Date of Award


Document Type

Open Access Dissertation


Chemical Engineering


College of Engineering and Computing

First Advisor

Michael A. Matthews


The overall goal of this research was to develop a novel approach to reduce the potency of certain asthma triggers, namely, proteins produced by pests or pets in indoor environments. The broad hypothesis of the research was that naturally occurring essential oils will demonstrate enhanced denaturing ability. In any indoor environment, allergens are bound to dry dust particles. In this work, the effectiveness of using dry ice and CO2 with potential for essential oils on dry allergenic proteins through CFD modeling and ELISA methods were evaluated.

There are three objectives central to this work. The first objective was to apply engineering principles through computational fluid dynamic (CFD) modeling on a Coanda spray nozzle. A Coanda nozzle can be used to produce a high velocity mixture of air, gaseous CO2, and dry ice particles from a supply of liquid CO2. Such a process is effective (for instance) for residue-free rapid cooling or precision cleaning. A thermodynamic and computational fluid dynamics analysis of this flow is presented for the purposes of optimizing and modeling the process parameters, which includes the temperature of the liquid CO2 supply, the flow rate, and the pressure, nozzle, and air configurations. The proposed design will result in a new intervention strategy for asthma sufferers and their doctors, in the form of a home allergen abatement service. The allergen abatement process is based on current technology. The abatement uses a concurrent spray nozzle composed of both air and dry ice (carbon dioxide). The nozzle that forms the air/dry ice spray is mounted inside a specially-designed vacuum clear head, which instantly collects both the dislodged particles as well as the CO2 as it sublimes from solid to gas. Upon vacuuming via the concurrent spray of air and dry ice, higher levels of dust are dislodged over conventional vacuuming. The research presented in this dissertation employs CFD simulations that model the spray geometry and process characteristics of a Coanda nozzle. The CFD model generates microscopic details of the fluid including the velocity, direction, flow rate, pressure, nozzle diameter and temperature as a function of air and CO2. The second objective was to determine solubility data over a range of temperature and density for the most dominant components in three essential oils as a function of temperature and density in both liquid and supercritical CO2. As a continuation from the first objective, we employed essential oils within the “dry-clean” process to prevent re-infestation. We have every reason to believe that essential oils and CO2 are soluble to do them being nonpolar however, there are some data suggesting that the solubility of the most abundant component of essential oils in supercritical CO2, there are no known data available on the solubility of the most abundant component in tea tree oil, cedar wood oil and hinoki oil at temperature ranges from 25°C to 60°C and density ranges from 0.2 g/mL to 0.7 g/mL. These oils are each a mixture of several chemical species, which greatly complicates the measurement of solubility. To address this, gas chromatography/mass spectrometry were employed to identify the major component on each oil.

The last objective of this work tested an essential oil’s ability to inactivate allergenic proteins on two well-known indoor allergens, Fel d 1 (cat) and Der f 1 (dust mite). This research addresses whether essential oils alone are able to deactivate the proteins on dry dust and quantifies it in μg of allergen per total grams of dry house dust. Mutliplex Array for Indoor Allergens (MARIA) is the primary analytical tool for evaluating the activity on each protein.