A Novel Method for Understanding the Mixing Mechanisms to Enable Sustainable Manufacturing of Bioinspired Silica

Abstract

Bioinspired silica (BIS) has received unmatched attention in recent times owing to its green synthesis, which offers a scalable, sustainable, and economical method to produce high-value silica for a wide range of applications, including catalysis, environmental remediation, biomedical, and energy storage. To scale-up BIS synthesis, it is critically important to understand how mixing affects the reaction at different scales. In particular, successful scale-up can be achieved if mixing time is measured, modeled, and kept constant across different production scales. To this end, a new image analysis technique was developed using pH, as one of the key parameters, to monitor the reaction and the mixing. Specifically, the technique involved image analysis of color (pH) change using a custom-written algorithm to produce a detailed pH map. The degree of mixing and mixing time were determined from this analysis for different impeller speeds and feed injection locations. Cross validation of the mean pH of selected frames with measurements using a pH calibration demonstrated the reliability of the image processing technique. The results suggest that the bioinspired silica formation is controlled by meso- and, to a lesser extent, micromixing. Based on the new data from this investigation, a mixing time correlation is developed as a function of Reynolds number─the first of a kind for green nanomaterials. Further, we correlated the effects of mixing conditions on the reaction and the product. These results provide valuable insights into the scale-up to enable sustainable manufacturing of BIS and other nanomaterials.