4. Learning thermodynamic properties of materials
Spokesperson: Tristan Bereau (MPI for Polymer Research)
Though present in almost any product of our daily life and of being the materials all living things are made of, soft matter is by far less understood than traditional inorganic crystals. Over the years scientists and engineers developed a rather comprehensive operational knowledge, which is based on general physical principles, chemical insight, engineering experience and well defined work flows. However, the need for a structured and comprehensive database of soft matter material properties is imminent.
We plan to participate with two topics: (i) data mining of high-throuhgput databases in soft-matter and (ii) machine learning methodologies to efficiently calculate the stability of molecular crystal polymorphs
The individual project and members are the successive:
4.1. High throughput coarse-grained simulations to rationally design and characterize soft-matter materials - Tristan Bereau (MPI for Polymer Research) , Kurt Kremer (MPI for Polymer Research), Jilles Vrekeen (MPI for Informatics), Luca Ghiringhelli (Fritz Haber Institute) .
4.2. Towards an accurate, high-throughput framework for the prediction of anharmonic free energies in molecular crystals - Mariana Rossi, Marcin Krynski (Fritz Haber Institute), Tristan Bereau (MPI for Polymer Research)