Abstract
This study presents a novel methodology framework for simulating and optimizing reaction kinetics in natural convection microfluidic devices. The approach involves coupling heat and mass transfer, fluid flow, and chemistry. Visual and regression analyses are performed to evaluate the impact of different operational parameters on reaction speed, aiming to improve microfluidic natural convection systems. The methodology was applied to a practical example of a Polymerase Chain Reaction triangular microfluidic glass device that utilizes natural convection for the required reactions. The findings showed that the fluid flow velocity is significant in determining the reaction speed, which can be controlled by adjusting the temperature cycling differences and the inner diameter of the device. Despite challenges posed by the fluid flow direction, the best reaction times achieved ranged from 18 to 21 minutes. Due to its computational efficiency, the developed methodology allows simulations to be conducted on mid-range computers. Also, the visual and regression analyses offer insights into improving a specific device by measuring the influence of several parameters. Then, the methodology is convenient for selecting the best conditions before developing an experiment.
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