On-Demand 3D Spatial Distribution of Magnetic Permeability Based on Fe₃ O₄ Nanoparticle Liquid Toward Micro-Cavity Detectors

The change of 3D spatial distribution of magnetic permeability can lead to the generation of introduced electrical signals. However, present studies can only achieve rough regulation by simple shape deformation of magnetic elastomers such as compression, bending, or stretching. Accurate control of the 3D spatial distribution of magnetic permeability is still an open question. In this study, an on-demand 3D spatial distribution of magnetic permeability by controlled flowing of Fe₃ O₄ nanoparticle liquid (FNL) is demonstrated. The flowing routes of FNL are tuned by a 3D-printed cage with pre-designed hollow structure, thus changing the 3D spatial distribution of magnetic permeability. Then, eight symmetrically distributed coils under cage are used to receive characteristic induction voltage signals. Maxwell numerical simulation reveals the working mechanism of signal generation. Notably, those eight coils can detect FNL flowing status in eight directions, allowing recognition of up to 255 different FNL flowing combinations. By introducing machine learning, the micro-cavity detector based on FNL can distinguish nine kinds of micro-cavity structures with an accuracy of 98.77%. This work provides a new strategy for the adjustment of the 3D spatial distribution of the magnetic permeability and expands the application of FNL in the field of space exploration.