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Introduction: Additive manufacturing has transformed material science by enabling 3D printing of tunable structures for applications like micro-robotics, sensors, and tissue engineering [1]. However, conventional extrusion-based printing uses fixed nozzle shapes, which limit control over the extruded material compositions and printed geometries. Recent methods offer some composition and flow control but rely on bulky, complex systems [2]. Passive techniques like co-axial nozzles, Dean vortices, and hydrodynamic focusing lack dynamic modulation [3–4]. Here, we present Active Flow Sculpting (ActiSculpt), a method for spatiotemporal modulation of multi-layered laminar streams using on-demand acoustic streaming, enabling dynamic flow structuring. We developed software to predict the cross-sectional flow patterns using a comprehensively enhanced acoustic streaming model that accurately depicts the experimental conditions. We achieved a five-fold increase in the moment of inertia (MoI) of the sculpted cross-sectional flow profile, translating into a wide range of bending and torsional strengths of a cured fiber.
Methods: Surface acoustic waves from interdigital transducers (IDTs) generate strong body forces to shape laminar flow in the ActiSculpt platform (Fig. 1a). Four straight IDTs, offset by 250 µm, are placed beneath a 1 mm × 1 mm PDMS microchannel. Each IDT (37–48 MHz) is actuated independently via time-division multiplexing (TDM) (Fig. 1b). A low-cost numerical model is developed to simulate the fluid transformation based on Eckart’s streaming (Fig. 1c). Red and blue photo-curable precursors are polymerized via stop-flow lithography[5,6] to reveal cross-sectional flow profiles (Fig. 1d). The TDM allows combinatorial actuation of the multiple IDTs.
Results and discussion: Distinct sculpted flow shapes are achieved in a precisely controllable manner by selectively varying the input power to IDTs 1–4. The sculpted shapes are characterized using a diffusion parameter based on standard deviation, with values remaining above the mixing threshold even at higher power levels (Fig. 2a). The sculpted shape uniformity is assessed by comparing results across different cycles. The uniformity exceeds 75% (up to ~95%) for different actuations by IDTs 1-4, confirming the robustness of our method (Fig. 2b). Transformation of the center of mass for each labelled channels quantified by cumulative dislocation parameter as swiping the power values (Fig. 2c). We measured the MoI of the sculpted shapes to vary by 5-fold using a single ActiSculpt platform (not shown), which highlights the versatility of our method. A combinatorial actuation of actuators reveals more unique shapes and opportunities for cross-sectional sculpting (Fig. 3).
Conclusion: The ActiSculpt platform offers highly flexible and unique capabilities to actively manipulate multi-layered flows on-demand, which will unveil new possibilities in the field of microfluidic flow control, 3D printing, and additive manufacturing.
References: [1] Truby et al. Nature 540, 371 (2016). [2] Larson, N.M.et al. Nature 613, 682 (2023). [3] Destgeer G, et al. Lab Chip, 2020,20, 3503-3514. [4] Amini, H. et al. Nat Commun 4, 1826 (2013). [5] M. A. Sahin, et al. Small 2024, 2307956. [6] M. U. Akhtar, et al. Adv. Mater. Technol. 2024, 9, 2301967.
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