• Introduced a contactless acoustophoretic printing strategy for on-demand patterning of porous structures in soft materials. • Established a two-stage geometric and energy model that captures bubble formation under localized ultrasonic pressure and predicts enclosure thresholds across liquids. • Enabled programmable porous architectures with tunable pore placement, size, and distribution through software-controlled acoustic focusing. • Unified porous patterning, contact-free multi-material deposition, and customized stereolithography within a single acoustophoretic platform. • Demonstrated the versatility of the approach across edible hydrogels, soft robotic structures, and composite devices with embedded functionalities. Achieving programmable control over pore placement is essential for engineering soft and functional materials with tunable properties. However, existing fabrication methods remain limited by poor spatial specificity, lack of real-time tunability, and cross-contamination risks from physical contact. Here, we present a contactless acoustophoretic printing approach that enables on-demand patterning of porous structures within soft materials using focused ultrasound. We uncover the underlying physics of bubble formation under localized ultrasonic energy through a two-stage geometric and energy model, and apply this principle to print programmable porous architectures that tune mechanical and structural properties. Furthermore, the same device achieves contact-free multi-material deposition via acoustic levitation, unifying porosity and composition within a single process. We demonstrate this versatility by fabricating textured edible hydrogels, soft robotic actuators with compliant porous hinges, and composite devices with embedded optical and magnetic functionalities. These capabilities establish a reconfigurable and contactless route to architected soft matter, enabling field-programmable materials for applications in biofabrication, food engineering, soft robotics, and adaptive manufacturing.
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Hongyi Chen
Shubhi Bansal
Fei Huang
Materials & Design
University College London
Sanofi (France)
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Chen et al. (Wed,) studied this question.
www.synapsesocial.com/papers/69df2a4be4eeef8a2a6af7eb — DOI: https://doi.org/10.1016/j.matdes.2026.116007