Virtual Materials Design (VirtMat)
The challenges of the digital economy of the 21st century and of the 4th industrial revolution call for an accelerated development of novel materials to enable novel applications. In order to evolve the research agenda of the BIFTM and STN Helmholtz-programs towards information driven materials research, 42 PIs from 17 institutes have united in a joint initiative aiming at virtual materials design (VirtMat), which aims at developing an information-driven approach towards predictive material simulations that enables experimental breakthroughs in physics, chemistry, biotechnology and materials science. With this initiative, we aim to address present challenges in the design of complex high-technology products and to establish new materials development strategies to fulfill the requirements of the economy of the 21st century. To achieve this goal we need to overcome the limits of the traditional unidirectional development line of “new materials –> new components –> new products” and replace it with an information based strategy that enables reverse-engineering of materials and device components on the basis of system and device requirements. At the core of this approach are scales bridging computational methods that are supplied by the platform for modelling and virtualization at the KIT-center for materials in technology and life sciences, which is supported by all theoretically oriented groups in the programs STN and BIFTM. These modelling tools integrate with, and are validated by experimental methods in both programs within the support of the KNMF to enable information-driven co-development of novel materials that goes beyond established big-data approaches. The virtualization of materials research and development creates a competitive platform for novel complex and hybrid materials similar to established modelling technologies that drive product development in the automobile, aircraft industry and electronics industry. Ultimately this platform will enable end-users to systematically apply information-driven methods in product development in novel application areas and to exploit the resulting competitive advantages regarding the reduction of the R&D expenses and the product cycle.