Engineering Specific Magnetic Interactions for Microscale Self-Assembly

The programmable self-assembly of microscale building blocks into complex, functional materials is a longstanding goal in materials science, with implications for biomedicine, energy, and nanotechnology. While DNA nanotechnology and colloidal synthesis have enabled programmable interactions through DNA hybridization and shape complementarity, scaling these methods and increasing the diversity of specific interactions remain challenging. Here, we introduce a novel assembly platform that leverages lithographically patterned magnetic dipoles to engineer specific and tunable magnetic interactions at the microscale, demonstrating the scale-invariant nature of magnetic forces for self-assembly.
By encoding information into rigid particles using arrays of nanomagnets, we achieve highly specific binding interactions, enabling the formation of complex structures with high fidelity. Specifically, we design 12 unique dipole patterns that can potentially generate over 30 distinct specific bond pairs. For select pairs, we observe bond formation accuracies exceeding 95%, demonstrating the feasibility of achieving highly specific interactions.
Through computational simulations and preliminary experimental validations, we establish design principles for programming these magnetic interactions. Our simulations predict high-yield assembly of designed structures, and initial experiments at the microscale using advanced lithography techniques support these predictions. Unlike existing methods, our magnetic encoding platform offers tunable mechanical strength, high information capacity, and is inherently scale-invariant, facilitating self-assembly across multiple length scales.
This approach unlocks new capabilities in self-assembly by allowing precise control over particle interactions and assembly pathways. The ability to form specific magnetic bonds with high accuracy in select cases paves the way for constructing advanced materials with programmable properties.