DiProMag aims to systematically collect for a class of magnetocaloric Heusler compounds the fabrication parameters, the properties measured during fabrication (in situ), the structural data, the data from thermal post-treatments (ex-situ) and the data obtained from multiscale simulations and to relate them to the magnetocaloric efficiency in order to obtain a complete data set on the triangle fabrication-post-treatment-simulation and magnetocaloric properties.
The data generated at each step of the process provide the basis for the development of a suitable ontology. OTTR templates are used to capture and semantically represent process data.
Structured and unstructured data are used to train a vector space model. The result is a vector space that contains semantics and can be queried to gain new knowledge.
In collaboration with industry sponsor Miele, the findings will be transferred to new compounds and used for prototype applications.