Graduation Year


Document Type




Degree Name

Doctor of Philosophy (Ph.D.)

Degree Granting Department

Chemical Engineering

Major Professor

Venkat R. Bhethanabotla, Ph.D.

Co-Major Professor

Scott W.Campbell, Ph.D.

Committee Member

John N. Kuhn, Ph.D.

Committee Member

Thomas M. Weller, Ph.D.

Committee Member

Samuel Wickline, Ph.D.


Sorption, Selectivity, Response, Sensitivity


Volatile organic compounds (VOCs) are chemicals that evaporate easily and become gases at ambient temperature and pressure. The EPA has made the monitoring of VOCs mandatory due to their health impacts, which range from headaches and nausea to cancer. The current techniques used for VOC monitoring such as photoionization, gas chromatography, mass spectroscopy, and e-noses sensors are expensive, time-intensive, demand rigorous sample preparation, and cannot quantify the VOCs in the air. Chemical sensors based on piezoelectric transduction like the quartz crystal microbalance (QCM) show promising results in terms of providing cost-effective real-time data, robustness, and low power requirements. In this work, QCM has been employed as the chemical sensor to detect and quantify BTEX gases in the air using a polymer-plasticizer blend as the sensing film.Plasticization helps to modify the chemical and physical properties of the glassy polymer by decreasing the glass transition temperature, altering the pore dimensions, and increasing the free volume of the polymer film thus enabling higher diffusion and sorption of the analyte molecules. Sensing films based on polymer-plasticizer films have been developed to detect the volatile organic compounds in the air, primarily benzene, ethylbenzene, toluene, and xylene (BTEX) using two QCM devices built and modified in the lab, each able to detect the analytes at a certain concentration. This work shows how the selectivity and sensitivity of a glassy polymer film can be altered by adding a precise amount and type of plasticizer for BTEX detection. To quantify the film saturation dynamics and understand the absorption of BTEX analyte molecules into the bulk of the sensing film, a diffusion study was incorporated to interpret the frequency vs time curve from a QCM. The sensor responses for individual analytes like benzene, toluene, etc. were collected and fit to exponentials which give a characteristic value for response time, ? for individual analytes like benzene, toluene, and, ethylbenzene, thus helping in identifying the analyte. The model was also able to quantify individual analyte concentrations from a gas mixture based on the difference in values using a single polymer-plasticizer film on a QCM sensor. Several polymer/plasticizer materials were screened to optimize the film for the best BTEX sensing performance based on sorption properties (solubility, partition coefficient, tau) and stability of these films over a period as opposed to the traditional approach of using a sensor array. The experiments done at higher concentrations (a few 1000 ppm) using the original QCM apparatus helped in selecting the top three polymer-plasticizer films and further translated to lower concentration (a few 100 ppm) to check its applicability using the modified new apparatus built in the lab. The novel contributions of this dissertation towards the field of BTEX sensing are:

  1. This work shows that the selectivity and sensitivity of glassy polymers can be tailored by introducing a plasticizer. It was found that the sensitivity of a plasticized glassy polymer was higher than that of rubbery polymers.
  2. As opposed to the concept of an array of sensor films, this study employs the use of a single film that can both detect and quantify BTEX analytes in the air using the QCM device. Out of a wide variety and types of polymers and plasticizers available in the literature, we have come up with a procedure to identify an optimum film, and thus provided a single film based on the examination done.
  3. Sensor response curves for individual analytes, binary and ternary mixtures were characterized to detect BTEX compounds using the QCM device. We were able to determine the compositions of the analyte in the gas phase by interpreting the sorption frequency-time curve. The model-predicted analyte mole fractions lined up well with the actual gas phase composition both at high and low concentrations.