The advancement of innovations in energy generation and conversion, mobility, infrastructure and safety requires corresponding construction materials. Now, new materials are to be developed with material and energy efficiency in mind. The central goal of the Collaborative Research Centre 1232 is to develop a novel scientific method that can be used to find metallic construction materials experimentally efficiently in a very large search space. This method is based on a high-throughput procedure that enables the generation of diverse alloys in the form of small samples, their microstructure adjustment and short-term characterisation, as well as the transfer of these data to material properties of macroscopic samples.
Since June 2016, our working group has been integrated into this concept with the sub-project Design of Experiments in order to support the scientific results of the engineers and computer scientists with mathematical methods. This sub-project deals with the task of identifying suitable process parameters for a given requirement profile of material properties. For this purpose, the project develops algorithms for generating the test plans for high-throughput testing. The generation of a test plan is based on modelling the relationship between process parameters, micro-level descriptors and macro-level material properties. In order to establish a relationship between process parameters and micro-level descriptors, a micro-process function will be developed based on experimental data. This is to be continuously further developed in the course of the project through the experiments carried out. The predictor function will be developed and used to link micro-level descriptors and macro-level material properties. This project will be carried out through interdisciplinary cooperation between the fields of computer science, statistics and industrial mathematics.