Correlation and prediction of adsorption capacity and affinity of aromatic compounds on carbon nanotubes. (1st January 2016) - Wu, Wenhao; Yang, Kun; Chen, Wei; Wang, Wendi; Zhang, Jie; Lin, Daohui; Xing, Baoshan
Abstract: Adsorption of 22 nonpolar and polar aromatic compounds on 10 carbon nanotubes (CNTs) with various diameters, lengths and surface oxygen-containing group contents was investigated to develop predictive correlations for adsorption, using the isotherm fitting of Polanyi theory-based Dubinin-Ashtakhov (DA) model. Adsorption capacity of aromatic compounds on CNTs is negatively correlated with melting points of aromatic compounds, and surface oxygen-containing group contents and surface area ratios of mesopores to total pores of CNTs, but positively correlated with total surface area of CNTs. Adsorption affinity is positively correlated with solvatochromic parameters of aromatic compounds, independent of tube lengths and surface oxygen-containing group contents of CNTs, but negatively correlated with surface area ratios of mesopores to total pores of CNTs. The correlations of adsorption capacity and adsorption affinity with properties of both aromatic compounds and CNTs clearly have physical significance, can be used successfully with DA model to predict adsorption of aromatic compounds on CNTs from the well-known physiochemical properties of aromatic compounds (i.e., solvatochromic parameters, melting points) and CNTs (i.e., surface area and total acidic group contents), and thus can facilitate the environmental application of CNTs as sorbents and environmental risk assessment of both aromatic contaminants and CNTs. Graphical abstract: Highlights: Adsorption of 22 aromatic compounds on 10 CNTs all can be fitted well by DA model. Correlations of adsorption with properties of both aromatics and CNTs were obtained. LSERs approach based on DA model and solute solvatochromic parameters was applied. Correlations are solute concentration-independent and with physical significance. Correlations can be used successfully to predict adsorption of aromatics on CNTs.