With the incline of multidrug resistant bacteria due to the widespread use of antibiotics, there has been an ongoing search for a faster and more effective method to test the effect of antibiotics on bacteria. With current techniques for investigation of bacterial resistance requ
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With the incline of multidrug resistant bacteria due to the widespread use of antibiotics, there has been an ongoing search for a faster and more effective method to test the effect of antibiotics on bacteria. With current techniques for investigation of bacterial resistance requiring a minimum of 24 hours to complete, a new technique is essential to reduce the widespread misuse of antibiotics worldwide. In the last decade, new methods of this so-called Antibiotic Susceptibility Testing have been on the rise, with an emphasis on the use of nanomechanical oscillators as highly sensitive sensors. In this thesis, a novel method based on cavities in silicon substrates is introduced to detect the motion of a single motile bacterium and is compared to a highly sensitive sensor based on graphene membranes. A sensor with bacteria attached will exhibit random oscillations and these oscillations can be monitored with a laser. The rigid silicon substrates are intuitively not showing any oscillations. Nonetheless, the motility of a bacterium can still be observed by the changes in the laser path. By using an interferometric setup and monitoring the fluctuation in the voltage signal, coming from bacterial biophysical processes, the Signal-to-Noise-Ratio is determined. The amplitude increase in the fluctuation of the signal is evidently correlated with the motility of the bacteria and is demonstrated to show an increasing trend when presented with a deterministically known topographical location of the bacteria. Subsequently, the ability to detect motile cells enables the capabilities of Antibiotic Susceptibility Testing on these substrates, by monitoring the change in motion of the bacteria prior and post exposure to an effective antibiotic. The motion change, due to antibiotic exposure, is observed to show a significant difference even for a single bacterium, which opens up opportunities for an elementary non-invasive monitoring tool based on silicon.