Morteza Bayareh, Fatemeh Alipour, Zahra Ghorbani Kharaji, Samira Sourani, Ahmad Najafpour, Dariush Bahrami
Micromixing governs reaction efficiency, selectivity, and product quality in microfluidic chemical reactors. While many reviews catalogue mixer designs, a critical synthesis quantitatively linking designs to chemical outcomes through a rigorous methodology is absent. This review fills that gap by employing a systematic, PRISMA-guided literature selection to analyze micromixer fundamentals and their applications. Moving beyond descriptive classification, this paper critically evaluates how specific geometries and operational parameters directly dictate performance in key processes like nanoparticle synthesis and multiphase catalysis. This analysis reveals a persistent disconnect between advanced mixer design and predictive, application-specific models. This paper, therefore, articulates insights into emerging paradigms, such as machine-learning-aided design and integrated real-time analytics, that are poised to transition the field from iterative prototyping to tailored, digitally-driven development.