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Advances in passive micromixer designs for biochemical systems: A review on mechanistic insights and performance evaluation

Publication Type : Review Article

Publisher : Elsevier BV

Source : Chemical Engineering Journal Advances

Url : https://doi.org/10.1016/j.ceja.2026.101122

Keywords : Micromixer, Chaotic advection, Concentration distribution, Mixing index, Reynolds number

Campus : Amritapuri

School : School of Engineering

Department : Mechanical Engineering

Year : 2026

Abstract : Traditional micromixing techniques require substantial amounts of samples, leading to high costs and operational challenges. Passive micromixers are key components of microfluidic technology, and contemporary passive microfluidic systems offer simple and cost-effective solutions for controlled sample mixing and improved performance. The present study integrates findings from numerical modeling and experimental studies to provide a comprehensive understanding of passive micromixer design strategies and performance assessment. This comprehensive review examines passive micromixer designs by exploring a range of configurations from traditional T- and Y-shapes to novel strategic designs, such as split and recombine (SAR) models, obstacle-based designs, curved and serpentine patterns, baffle-based structures, and topology-optimized layouts. The design impact on mixing efficiency and pressure drop, along with the fundamental mixing mechanisms, advantages, and appropriate applications across diverse domains were evaluated. Numerous advances in innovative and bio-inspired passive micromixers, with applications spanning fields such as biochemistry, energy, and water screening, thereby contributing to the achievement of sustainable development goals (SDG - 3, 6, and 7), are also examined.

Cite this Research Publication : Abhilash Anand M.K., Ajith Kumar S., Jeetu S. Babu, Advances in passive micromixer designs for biochemical systems: A review on mechanistic insights and performance evaluation, Chemical Engineering Journal Advances, Elsevier BV, 2026, https://doi.org/10.1016/j.ceja.2026.101122

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