Structural, optical, XPS and magnetic properties of Zn particles capped by ZnO nanoparticles

Morozov, Yu. G.; Белоусова, О. В.; Ortega, Daniel; Mafina, Marc-Krystelle; Kuznetcov, M.V.

doi:10.1016/j.jallcom.2015.01.285

Cited by 138 publications

(56 citation statements)

References 79 publications

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“…These peaks are compatible with the standard XRD data for the hexagonal Zn lattice (JCPDS file 04-0831) ( Figure 6) [43]. The characteristic peaks of ZnO at 32 • and 34.7 • are assigned to (100) and (002) facets [44,45].…”

Section: Characterization Of the Commercially Available Nzvzsupporting

confidence: 84%

Modeling of Malachite Green Removal from Aqueous Solutions by Nanoscale Zerovalent Zinc Using Artificial Neural Network

Ruan

Shi

et al. 2017

Applied Sciences

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Abstract:The commercially available nanoscale zerovalent zinc (nZVZ) was used as an adsorbent for the removal of malachite green (MG) from aqueous solutions. This material was characterized by X-ray diffraction and X-ray photoelectron spectroscopy. The advanced experimental design tools were adopted to study the effect of process parameters (viz. initial pH, temperature, contact time and initial concentration) and to reduce number of trials and cost. Response surface methodology and rapidly developing artificial intelligence technologies, i.e., artificial neural network coupled with particle swarm optimization (ANN-PSO) and artificial neural network coupled with genetic algorithm (ANN-GA) were employed for predicting the optimum process variables and obtaining the maximum removal efficiency of MG. The results showed that the removal efficiency predicted by ANN-GA (94.12%) was compatible with the experimental value (90.72%). Furthermore, the Langmuir isotherm was found to be the best model to describe the adsorption of MG onto nZVZ, while the maximum adsorption capacity was calculated to be 1000.00 mg/g. The kinetics for adsorption of MG onto nZVZ was found to follow the pseudo-second-order kinetic model. Thermodynamic parameters (∆G 0 , ∆H 0 and ∆S 0 ) were calculated from the Van't Hoff plot of lnKc vs. 1/T in order to discuss the removal mechanism of MG.

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Section: Characterization Of the Commercially Available Nzvzsupporting

confidence: 84%

Modeling of Malachite Green Removal from Aqueous Solutions by Nanoscale Zerovalent Zinc Using Artificial Neural Network

Ruan

Shi

et al. 2017

Applied Sciences

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“…Particularly, highly disordered brown-black ZnO warrants further attention for magneto-optic investigations and enthusiastic efforts have been started in this direction [51]. …”

Section: Discussionmentioning

confidence: 99%

Low temperature photoluminescence from disordered granular ZnO

Pal

Sarkar²,

Kumar

et al. 2016

Journal of Luminescence

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“…FromFig. 9(c), Zn 2p 3/2 and Zn 2p 1/2 peaks are located at 1022.0 and 1045.0 eV, respectively, which were the characteristics of Zn(II)[61,62]. FromFig.…”

mentioning

confidence: 85%

Studies on the optimum conditions using acid-washed zero-valent iron/aluminum mixtures in permeable reactive barriers for the removal of different heavy metal ions from wastewater

Han

Cheng

et al. 2016

Journal of Hazardous Materials

139

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Structural, optical, XPS and magnetic properties of Zn particles capped by ZnO nanoparticles

Cited by 138 publications

References 79 publications

Modeling of Malachite Green Removal from Aqueous Solutions by Nanoscale Zerovalent Zinc Using Artificial Neural Network

Modeling of Malachite Green Removal from Aqueous Solutions by Nanoscale Zerovalent Zinc Using Artificial Neural Network

Low temperature photoluminescence from disordered granular ZnO

Studies on the optimum conditions using acid-washed zero-valent iron/aluminum mixtures in permeable reactive barriers for the removal of different heavy metal ions from wastewater

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