|M.Sc Student||Rapoport Shelley|
|Subject||Nanomatreial-Based Field Effect Transistors for|
Detection of Chirality of Volatile
|Department||Department of Chemical Engineering||Supervisor||PROF. Hossam Haick|
|Full Thesis text|
Chiral recognition and separation are currently considered an active area of research due to the potential applications in fields such as chemical synthesis, pharmaceutics, and biotechnology. Chiral enantiomers have shown to behave differently in the body or to be the product of a totally different metabolic system in the body being markers of different diseases. Since enantiomers have the same physical and chemical characteristics only differing from each other in optical activity, their distinction has always been regarded as one of the most challenging in the field of analytical chemistry. The search for a quicker, inexpensive, and easier methods became increasingly important but just as challenging.
This research presents a novel gas sensor that would be able to detect enantiomers of volatile organic compounds (VOCs). To achieve the desired sensitivity, A sensor was fabricated as a field effect transistor (FET) was modified using a novel Polyaniline (PANI)-Carbon nanotube (CNT) composite. The sensor was tested both as a resistor and a FET depending on the gate voltage. Chiral PANI was synthesized in a unique helical form with different handedness. The idea was to try and create a steric factor in addition to electrical, since the differences between enantiomers are very slight.
The helical PANI synthesized was successfully proven to be chiral using circular dichroism (CD). A sensor array was made using five different application methods, CNTs alone, each chiral PANI form alone and with CNTs. Scanning electron microscopy (SEM) analysis was done to assure efficient application of the nanomaterials on the silicon surface of the FET. I-V characteristics were done to ensure that the sensors were working FETs before exposer to the VOCs. The results showed that when the FET is coated with PANI alone, it does not preform like a FET. On the other hand, when combined with the CNTs, the results demonstrated FET behavior at certain conditions.
The array was then exposed to a few VOC groups in addition to the enantiomer VOCs of Limonene in a range of concentrations. The results showed a different response to each concentration to most of the VOCs and a clear stronger response to sensors when PANI is combined with CNTs rather than CNTs alone. The collective data of the array exposure was then re-analyzed using multi-variant pattern recognition algorithm discriminant functional analysis (DFA). DFA was done on each PANI/CNTs composite sensor (R-CSA doped PANI and S-CSA doped PANI) separately and together to better visualize the grouping of the different Xylene isomers and Limonene enantiomers. The results showed successful discrimination among the Xylene isomers with accuracy of 73-80% and the chiral enantiomers with accuracy of 86-93% which shows good enantiomer distinction. An additional DFA analysis was done where the groups in this case were the sensor types while exposed to the same VOC. The results showed 90-99% accuracy which proves successful selectivity of the sensors i.e., react differently to the same VOC.