Database driven science for new materials

In computational materials science materials properties can now be computed with unprecedented precision using quantum mechanical approaches and the advent of high-performance computing facilitates enables high-throughput calculations. Unfortunately, this data is rarely shared with industry and is often as quickly "forgotten" as it was generated, creating a "materials gap" between science and industry. Efforts are underway worldwide to build materials databases and data analysis tools to utilise this data as a resource. Such database driven materials science is emerging as a new trend in academic research, but to close the materials gap it has to become a new paradigm adopted by industry to accelerate materials discovery and societal impact. In the Database Driven Science for New Materials (DataSciMat) project, we will address this paradigm shift from local and global perspectives. Locally, we will form an interdisciplinary team involving four schools at Aalto University and an industrial partner to analyse data and identify the most stable material for a particular industrial coating application of a new promising solar cell material. Globally, DataSciMat will pilot a project to demonstrate the knowledge transfer from materials databases to industry and conduct an extensive, multinational status and socio-economic impact study of the field of database driven science.