Field-Programmed Anisotropy in Magneto-Piezoelectric Composites for Material-Encoded Mechanoperception

Abstract

Decoupling superposed force vectors along spatially distinct axes is a prerequisite for artificial somatosensation in soft intelligent systems. Although polymer-piezoelectric composites offer essential compliance, randomly distributed nanofillers result in a loss of inherent polar directionality and macroscopic anisotropy, which prevents force-vector discrimination. Here, we address this challenge by encoding force-mode selectivity into magneto-piezoelectric composites via field-programmed anisotropy. Guided by a rigorous torque-balance framework, we achieve the deterministic spatial alignment of Fe3O4-decorated BaTiO3 nanowires within a shape-memory polymer matrix. The resulting axially aligned hierarchical percolation networks serve as continuous load-transfer pathways to concentrate mechanical stress along the principal axes of the nanowires while suppressing off-axis interference. Such structure-driven anisotropy in electromechanical coupling maximizes piezoelectric transduction efficiency and empowers the nanocomposite to intrinsically distinguish force modalities. By upscaling the intrinsic anisotropy of piezoelectric nanowires to the macroscopic composite level, our approach defines a physical basis for material-encoded mechanoperception. Our findings establish a versatile platform for soft embodied intelligence that offers vector-resolved somatosensory capabilities at the material level.