In addition we will have some outstanding invited talks given by (some of them not yet confirmed): - Tilmann Beck (TU Kaiserslautern) - Cecilie Hebert (EPFL Lausanne, Switzerland) - Jan Janssen (MPIE Düsseldorf) - Marcus J. Neuer (BFI Düsseldorf) - Stefan Sandfeld (TU Freiberg)
Please, note that this is session is not identical with the symposium "Big data driven materials science (SYBD)", which is on invitation only. Our session in MM is more focussed on structure-composition-property relationships in materials science. Please see the abstract below for details.
We are looking foward to a vivid session on innovative developments! Abstract:---------- This session covers innovative high-throughput and materials-informatics approaches for the discovery, description and design of materials. The contributions should address recent developments in the fields of data mining, machine learning, and artificial intelligence for the identification of structure-composition-property relationships in the highly diverse, but often sparse materials data space. Contributions from experiment such as diffraction and various tomography techniques, materio-graphic feature identification, as well as simulation results from the atomistic up to the continuum level are foreseen. A particular focus will be on the consideration of extended materials defects (grain boundaries, stacking faults, dislocation cores) and microstructures. Furthermore, submissions of contributions on accumulating, analyzing, interpreting, storing, and sharing fundamental knowledge about materials is solicited. Contributions may range, and preferably bridge, from physics-based materials understanding to data-driven and application-oriented development.