Integration of Computational Chemistry and Artificial Intelligence for Multi-scale Modeling of Bioprocesses

Bio-based manufacturing is playing an increasingly important role. Flocculation is an important step in bio-manufacturing, and in water, wastewater treatment and the food industry. Flocculation is a multi-scale process with phenomena that span from the nano-scale all the way beyond the microscale. The control and monitoring of such a process is a difficult task due to the lack of knowledge towards modeling the process across the scales. The intention of this work is to develop a hybrid systematic model-based framework, which integrates the computational methods in chemistry and stochastic modeling approaches for monitoring and control of the flocculation process above microscale. The framework therefore utilizes a hybrid model structure. Since industry resorts to either manual control or no control at all for flocculation, it is aimed to reduce the time required for manual control and to avoid unnecessary product losses and unwanted process variations during the operation.