Characterization of an enzymatic packed-bed microreactor

Process intensification is a key contribution to fast growth and development in modern industries. This is due to technological development and needs to satisfy customer demand. For instance, miniaturized reactors have gained popularity over the few decades owing to their small dimensions that ensure high surface to volume ratio. Presently, most industries are turning to continuously operated biocatalytic processes in reactors due to their numerous advantages including their durability and efficiency. However, the currently used miniaturized reactors do not provide long operational stability and high biocatalyst loads and therefore better alternatives are needed.

Recently, miniaturized packed-bed reactors have been used to overcome the aforementioned challenges. Unfortunately, the simultaneous increase in the reactor capacity and enhanced microscale processing benefits have been difficult to obtain. This is attributed to the dependence of the reactor performance on the fluid flow distribution within the packed bed. Consequently, hydrodynamic studies of the pressure drop, flow regime within the micro packed-bed reactor have not been fully explored. To this end, the use of compatible devices such as biosensors as analytical tools has attracted attention amongst researchers due to their efficiency and accuracy.

Among the available methods used in hydrodynamics modeling, lattice Boltzmann is simple and efficient especially in the incorporation of complex geometries, unlike the other conventional methods. This is suitable for micro-packed bed reactor. However, application of the method in the simulation of chemical reaction and flow field have borne inaccurate results and more so in systems with very low solute diffusion rate.

In a recent research work published in Chemical Engineering Journal University of Ljubljana researchers led by Professor Polona Žnidaršič-Plazl investigated the micro packed-bed reactor based on two parallel plate configurations. It contained porous resins with immobilized Candida antarctica lipase B. Furthermore, they utilized the lattice Boltzmann method to predict the random distribution of particles placed in one layer. Eventually, they compared the numerical solutions with the residence time distribution obtained through stimulus-response technique comprising of an in-line monitoring biosensor.

The research team observed that by keeping the bed porosity constant, the residence time distribution was not affected by uniform random packing. Consequently, numerical experiments depicted similar results. On the other hand, glucose oxidase biosensor provided accurate online data thus proving to be a useful tool in residence time distribution analysis as compared to other conventional analytical equipment that are time consuming, inaccurate and difficult to use.

According to Professor Polona Žnidaršič-Plazl and her colleagues, the results exhibited the presence of enzymes as well as favorable hydrodynamic conditions. For instance, very low-pressure drops were noticed for characterized micron packed-bed reactor for different sizes and dimensions as compared to its counterparts. Owing to the accurate and agreement between the theoretical and experimental results obtained, their study will enhance applicability for a production system in the industries and in particular those based on the numbering-up approach and hope will escalate industrial growth across numerous fields.