Large Eddy Simulations of Reactive Mixing in Jet Reactors of Varied Geometry and Size

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

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.

Molybdenum Disulphide Precipitation in Jet Reactors: Introduction of Kinetics Model for Computational Fluid Dynamics Calculations

In our previous work, we used the population balance method to develop a molybdenum disulphide kinetics model consisting of a set of differential equations and constants formulated to express the kinetics of complex chemical reactions leading to molybdenum disulphide precipitation. The purpose of the study is to improved the model to describe the occurring phenomena more thoroughly and have introduced computational fluid dynamics (CFD) modelling to conduct calculations for various reactor geometries. CFD simulations supplemented with our nucleation and growth kinetics model can predict the impact of mixing conditions on particle size with good accuracy. This introduces another engineering tool for designing efficient chemical reactors.

Rheological Properties of Engine Oil with Nano-Additives Based on MoS2 Materials

To enhance oil’s tribological and rheological properties, various nano-additives are used. An example of such a nano-additive is nanosized molybdenum disulfide (MoS2). Due to its unique properties, MoS2-based materials used as lubricants have attracted significant attention. In our previous work, we developed a novel, scalable, and low-cost method for MoS2-based materials production using an impinging jet reactor. Hybrid nanostructures based on MoS2 and carbon nanomaterials (MoS2/CNMs) decreased the friction factor of the base oil. In the present study, a mathematical model that accounts for the viscous heating effects in rheograms was formulated. The model was used to interpret the results of rheological measurements conducted for the base oil 10W40 and its mixtures with different nanosized lubricant additives. The model of the non-isothermal Couette flow allowed us to correct the rheograms of the engine oils in the region of high shear rates where viscous heating effects become significant. The temperature correlations for the consistency and flow behavior indexes were proposed. The nanohybrid suspensions of MoS2 in the base oil were found to have the lowest apparent viscosity at low temperatures, typical for the cold engine startup.