Date of Award
8-2014
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Legacy Department
Environmental Engineering and Earth Science
Committee Chair/Advisor
Dr. Tanju Karanfil
Committee Member
Dr. Brian Powell
Committee Member
Dr. Cindy Lee
Committee Member
Dr. Steve Klaine
Abstract
The main objective of the study was to investigate mechanisms and statistical modeling of synthetic organic contaminant (SOC) adsorption by carbon nanotubes (CNTs). First, predictive models were developed for adsorption of low molecular weight aromatic compounds by multi-walled carbon nanotubes (MWCNTs) using experimental data for 59 compounds. Quantitative structure-activity relationship (QSAR) and linear solvation energy relationship (LSER) approaches were employed and developed models were externally validated using an independent dataset obtained from the literature. Up to date, no QSAR model has been reported for predicting adsorption of organics by CNTs. No LSER model is available which comprehensively investigates the adsorption of organics on CNTs. Only recently, one study reported an LSER equation for the modeling of their experimental adsorption data on one MWCNT. Then, adsorption of ten environmentally relevant halogenated aliphatic SOCs by a single walled (SWCNT) and MWCNT was tested experimentally for the first time in the literature. Several LSER models were developed to further examine the adsorption mechanisms. The LSER equations constitute the first predictive models generated for adsorption of aliphatic SOCs by CNTs. In addition, the poly-parameter LSER model was compared to those previously generated for adsorption of aromatic SOCs by CNTs. The LSER model generated in this research is currently the most comprehensive models available in the literature. Finally, the role of carbon nanotube morphology (i.e. surface area, diameter, and length) on the adsorption of phenanthrene (PNT) was investigated by analyzing the adsorption isotherms obtained with several SWCNTs and MCWNTs in the laboratory and the literature. The QSAR (r2 = 0.88), and LSER (r2 = 0.83) equations and their external validation accuracies indicated the success of parameter selection, data fitting ability, and the prediction strength of the developed models. These models were developed for adsorption of low-molecular weight (/mol) aromatic SOCs by MWCNTs (with less than 5% oxygen content) in distilled and deionized water. For aromatic SOC adsorption models, the molecular volume term (V) of the LSER model was the most influential descriptor controlling adsorption at all concentrations. At higher equilibrium concentrations, hydrogen bond donating (A) and hydrogen bond accepting (B) terms became significant in the models. For halogenated aliphatic SOC adsorption models, at higher concentrations, the B parameter, capturing hydrogen bond accepting ability, was the most influential descriptor both for SWCNT and MWCNT. The negative dependence on B indicates that as the hydrogen bond accepting ability of an aliphatic compound increases, it becomes less likely to be adsorbed by CNTs. The other important LSER parameters were V (size) followed by P (polarizability), and they were positively correlated with adsorption, indicating that size and polarizability favors adsorption. The contribution of these parameters was 2 - 3 times less than the B parameter. However, there was no single parameter predominant in the aliphatic SOC models. The number of data points for aliphatic SOCs were much smaller than aromatic models. These results indicated that adsorption of aromatic SOCs by CNTs strongly depend on adsorbate hydrophobicity; while for aliphatic SOCs, in addition to hydrophobic driving force, other interactions (i.e., hydrogen bond accepting ability) also play a role. Additional investigation of CNT properties on adsorption of PNT showed that at low (e.g., 1 μg/L) equilibrium concentrations, MWCNTs with the larger outer diameters exhibit higher adsorption capacity on a specific surface area basis than those with smaller diameters. With increasing equilibrium concentration, adsorption on a specific surface area basis becomes independent of MWCNT diameter, and maximum adsorption capacity was controlled by the total surface area. A similar analysis for the adsorption of naphthalene (NPT), a planar molecule with one less benzene ring but twenty times higher solubility than PNT, showed no correlation with respect to MWCNT outer diameter at both low and high equilibrium concentrations. The results indicated that the surface curvature of MWCNT was more important on the adsorption of PNT than on the adsorption of NPT due to its smaller molecular size and lower adsorption capacity than PNT. Specific surface area normalized isotherms did not show a correlation between PNT adsorption and lengths of SWCNTs and MWCNTs. Carbon nanotube characterization results showed that the morphology of CNTs impacts their aggregation and plays an important role on the available surface area and pore volume for adsorption. Manufacturer's data may not always represent the characteristics of CNTs in a particular batch. Therefore, accurate characterization of CNTs is essential to systematically examine the behavior of CNTs (e.g., adsorption, transport) in environmental systems. A fundamental understanding of CNT-SOC adsorption interactions is important to (i) assess the environmental implications of CNT releases and spills to natural waters, and their roles as the contaminant carriers in the environment and, (ii) evaluate the potentials of CNTs as adsorbents in water and wastewater treatment applications. Predictive LSER modeling can be used to gain insight to the adsorption mechanisms by examining the individual contribution of intermolecular interactions to overall adsorption. This study examined and showed adsorption mechanisms and CNT properties (such as surface area, pore volume, outer diameter, and surface oxygen content) on the adsorption behavior of different classes of SOCs by CNTs.
Recommended Citation
Apul, Onur, "Predictive Model Development for Adsorption of Organic Contaminants by Carbon Nanotubes" (2014). All Dissertations. 1290.
https://tigerprints.clemson.edu/all_dissertations/1290