An exploratory study using QICAR models for prediction of adsorption capacity of multi-walled carbon nanotubes for heavy metal ions.

Abstract:

:The Quantitative Ion Character-Activity Relationship (QICAR) method was used for correlating metal ionic characteristics with the maximum adsorption capacity (qmax) of multi-walled carbon for heavy metals. The experimental values of qmax for 25 heavy metal ions, estimated by the Langmuir isotherm model, were used to construct a QICAR model. The genetic algorithm, enhanced replacement method and successive projection algorithm procedures were applied as variable selection algorithms to choose the optimal subsets of descriptors. The selected variables were correlated with qmax values by using partial least squares (PLS) regression. Orthogonal signal correction was applied as a pre-processing technique. Among of different variable selection methods, the enhanced replacement method displayed noticeable statistical parameters of the final model. The results of the enhancement replacement method-orthogonal correction signal-PLS model, with RMSEC = 0.733, r2c = 0.999 and r2p = 0.946, were excellent and dramatically better than those of other models. The developed QICAR model satisfied the internal and external validation criteria. The importance of electronegativity, ionic radius and atomic number of the heavy metal ions indicated the impact of the tendency to accept electrons and the size of ions in adsorption on carbon nanotubes.

journal_name

SAR QSAR Environ Res

authors

Salahinejad M,Zolfonoun E

doi

10.1080/1062936X.2018.1538059

subject

Has Abstract

pub_date

2018-12-01 00:00:00

pages

997-1009

issue

12

eissn

1062-936X

issn

1029-046X

journal_volume

29

pub_type

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