Graphene oxide/polyamidoamine dendrimers (GO/PAMAMs) were prepared via a "grafting to" method. The adsorption behavior of the GO/ PAMAMs for Pb(II), Cd(II), Cu(II), and Mn(II) was studied, and the effects of solution pH, adsorption time, and initial metal ion concentration on adsorption capacity of the adsorbent were also investigated. The pseudo-first-order and pseudo-second-order kinetic models were used to describe the kinetic processes, and the results indicated that the adsorption of Pb(II), Cd(II), Cu(II), and Mn(II) followed a second-order type reaction kinetics and the adsorption of Pb(II), Cd(II), Cu(II), and Mn(II) onto GO/PAMAMs is a chemical adsorption. The adsorption capacities of GO/PAMAMs were found to be 568.18, 253.81, 68.68, and 18.29 mg/g for Pb(II), Cd(II), Cu(II), and Mn(II), respectively. The adsorption reached equilibrium within 60 min and characteristics of the adsorption process were evaluated by using the Langmuir and Freundlich isotherm models. The adsorption processes fit better with the Langmuir model for Cu(II) and Mn(II) than for Pb(II) and Cd(II); the adsorption of Cu(II) and Mn(II) on GO/PAMAMs was a typical monomolecular layer adsorption. ■ INTRODUCTIONThere are plenty of mineral resources in Western Hunan in China; however, a lot of wastewater and waste residue containing heavy metal ions affect sustainable exploitation and utilization of the mineral resources. Water pollution by heavy metal ions has become an urgent problem to be solved.Adsorptive removal of heavy metal ions has been widely applied using such materials as activated carbon, 1−4 multiwalled carbon nanotubes, 5−8 zeolites, 9−12 chitosan, 13−20 metal oxide, 21,22 polymer absorbents, 23 and agricultural byproducts. 24,25 Recently, some effective adsorbents based on graphene and graphene composites were made and applied in removing heavy metal ions. 26−34 For example, the polypyrrole− reduce graphene oxide composite showed a highly selective removal capacity with a high Hg 2+ adsorption capacity of 980 mg·g −1 and an extremely high desorption rate of up to 92.3 %, showing practical utility for wastewater treatment. 26 Graphene oxide (GO) aerogels prepared by a unidirectional freeze-drying method were used as an effective adsorbent for Cu 2+ removal from water. 28 Deng et al. found that the functionalized graphene could be fabricated by a simple and fast method of electrolysis with potassium hexafluorophosphate solution as electrolyte under the static potential of 15 V; the adsorption processes reached equilibrium in just 40 min and the adsorption isotherms were described well by Langmuir and Freundlich classical isotherms models. 33 Polyamidoamine dendrimers (PAMAMs) are highly reactive because of the presence of a large amount of terminal functional groups. 35,36 Mamadou et al. 37 found that the Cu(II) binding capacities of the EDA core PAMAM dendrimers were much larger and more sensitive to solution pH than those of linear polymers with amino groups, and the metal ion laden dendrimers can be regenerated by decreas...

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a Two novel algorithms which employ the idea of stacked generalization or stacked regression, stacked partial least squares (SPLS) and stacked moving-window partial least squares (SMWPLS) are reported in the present paper. The new algorithms establish parallel, conventional PLS models based on all intervals of a set of spectra to take advantage of the information from the whole spectrum by incorporating parallel models in a way to emphasize intervals highly related to the target property. It is theoretically and experimentally illustrated that the predictive ability of these two stacked methods combining all subsets or intervals of the whole spectrum is never poorer than that of a PLS model based only on the best interval. These two stacking algorithms generate more parsimonious regression models with better predictive power than conventional PLS, and perform best when the spectral information is neither isolated to a single, small region, nor spread uniformly over the response. A simulation data set is employed in this work not only to demonstrate this improvement, but also to demonstrate that stacked regressions have the potential capability of predicting property information from an outlier spectrum in the prediction set. Moisture, oil, protein and starch in Cargill corn samples have been successfully predicted by these new algorithms, as well as hydroxyl number for different instruments of terpolymer samples including and excluding an outlier spectrum.

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