This paper presents a computational fluid dynamics (CFD) methodology to accurately predict the heat transfer characteristics of an unconfined steady impinging air jet in the transitional flow regime, impinging on a planar constant-temperature surface. The CFD methodology is validated using detailed experimental measurements of the local surface heat transfer coefficient. The numerical model employs a transitional turbulence model which captures the laminar–turbulent transition in the wall jet which precisely predicts the intensity and extent of the secondary peak in the radial Nusselt number distribution. The paper proposes a computationally low-cost turbulence model which yields the most accurate results for a wide range of operating and geometrical conditions. A detailed analysis of the effect of mesh grid size and properties, inflow conditions, turbulence model, and turbulent Prandtl number Prt is presented. The numerical uncertainty is quantified by the grid convergence index (GCI) method. In the range of Reynolds number 6000 ≤ Re ≤ 14,000 and nozzle-to-surface distance 1 ≤ H/D ≤ 6, the model is in excellent agreement with the experimental data. For the case of H/D = 1 and Re = 14,000, the maximum deviations are 5%, 3%, and 2% in terms of local, area-averaged and stagnation point Nusselt numbers, respectively. Experimental and numerical correlations are presented for the stagnation point Nusselt number.

The demand for rapid, high-quality, and controlled mixing at the microscale has led to the development of various types of micromixers. Micromixers are commonly categorised as active, or passive based on whether they utilise external energy to enhance mixing. Passive micromixers utilise a complex geometry to enhance the diffusion coefficient at lower Reynolds numbers and induce chaotic advection at higher Reynolds numbers for effectively mixing fluids without external energy. Active micromixers, on the other hand, achieve precise, fast, and controllable mixing by employing external energy sources such as pressure, electric, magnetic, or acoustic fields. Some active methods such as magnetic field-driven micromixers need fluids with specific properties. Others, such as acoustic field-driven micromixers apply to various types of fluids. Bubbles can be used as membranes or stirrers in microfluidic devices for both passive and active micromixers. They are easy to use, compatible with microfluidic systems, low cost, and effective. Improvements in manufacturing methods, notably, 3D printing have emerged as promising methods for the development of new micromixer designs. In this paper, a wide range of micromixer types is reviewed and the main mechanism for enhanced mixing is investigated. This study aims to guide researchers proposing innovative designs. Furthermore, it is shown that combining different methods can lead to the development of more effective micromixers, promising further advancements in microscale mixing technology.