Electrification and the circular economy are leading to increasing demand for recycled steel, including in the field of electrical steel. In particular, more powerful electric motors require both high mechanical strength and stable soft magnetic properties under real operating conditions. Tolerance to impurities, such as Cu contamination from recycling processes, is playing an increasingly important role in this context. The aim of the project is to research digital methods for inverse material design and to use them to develop new, sustainable, and recycling-adapted electrical steels. The collaboration between the WKK at RPTU Kaiserslautern-Landau and the IEHK at RWTH Aachen covers the entire value chain of modern electrical steels. While the IEHK provides simulation-based predictions of Cu precipitation and recrystallization, the WKK uses short-term methods such as cyclic indentation testing, load increase testing, and micromagnetic 3MA measurements to characterize mechanical and magnetic properties. Machine learning-based metallography and atomic probe tomography provide microstructure descriptors, which are supplemented by non-destructive 3MA process monitoring to establish process-structure-property (PSP) relationships.