Bioremediation, the most environment-friendly soil remediation method, should receive adequate attention. However, its efficiency has often been criticized, reflecting the dearth of information about microbial activity in the soil. Biosensors can use the signals sent by microorganisms to quantify and analyze microbial activity. Therefore, combining biosensors with bioremediation can enhance the application of bioremediation technology.
This thesis focused on designing and fabricating of portable microbial fuel cell (MFC) and oxidation-reduction potential (ORP) based sensor to achieve in situ soil bioremediation application in the future. This is because conventional biosensors cannot reflect the detailed microbial growth characteristics during soil bioremediation.
During the experiment, two portable sensors were designed. First, two cylindrical polypropylene bottles were compressed tightly to form a preliminary sensor containing a proton exchange membrane (PEM), an O-ring, and a cathode electrode. After successfully testing the preliminary sensor’s workability, a smaller, easier-to-assemble 3D-printed sensor was designed based on the same concept.
The extracellular electrogenic bacterial Bacillus subtilis was used to test both sensors’ workability. MFC and ORP sensors provide voltage and redox potential outputs. By integrating real-time redox potential and voltage outputs, a typical microbial growth (potential parameter) curve can be created. The derivative optical density (OD) value (OD per hour) was found to correspond to the potential parameter. The preliminary sensor could acquire detailed microbial growth characteristics at 6.5 and 18 hours, and the 3D-printed sensor at 10 and 21 hours. The accompanying derivative OD values supported these conclusions. This novel sensor can monitor real-time microbial growth, report detailed growth characteristics in soil, and help select better bioremediation solutions.
Future work is required to improve the responsive of the 3D-printed sensor to achieve higher-resolution result
