Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

TL;DR

This paper presents a digitalized process chain for magnetocaloric materials research, integrating experimental, theoretical, and data-driven methods to accelerate development of environmentally friendly cooling technologies.

Contribution

It introduces an integrated digital framework combining ontology, data automation, and modeling to streamline magnetocaloric alloy research and facilitate innovation.

Findings

Successful digitalization of the synthesis and characterization process

Development of tools for automated data acquisition and analysis

Demonstration of improved prediction of material properties

Abstract

Refrigeration based on the magnetocaloric effect (MCE) can contribute to energysaving, 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. Here we show, how to digitalize the process chain for the synthesis, theoretical and experimental characterization, and prototypical application of magnetocaloric alloy. Different Heusler alloys are examined experimentally as model systems for potential application in magnetic cooling. OTTR templates are used 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 are developed that automate data acquisition into ontological structures and workflows are implemented that provide an easy-to-use theoretical and experimental evaluation of the MCE from first principles and raw data.