Abstract
Lipid nanoparticle preparation is important in nanomedicine and biomedical engineering, and micromixers provide an effective technique to achieve precise control over particle size, uniformity, and composition by microscale fluid mixing. This study introduces a novel superellipse bifurcating micromixer (SBM), in which the nonlinear geometric elements are utilized to actively enhance microscale fluid mixing. Through systematic computational fluid dynamics simulations, we evaluate nine distinct superelliptic configurations and identify an optimal geometry that achieves the highest mixing index. Our analysis reveals that this design promotes a multi-scale interaction between the main Dean vortices and corner vortices, which significantly enhances chaotic advection and thereby maximizes the mixing performance. This improvement is evidenced by a threefold increase in the maximum Q-criterion compared to conventional circular designs, accompanied by an acceptable 37% increase in pressure drop. A ten-unit SBM based on this optimized geometry demonstrates high mixing efficiency in both simulations and experiments. Simulation results show that mixing efficiency improved with increasing Reynolds number and is further enhanced under an asymmetric flow rate ratio (FRR). Experimental results confirm that an optimal flow rate ratio between the two inlets yields improved particle size distribution. This work not only presents a high-performance, scalable micromixer but also deepens the physical understanding of mixing enhancement through multi-scale vortex dynamics, providing critical guidance for advanced nanomanufacturing. © 2026 Author(s).
| Original language | English |
|---|---|
| Article number | 032027 |
| Number of pages | 17 |
| Journal | Physics of Fluids |
| Volume | 38 |
| Issue number | 3 |
| Online published | 27 Mar 2026 |
| DOIs | |
| Publication status | Published - Mar 2026 |
Funding
This research was supported by the National Natural Science Foundation of China (Nos. 12202258 and 12332016). Beijing Beilong Supercloud Computing Co., Ltd. provides support in computational resources.
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