May 18 – 23, 2026
Europe/Rome timezone

Numerical Investigation of a Cristae-Inspired Passive Micromixer for Microfluidic Applications

May 23, 2026, 12:40 AM
20m
Poster Computational and data-driven approaches in microfluidics Poster 19/05

Description

Microfluidic lab-on-a-chip (LOC) systems integrate key analytical processes, such as sample preparation, reaction, separation, and detection, within miniaturized platforms for chemical and biomedical applications. Efficient fluid mixing has been a major challenge in these systems due to the dominance of laminar flow and low Reynolds number conditions, where mixing is predominantly dependent on slow molecular diffusion. Achieving rapid and homogeneous mixing within limited channel lengths is difficult. In this study, a bioinspired passive micromixer is developed based on the cristae architecture of mitochondria, which is known for maximizing surface area and transport efficiency in biological systems. The micromixer incorporates cristae like microstructures within a straight microchannel to produce continuous flow deflection, stretching, and folding, thereby promoting chaotic advection without taking the advantage of external energy sources. This design preserves the fundamental advantages of passive micromixers, that include structural simplicity, low fabrication complexity, and ease of integration with the lab-on-a-chip platforms. Numerical simulations were carried out to investigate the mixing performance of the proposed micromixer under laminar flow conditions across a range of Reynolds numbers (Re<100) that are relevant to microfluidic applications. Mixing efficiency is evaluated using concentration field analysis and a mixing index. The results have shown a significant improvement in the mixing efficiency in comparison to the conventional straight microchannel, attributed to increased interfacial area and enhanced transverse flow generated by the cristae-inspired geometry. The proposed design has shown the potential of mitochondrial-inspired microarchitectures for improving passive micromixing performance and provides a promising approach for advancing microfluidic mixing in biomedical diagnostics, chemical synthesis, and microscale analytical systems.
Keywords: Computational fluid Dynamics (CFD), Bio-mimetic, Microfluidics, Mitochondria, Chaotic Advection, Passive Mixing.

Author

Muhammad Ali Hashmi (Kaunas University of Technology (KTU), Lithuania)

Co-author

Prof. Arvydas Palevičius (Kaunas University of Technology (KTU), Lithuania)

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