Nature rarely builds with uniform materials; instead, it achieves exceptional performance by arranging composition and structure across multiple length scales. Mimicking such architectures has become increasingly feasible with additive manufacturing, and especially with multimaterial 3D printing, where complex structures with spatially varying material composition can be fabricated. However, although 3D printing is widely recognized as a digital manufacturing method, multimaterial 3D printing remains only partially digitalized and still relies heavily on trial‐and‐error experimentation to identify printing strategies that produce the desired microstructures. To address this, we present the µSlicer that enables digital programming of internal multimaterial microstructures within individual printed strands. The µSlicer combines a numerical physics framework with an automatic signal generation module, allowing target microstructures to be translated into deposition signals for multimaterial extrusion. This approach fundamentally transforms slicing from purely geometric toolpath generation to microstructure programming, providing a route toward bioinspired, multifunctional, and digitally designed material architectures in extrusion‐based additive manufacturing.
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Meile et al. (2026) studied this question.
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