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Predictive Model Development For Adsorption Of Organic Contaminants By Carbon Nanotubes, Onur Apul
Predictive Model Development For Adsorption Of Organic Contaminants By Carbon Nanotubes, Onur Apul
All Dissertations
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 …
Adsorption Of Halogenated Aliphatic Contaminants By Graphene Nanomaterials: Comparison With Carbon Nanotubes And Granular Activated Carbons, Yang Zhou
All Theses
Graphene nanomaterials are two-dimensional single layer sp2 hybridized carbon atoms densely packed in a hexagonal honeycomb lattice and can be visualized as basic building blocks for fullerenes, carbon nanotubes (CNTs), and graphite. In addition, they are hydrophobic nanomaterials and possess a large specific surface area (SSA), thus they have been evaluated as promising adsorbents to remove synthetic organic compounds (SOCs) from water. As with granular activated carbons (GACs) and CNTs, adsorption behavior of SOCs on graphene depends on the physicochemical properties of the adsorbents (e.g., specific surface area, pore size distribution and surface chemistry), SOCs (e.g., hydrophobicity, molecular size and …