Refrigeration based on the magnetocaloric effect (MCE) can contribute to energy‐saving, environmentally friendly cooling in private households, or industrial application. The cooling is based on the reversible heat release or uptake during a phase‐transformation of the materials that can be controlled by a magnetic field. This process could replace conventional compression‐based refrigeration, which often relies on environmentally harmful refrigerants. The MCE is observed in a large number of magnetic alloys, upon them are Heusler alloys. Thus, optimization of MCE materials involves the screening and testing of many different materials systems, generating a large amount of data that, so far, has not been organized in a systematic manner, hindering the progress of the field. Here, were present an approach to digitalize the process chain from synthesis, experiment, and simulation to prototypical applications. Different Heusler alloys have been examined experimentally as model systems for potential applications in magnetic cooling. Templates based on the OTTR technology have been developed and implemented for the acquisition and semantic representation of knowledge in the development of an ontology. The ontology, when combined with unstructured data, can be exploited to train a model that can then be used to predict missing facts, which can help to gain new insights and to generate new hypotheses. Furthermore, tools have been developed that automate and accelerate data acquisition into ontological structures, and workflows have been implemented that provide a fast, easy‐to‐use theoretical and experimental evaluation of the MCE from first principles and raw data.
Bekemeier et al. (Sat,) studied this question.
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