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Multivariate calibration for carbon nanotubes in the environment using the microwave induced heating method
He, Y., S. Al-Abed, AND D. Dionysios. Multivariate calibration for carbon nanotubes in the environment using the microwave induced heating method. Environmental Nanotechnology, Monitoring and Management. Elsevier B.V., Amsterdam, Netherlands, 11:100204, (2019). https://doi.org/10.1016/j.enmm.2018.100204
With mass production and wide applications of carbon nanotubes (CNTs), the release of the nanomaterials into the environment is inevitable and may cause risk to human a ecosystem health. Sensitive and reliable quantification approaches are imperative for evaluating CNTs for their fate, transport, bioaccumulation and risks in the environment. Thus, several methods have been developed to quantitatively determine quantity of CNTs in the environment, but all current methods were designed for the environmental matrix containing only single type of CNTs. However, the likelihood of presence of a mixture of different types of CNTs in the environment cannot be ignored because various types of CNTs are used in numerous applications for different purposes. The long term goal of this paper is to develop multivariate calibration approaches for simultaneously quantify a particular type of CNTs in a multicomponent environmental matrix using a microwave induced heating method. This research will assist in quantifying a mixture of CNTs in environmental matrix to predict the risk in the near and far field. This research will improve on regulating of CNTs through TSCA and exposure scenarios that EPA Regional and Program offices will benefit from as well the scientific and industrial communities.
With continuous increase in production and application of various types of carbon nanotubes (CNTs), the presence of a mixture of different types of CNTs in the environment cannot be neglected. Since distinct types of CNTs have different influences on environmental and human health, the environmental quantification of each type of CNTs has become a critical step in all CNTs-related studies. However, most of existing quantification methods have not been implemented to determine mass/concentration of individual type of CNTs in multicomponent samples. Therefore, the goal of the present paper is to develop Chemometrics-based multivariate calibration approaches for simultaneously quantifying individual type of CNTs in the environment with the microwave induced temperature rise spectra. Motivated by successful applications of partial least square regression (PLS), least square-support vector machine (LS-SVM) and artificial neural networks (ANN) in measuring specific contaminants in mixtures, the potential of applying these techniques in predicting quantities of Singlewalled CNTs, Multi-walled CNTs and carboxylate Multi-walled CNTs in environmental matrices (agricultural soil and anaerobic sludge) was investigated in this study. Our results revealed that the developed LS-SVM model presented high R2 and low root mean square error of prediction (RMSEP) in both 2-component and 3-component matrices, while the resulted ANN model was only accurate in the 2-component matrix. The PLS model was found to be ineffective in interpreting relationship between the microwave induced temperature rises and mass of CNTs as indicated by small R2 and large RMSEP.
Record Details:Record Type: DOCUMENT (JOURNAL/PEER REVIEWED JOURNAL)
Organization:U.S. ENVIRONMENTAL PROTECTION AGENCY
OFFICE OF RESEARCH AND DEVELOPMENT
NATIONAL RISK MANAGEMENT RESEARCH LABORATORY
LAND AND MATERIALS MANAGEMENT DIVISION
EMERGING CHEMISTRY AND ENGINEERING BRANCH