employed in cooperation between research and business units, e.g. in BASF, regarding the transfer of knowledge into business.