Optimizing the physical-chemical properties of carbon nanotubes (CNT) and graphene nanoplatelets (GNP) on Cu(II) adsorption.

Systematic experiments of copper adsorption on 10 different commercially available nanomaterials were studied for the influence of physical-chemical properties and their interactions. Design of experiment and response surface methodology was used to develop a polynomial model to predict maximum copper adsorption (initial concentration, Co=10mg/L) per mass of nanomaterial, qe, using multivariable regression and maximum R-square criterion. The best subsets of properties to predict qe in order of significant contribution to the model were: bulk density, ID, mesopore volume, tube length, pore size, zeta-charge, specific surface area and OD. The highest experimental qe observed was for an alcohol-functionalized MWCNT (16.7mg/g) with relative high bulk density (0.48g/cm(3)), ID (2-5nm), 10-30μm long and OD<8nm. Graphene nanoplatelets (GNP) showed poor adsorptive capacity associated to stacked-nanoplatelets, but good colloidal stability due to high functionalized surface. Good adsorption results for pristine SWCNT indicated that tubes with small diameter were more associated with good adsorption than functionalized surface. XPS and ICP analysis explored surface chemistry and purity, but pHpzc and zeta-charge were ultimately applied to indicate the degree of functionalization. Optimum CNT were identified in the scatter plot, but actual manufacturing processes introduced size and shape variations which interfered with final property results.