Mixing indexes considering the combination of mean and dispersion information from intensity images for the performance estimation of micromixing

Abstract

Herein, micromixing was utilized to achieve chemical reaction, homogenization, emulsification, and in applications of microfluidics. In these applications, efficient mixing is one of the most fundamental and difficult-to-achieve characteristics. To quantitatively represent the mixing performance, nearly all the methods to characterize the micromixing processes in miniaturized devices depend on the images obtained by a microscope coupled with a CCD device or a video camera. The experimental images are generally stored in an RGB or gray-scale format. Intensity information of the micromixing images is most often used to estimate the mixing performance. Reliable quantification of the mixing effects is one of the most important and fundamental issues to study the performances of mixers and to optimize the designs. Thus, mixing indexes are of great significance to quantify the mixing effects. However, mixing indexes merely based on dispersion information cannot always produce reliable results if the variation of the mean intensity with enhanced mixing is neglected. Therefore, mixing indexes that consider the combination of mean and dispersion information from the intensity images in two specific forms were proposed. In addition, two practical criteria were used to evaluate the performances of the quantitative mixing indexes. One is the reliability and the other is repeatability precision. According to the comparisons of different mixing indexes studied herein, mixing indexes that consider the combination of mean and dispersion information can ensure the reliability of the calculated result every time and the repeatability precision was less than ±3.5%. Therefore, it can be concluded that the mixing indexes that consider the combination of mean and dispersion information can more reliably represent the mixing performance.