Biofilms play a critical role in wastewater treatment by providing a surface for microorganisms to adhere to, facilitating the breakdown of organic pollutants. In biofilm-based treatment systems, bacteria and other microbes within the biofilm metabolize contaminants, leading to improved water quality. We apply mathematical modeling and statistical tools to understand the biofilm dynamics, substrate utilization, and pollutant removal efficiency, and to furthermore predict treatment performance and optimize system design for maximum efficiency in wastewater treatment.
Results from quorum sensing induced dispersal and hollowing effect
The study aims to develop comprehensive models that accurately capture biofilm dynamics at the reactor scale, with an emphasis on one-dimensional biofilms and cell dispersal mechanisms. Biofilms play a crucial role in bioreactor processes like wastewater treatment, and understanding their behavior is key for optimization. This research examines how dispersal mechanisms such as quorum sensing, nutrient depletion, and shear forces influence biofilm growth, detachment, and stability. By integrating these factors into mathematical models, we aim to predict biofilm performance and identify key variables for optimizing reactor design and operational efficiency.
Schematic representation of Biofilm reactor by easy-peasyAI.
Reactor scale modeling of quorum sensing induced biofilm dispersal, result from the simulation data