Design of Polymeric Sensing Materials for Volatile Organic Compounds: Optimized Material Selection for Ethanol with Mechanistic Explanations
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There are many applications in which sensing and monitoring volatile organic compounds (VOCs) and other gas analytes are important. This thesis focusses on finding suitable sensing materials for ethanol to reduce the instances of people driving while intoxicated. To find suitable sensing materials, many constraints must be taken into consideration. For example, a sensing material and sensor must have the appropriate sensitivity and selectivity required. The goal is to create a sensing material or multiple materials capable of detecting ethanol that is emitted from the skin (transdermally). This requires highly sensitive sensing materials and sensors capable of detecting ethanol close to 5 ppm. This limit of 5 ppm was confirmed by measuring transdermal ethanol. In addition, to avoid false positives, the sensor must be able to selectively identify ethanol (i.e. respond preferentially to ethanol). To achieve this goal, polymeric sensing materials were used because of their ability to be tailored towards a target analyte. Multiple polymeric sensing materials were designed, synthesized, and evaluated as a sensing material for ethanol. Both the sensitivity and selectivity of the sensing materials were evaluated using a specially designed experimental test set-up that included a highly sensitive gas chromatograph (GC) capable of detecting down to the ppb range. In total, over thirty potential sensing materials were evaluated for ethanol. These sensing materials, which include polyaniline (PANI) and two of its derivatives, poly (o-anisidine) (PoANI) and poly (2,5-dimethyl aniline) (P25DMA), doped with various concentrations of five different metal oxide nanoparticles (Al2O3, CuO, NiO, TiO2, and ZnO), were synthesized and evaluated for sensitivity and selectivity to ethanol. In addition, specialized siloxane-based polymers and other polymers such as poly (methyl methacrylate) (PMMA) and polypyrrole (PPy) were evaluated. From these thirty plus sensing materials, P25DMA doped with TiO2, NiO, and Al2O3, along with PPy, had the best sensitivity towards ethanol. Most of the materials tested, with the exception of the CuO doped P25DMA, P25DMA doped with 20% ZnO, poly (ethylene imine) (PEI), and the siloxane-based sensing materials, were able to sorb, and therefore detect, 5 ppm of ethanol. Therefore, the sensitivity requirement of 5 ppm was satisfied. In terms of selectivity, P25DMA doped with 5% Al2O3 and P25DMA doped with 10% TiO2 had the best selectivity towards ethanol with respect to five typical interferent gases (acetaldehyde, acetone, benzene, formaldehyde, and methanol). Some of the most promising polymeric sensing materials were then deposited onto two different kinds of sensors: a capacitive radio frequency identification (RFID) sensor and a mass-based microcantilever microelectromechanical systems (MEMS) sensor. These sensors were evaluated for sensitivity, selectivity, and response and recovery times. It was found that P25DMA doped with 20% NiO had a detection limit of 3 ppm on the RFID sensor, whereas P25DMA had a detection limit of 5 ppm on the MEMS sensor. It should be noted that not all sensing materials work well on all sensors. To improve the selectivity of a sensor, a sensor array or electronic nose can be used. These use a pattern-recognition algorithm to separate the responses for different gas analytes. A proof-of-principle study was done using principal component analysis that was capable of distinguishing between six different VOCs using five different polymeric sensing materials. In addition, a three sensor array was evaluated on the RFID platform. Using PCA as the filtering algorithm, four gas analytes (ethanol, methanol, acetone, and benzene) were able to be identified. These four analytes could also be identified even when in gas mixtures of twos and threes and when all four gas analytes were present. After this wide experimentation, and based on the knowledge gained from the sorption responses between various VOCs and polymers, along with what has been reported in the literature, various sensing mechanisms were proposed. These sensing mechanisms explain why certain VOCs sorb more preferentially onto certain polymers. Therefore, identifying the dominant sensing mechanisms for a target analyte can improve sensing material selection. Based on these sensing mechanisms, potential sensing materials can be chosen for a target analyte. By including other constraints from the specific application target and sensor, this list of potential sensing materials can be further narrowed. From here, these sensing materials can be evaluated for sensitivity and selectivity, before the most promising ones are deposited onto sensors for further testing. This has led to prescriptions that can be followed when designing a new sensing material for a target application. These prescriptions take into consideration the chemical nature of the target analyte (and thus, the dominant mechanisms by which it is likely to interact), any constraints of the target application (including operational temperature and type of sensor), and the chemical nature of the common interferents present with the target analyte. These prescriptions allow one to narrow down a list of hundreds or thousands of potential sensing materials to a manageable few, which can then be evaluated.
Cite this version of the work
Katherine Mariann Elizabeth Stewart (2016). Design of Polymeric Sensing Materials for Volatile Organic Compounds: Optimized Material Selection for Ethanol with Mechanistic Explanations. UWSpace. http://hdl.handle.net/10012/11092