Nanoparticle Clustering in Supraparticles to Control Magnetic Long‐Range Interactions

Abstract To tailor superparamagnetic iron oxide nanoparticles (SPIONs) to the specific needs of diverse application fields, it is essential to understand not only their intrinsic properties but also their interactions with each other. Theoretical models predicting/explaining the magnetization behavior of macroscopic samples containing millions of SPIONs are intricate due to the complexity of the underlying relaxation mechanisms in alternating fields. This study introduces supraparticles (SPs) as model architectures to empirically investigate magnetic interactions within and between large SPION clusters (>100 nanoparticles (NPs)). For this purpose, NP dispersions containing SPIONs and silica (SiO 2 )NPs as non‐magnetic building blocks are spray‐dried to form binary SPs. Selective salt‐induced agglomeration of the two building block types before spray‐drying is utilized to tailor SP architectures, including control over SPION cluster size, shape, and proximity. Magnetic particle spectroscopy (MPS), operating under ambient conditions, reveals altered magnetization behavior for different cluster structures. Not only the nearest SPION neighbors, but the whole cluster structure up to several micrometers is decisive for the magnetization behavior. This highlights the importance of long‐range magnetic interactions. This work presents a versatile approach for designing model architectures to advance empirical interaction studies between SPIONs in macroscopic samples.