The establishment of algae based production processes for application in different goods such as food, feed, nutritional supplements, medicine, fuel or platform chemicals is increasingly gaining more attention. A main reason for this development might be due to the crescent need to replace conventional industrial processes with more sustainable ways of production.
The ongoing increase of computational and sensoric capabilities opens new options to establish monitoring systems that allow to get better insights, statistical certainty and control over various process parameters in order to improve process performances rapidly. Experimental investigation of algae cultivation in laboratories however depicts itself quite far from being automated or digitalized. Typical work tasks during cultivation processes involve a frequent removal of sample volumes out of the reactor vessel to be analyzed with various methods to obtain the process describing data.
In many cases the analysis is done after the experiment has ended. Each of this samples taken poses the risk of a contamination and therefore a disruption of the whole experiment. Additionally it is required to take multiply samples at a time in order to guarantee a satisfactory statistical certainty of the dataset. On the other hand the amount of samples possible is limited by the small working volumes of a few liters in lab-scale reactor vessels. The aim of this project therefore lies on the development of an experimental set up for on-line monitoring. This will consist of suitable sensors, a data acquisition infrastructure and signal processing software for the on-line monitoring of relevant process parameters.
The description of the process state for example can be done by mass-balancing elemental components of the microalgae like carbon, oxygen and nitrogen to determine the time specific production and consumption rates and monitor them in real time.