Magnetic chitosan nanoparticles for removal of Cr(VI) from aqueous solution

Thinh, Nguyen Ngoc; Hanh, Pham Thi Minh; Ha, L.T.; Anh, Lê Ngoc; Hoang, Tran Vinh; Hoàng, Vũ Đình; Dang, Le Hai; Khôi, Nguyễn Văn; Лам, Тран Дай

doi:10.1016/j.msec.2012.12.013

Cited by 157 publications

(59 citation statements)

References 30 publications

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“…Above the pKa, the chitosan will be less protonated or neutral, and hence, Cr removal is reduced at pH higher than the pKa. Results corroborate maximum capture efficiency at pH 3, as below this pH, Cr exists in solution in the form of H 2 CrO 4 the strong competition for adsorption sites between H 2 CrO 4 and protons [27].…”

Section: Effect Of Ph On Percentage Removal Of Total Crsupporting

confidence: 68%

“…However, for an economically efficient remediation process, a minimum dose of adsorbent with higher removal efficiency is desirable. ANN-based output clearly indicates that the higher removal efficiency could be obtained at low-dose condition (0.5 mg/ml) assisted by low pH condition (2 and 3) and moderate temperature (25)(26)(27)(28)(29)(30)Figs. 6,8).…”

Section: Effect Of Nanoparticles Dose On Cr Removal Efficiencymentioning

confidence: 96%

“…The iron nanoparticles were also found to be effective for the detoxification of chlorinated compounds (chlorinated organic solvents, organochlorine pesticides, trinitrotoluenes, phenols, herbicide molinateetc [20,21]. Surface modification of INPs with biopolymers such as chitosan not only increases the stability of the bare INPs in the aqueous environment [22][23][24], but also increases its adsorption potential against the heavy metal pollutants [25][26][27]. Application of chitosan as oligosaccharide may solve the solubility issue for environmental and biological applications.…”

Section: Introductionmentioning

confidence: 99%

“…They have reported the outperformance of the ANN over the RSM for the prediction of the nonlinear behaviour of the system. Yetilmezsoy and Demirel [27] have utilized three-layer artificial neural network (ANN) model to predict the Pb ion removal efficiency of Antep pistachio (Pistacia vera) shells, from the aqueous solution. They report that the ANN model exhibited a good prediction of the experimental data.…”

Section: Introductionmentioning

confidence: 99%

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An artificial neural network (ANN)-based framework for the Cr removal from the spiked water samples by chitosan oligosaccharide-coated iron oxide nanoparticles

Shukla

Kumar

Prakash

et al. 2017

Nanotechnol. Environ. Eng.

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Chromium contamination in water has become a major concern worldwide due to its adverse health effects. Chitosan oligosaccharide-coated iron oxide nanoparticles (CSO-INPs) were used in the present study for the magnetic separation of chromium from a chromium spiked water samples. Transmission electron microscope-energydispersive X-ray spectroscopy elemental mapping and scanning electron microscope-energy-dispersive X-ray spectroscopy elemental analysis were carried out to confirm the successful removal of the contaminant (total Cr) from the spiked water samples. A feedforward artificial neural network (ANN) model has been developed to predict the optimum efficiency of chromium ions removal from aqueous solution by CSO-INPs. Both the batch experiments and the ANN have been applied to assess the impact of various factors such as pH, nanoparticles dose, temperature, and time influencing the Cr removal efficiency of CSO-INPs. Removal efficiency has been found to be higher at low pH, with higher dose of nanoparticles at higher temperature. The ANN simulation further gives us a set of desired conditions (pH 3, CSO-INPs dose 0.7 mg/ml, temperature 28-30°C, time 60 min) to achieve an optimum Cr removal efficiency of CSO-INPs. Graphical AbstractKeywords Chromium Á Chitosan oligosaccharide Á Iron nanoparticles Á Artificial neural network (ANN)

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Section: Effect Of Ph On Percentage Removal Of Total Crsupporting

confidence: 68%

Section: Effect Of Nanoparticles Dose On Cr Removal Efficiencymentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An artificial neural network (ANN)-based framework for the Cr removal from the spiked water samples by chitosan oligosaccharide-coated iron oxide nanoparticles

Shukla

Kumar

Prakash

et al. 2017

Nanotechnol. Environ. Eng.

View full text Add to dashboard Cite

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“…e e e max L max To examine the effect of temperature, adsorption experiments were also conducted at 298 K, 308 K and 318 K. The experimental data obtained at different temperatures were used for calculating the thermodynamic parameters, such as Gibbs free energy (ΔG), enthalpy (ΔH) and entropy (ΔS) according to the following equations [30]:…”

Section: Adsorption Modelsmentioning

confidence: 99%

Methylene Blue Adsorption by Novel Magnetic Chitosan Nanoadsorbent

Zhu

Zhang

Yan

2016

J. of Wat. & Envir. Tech.

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A novel magnetic nanoadsorbent (magnetic chitosan modified by N,N-bis (carboxymethyl) glutamic acid, G-MCTS for short) was prepared by covalent binding of tetrasodium of N,N-bis (carboxymethyl) glutamic acid onto the surface of chitosan-coated Fe 3 O 4 nanoparticles. The adsorbent was characterized by scanning electron microscopy, infrared spectrum, vibrating sample magnetometer and X-ray powder diffractometer. It was found that G-MCTS had a spherical structure with a particle size ranging from 100 − 150 nm and a saturation magnetization value of 21 emu/g. Meanwhile, the adsorption performances of G-MCTS were tested with adsorption of methylene blue. Correspondingly, the adsorption effect factors (initial concentration, solution pH, contact time and temperature), adsorption kinetics, isotherms and adsorption thermodynamics were investigated in detail. Results showed that the adsorption could reach equilibrium within 30 min, besides, the adsorption kinetics accepted the pseudo-second-order kinetic model, and the adsorption isotherm data fit with Freundlich model as well as Langmuir model. More importantly, the maximum adsorption capacity was 3.3 g/g obtained by Langmuir model and the adsorption capacity was more than 90% of the initial saturation adsorption capacity after being used for four times. All of these results indicated that, G-MCTS can serve as an effective adsorbent for the adsorption of methylene blue.

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