Acetone in exhaled breath is gaining attention as a non-invasive means of quantifying blood glucose levels in Diabetics. This calls for development of novel biosensors for the detection of trace concentrations of acetone present in human breath. Traditional gas detection systems, such as GC/MS and chemiresistive sensors, are currently used for this purpose. However, these systems have limitations with regards to size, cost, and operating temperature. This work presents the K2W7O22/Ti3C2 nanocomposite sensor as breath acetone sensor that overcomes the limitations in traditional detection systems. Sensing experiments were conducted using 5 different sensor materials in varying ratios. KWO/Ti3C2 - ratio 2:1 (annealed) and KWO/Ti3C2 - ratio 2:1 (Unannealed) showed excellent sensitivity to 2.85ppm and 5.4ppm acetone concentration. These materials were then implemented in a prototype device. Material and device test results confirm the potentials of the novel KWO/Ti3C2 nanocomposite as a good sensor for breath acetone detection.

The successful fabrication and characterization of two chemiresistive platforms for biomolecule detection was demonstrated by this work. The Si/Silica based single walled nanotube thin film (SWNTTF) platform was developed to understand the effect of device geometry on pH and M13 bacteriophage sensing capabilities as well as the underlying mechanisms governing SWNTTF chemiresistive biosensors. The dominant mechanism of sensing switched from direct chemical doping to electrostatic gating when the target analyte changed from H+/OH- ions in pH testing to whole viruses. The experimental limit of detection for M13 for this platform was 0.5pM and an increased sensitivity as well as variability was observed in devices with smaller channel widths. Preliminary device calibration was completed in order to correlate a resistance response to a bulk M13 concentration. The polyethylene terephthalate (PET) based SWNTTF platform was developed to demonstrate the commercial potential of SWNTTF chemiresistive biosensors by detecting relevant concentrations of brain natriuretic peptide (BNP) on economically viable substrates. The pH response of these chemiresistors confirmed that chemical doping was the cause for resistance change in the SWNTTFs. The preliminary results demonstrated successful BNP detection at 50pg/mL using both aptamers and antibodies as recognition elements. Using SWNTTFs as the transducing element of chemiresistors allowed for further understanding of electrical mechanisms of sensing as well as achieving sensitive, real-time and reproducible electrical virus and biomolecule detection. Although these platforms do not achieve ultrasensitive limits of detection, they demonstrate the commercial potential of platforms using SWNTTFs as the transducing element of electrical biomolecule sensors.

Disinfectants are added to the water distribution system and swimming pools to control the growth of pathogenic microorganisms in water. High disinfectant levels are health hazards since they produce disinfectant by-products which are carcinogens. Thus, monitoring the amount ofresidual disinfectants present and maintaining an optimal amount of residual disinfectants throughout the distribution network is very crucial for safe water distribution. Colorimetric measurements are the current standard for measuring disinfectant levels in water. However, it is very difficult to integrate colorimetric measurements into automated monitoring devices. Redox active molecules like the phenyl-capped aniline tetramer (PCAT) can be incorporated as a dopant into a single wall carbon nanotube sensor for detecting oxidant in drinking water. The sensor works on the principle of oxidizing adsorbed redox molecules on carbon nanotubes by oxidant present in drinking water thus changing the resistivity of the carbon nanotube film. Most commonly used disinfectants are HOCl, Cl2, ClO2, Chloramine, KMnO4, HOBr, H2O2, O3, Br2, I2, etc. They all are oxidizing agents and can be distinguished from one another as they have different oxidation potentials. For water treatment purposes, it is not enough to know the disinfectant level, but it is also very important to identify which disinfectant is present. Currently, there is no standard method for distinguishing different disinfectants presents in water. The development of sensor arrays based on redox active molecules having different redox potentials is a potential pathway towards differentiating between different disinfectants in water. Different aniline oligomers were synthesized to create a library of redox active molecules. Redox properties of these molecules have been determined, and expected results were compared with the sensor performance. In the future, these sensors can be incorporated into a reliable, resettable and reagent free sensor array for monitoring and distinguishing different disinfectants in water. Being able to constantly monitor the disinfectant level and identifying the disinfectant present in water will enable us to design an improved and sustainable disinfecting system. / Thesis / Master of Science (MSc)

Conductive polymer composite sensors have shown great potential in identifying gaseous analytes. To more thoroughly understand the physical and chemical mechanism of this type of sensors, a model was developed by combining two sub-models: a conductivity model and a thermodynamic model, which gives a relationship between the vapor concentration of analyte(s) and the change of the sensor signals. In this work, 64 chemiresistors representing eight different carbon concentrations (8–60 vol.% carbon) were constructed by depositing thin films of a carbon black–polyisobutylene composite onto concentric spiral platinum electrodes on a silicon chip. The responses of the sensors were measured in dry air and at various vapor pressures of toluene and trichloroethylene. Three parameters in the conductivity model were determined by fitting the experimental data. It was shown that by applying this model, the sensor responses can be predicted if the vapor pressure is known; furthermore the vapor concentration can be estimated based on the sensor responses. This model will guide the improvement of the design and fabrication of conductive polymer composite sensors for detecting and identifying organic vapors. A novel method was developed to optimize the selection of polymeric materials to be used within a chemiresistor array for anticipated samples without performing preliminary experiments. It is based on the theoretical predicted responses of chemiresistors and the criterion of minimizing the mean square error (MSE) of the chemiresistor array. After the number of chemiresistors to be used in an array and the anticipated sample chemistry are determined, the MSE values of all combinations of the candidate chemiresistors are calculated. The combination which has the minimum MSE value is the best choice. This can become computationally intensive for selection of polymers for large arrays from candidates in a large database. The number of combinations can be reduced by using the branch and bound method to save computation time. This method is suitable for samples at low concentrations where thermodynamic multi-component interactions are linear. To help users apply this polymer selection method for the sensors, a website including 10 solvents and 10 polymers was developed. Users can specify a target sample and obtain the best set of polymers for a sensor array to detect the sample. The activities of trichloroethylene and toluene in polyisobutylene were measured at very low concentrations. The activities for toluene are consistent with published values at higher concentrations. The values for trichloroethylene are a new contribution to the literature.

Globally, there is growing concern about the health risks of water and air pollution. The U.S. Environmental Protection Agency (EPA) has developed a list of priority pollutants containing 129 different chemical compounds. All of these chemicals are of significant interest due to their serious health and safety issues. Permanent exposure to some concentrations of these chemicals can cause severe and irrecoverable health effects, which can be easily prevented by their early identification. Molecularly imprinted polymers (MIPs) offer great potential for selective adsorption of chemicals from water and air samples. These selective artificial bio(mimetic) receptors are promising candidates for modification of sensors, especially disposable sensors, due to their low-cost, long-term stability, ease of engineering, simplicity of production and their applicability for a wide range of targets. Herein, innovative strategies used to develop MIP-based sensors for EPA priority pollutants will be reviewed.