Heavy metal adsorbents prepared from the modification of cellulose: A review

O’Connell, David; Birkinshaw, C.; O’Dwyer, Thomas F.

doi:10.1016/j.biortech.2008.01.036

Cited by 1,176 publications

(532 citation statements)

References 113 publications

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“…Cellulose is one such adsorbent that has been investigated for the adsorption of heavy metal ions (Isobe et al, 2013;O'Connell et al, 2008a). Cellulose is the most abundant natural, renewable, and biodegradable polymer and as a raw material is available at relatively low cost for the preparation of various functional polymers (O'Connell et al, 2008a).…”

Section: Introductionmentioning

confidence: 99%

Predicting the capability of carboxylated cellulose nanowhiskers for the remediation of copper from water using response surface methodology (RSM) and artificial neural network (ANN) models

Hamid

Jenidi

Thielemans

et al. 2016

Industrial Crops and Products

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This study observed the influence of temperature, initial Cu(II) ion concentration, and sorbent dosage on the Cu(II) removal from the water matrix using surface-oxidized cellulose nanowhiskers (CNWs) bearing carboxylate functionalities. In addition, this study focused on the actual conditions in a wastewater treatment plant. Conductometric titration of CNWs suspensions showed a surface charge of 54 and 410 mmol/kg for the unmodified and modified CNWs, respectively, which indicated that the modified CNWs provide a relatively high surface area per unit mass than the unmodified CNWs. In addition, the stability of the modified CNWs was tested under different conditions and proved that the functional groups were permanent and not degraded. Response surface methodology (RSM) and artificial neural network (ANN) models were employed in order to optimize the system and to create a predictive model to evaluate the Cu(II) removal performance of the modified CNWs. The performance of the ANN and RSM models were statistically evaluated in terms of the coefficient of determination (R 2 ), 2 absolute average deviation (AAD), and the root mean squared error (RMSE) on predicted experiment outcomes. Moreover, to confirm the model suitability, unseen experiments were conducted for 14 new trials not belonging to the training data set and located both inside and outside of the training set boundaries. Result showed that the ANN model (R 2 =0.9925, AAD = 1.15%, RMSE = 1.66) outperformed the RSM model (R 2 =0.9541, AAD = 7.07%, RMSE = 3.99) in terms of the R 2 , AAD, and RMSE when predicting the Cu (II) removal and is thus more reliable. The Langmuir and Freundlich isotherm models were applied to the equilibrium data and the results revealed that Langmuir isotherm (R 2 = 0.9998) had better correlation than the Freundlich isotherm (R 2 = 0.9461). Experimental data were also tested in terms of kinetics studies using pseudo-first order and pseudo-second order kinetic models. The results showed that the pseudo-second-order model accurately described the kinetics of adsorption.

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Section: Introductionmentioning

confidence: 99%

Predicting the capability of carboxylated cellulose nanowhiskers for the remediation of copper from water using response surface methodology (RSM) and artificial neural network (ANN) models

Hamid

Jenidi

Thielemans

et al. 2016

Industrial Crops and Products

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“…Various heavy metal ions such as lead (Pb), cadmium (Cd), chromium (Cr), copper (Cu), nickel (Ni), zinc (Zn) and mercury (Hg) are product of industrial wastewaters mainly from industry that processes metal plating, mining, and paint [7]. Substantial amounts of heavy metals was introduced into the atmosphere, aquatic and environment, leading to the increase of heavy metal exposure [8]. Heavy metals cannot be degraded by their own.…”

Section: Introductionmentioning

confidence: 99%

“…Cadmium causes nephrotoxic effects. With its long term exposure, it may cause bone damage [8]. Based on World Health Organization (WHO), the permissible limit in waste water for lead is 0.015 mg/L and cadmium is 0.01 mg/L [9].…”

Section: Introductionmentioning

confidence: 99%

NanoCrystalline Cellulose isolated from oil palm empty fruit bunch and its potential in cadmium metal removal

Lim

Chew

Choong

et al. 2016

MATEC Web of Conferences

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Abstract. NanoCrystalline Cellulose (NCC) was isolated via ultrasonic cavitation assisted acid hydrolysis method. Characterization was done using Dynamic Light Scattering (DLS) together with Scanning Electron Microscope (SEM) imaging to double prove the existence of NCC. DLS measures length of 236.6 nm with width of 34.40 nm, supported by SEM which showed NCC a rod-like shaped particle with large surface area and high porosity. It was then attempted for heavy metal cadmium ion (Cd 2+ ) removal from aqueous solution. The pH implication to the rate of Cd 2+ adsorption was investigated by varying the solution to pH 4, pH 7 and pH 10 over a duration of 120 minutes. The removal efficiency was analyzed using Atomic Absorption Spectroscopy (AAS) resulting in pH 7 being the most favorable for Cd 2+ removal.

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“…However, in these days, one of the key reasons of pollution in surface and ground waters is using the large scale of insecticides and pesticides in agriculture. Due to extensive use, safe, efficient, and economic strategies for their elimination were attracted so much attention [2]. In this, hence, the nanoparticles can play major roles for the treatment of natural waters, soils, sediments, industrial, and domestic waste water.…”

Section: Introductionmentioning

confidence: 99%

Carboxylated carbon nanotubes as an efficient and cost-effective adsorbent for sustainable removal of insecticide fenvalerate from contaminated solutions

2016

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In this study, carboxylic multiwall carbon nanotubes (CMNTs) were used as an adsorbent for removing fenvalerate as a toxic insecticide from solution through batch experiments. The influence of four independent parameters of HCl, initial fenvalerate concentration, CMNTs dosage, and contact time on the fenvalerate adsorption process was investigated. Raman spectroscopy and thermogravimetric analysis confirmed that the adsorption and maximum adsorption capacity (40.0 mg g -1 ) showed high adsorption potential of the proposed sorbent. The kinetic, isothermic, and thermodynamic of fenvalerate adsorptionon CMNTs were evaluated to better understand this environmental friendly adsorption strategy. A pseudo-first-order kinetic described very well the experimental data of the adsorption kinetics. The experimental data found to be properly fitted to Freundlich model, which indicates that the sorption takes place on a heterogeneous material. The thermodynamic results showed the negative value of the standard free energy (DG 0 ) and standard enthalpy change (DH 0 ) showing an exothermic and spontaneous system. Repeated availability of adsorbent investigated and SEM and HRTEM of reused adsorbent showed stability and non-aggregatable attributes of CMNTs.

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Heavy metal adsorbents prepared from the modification of cellulose: A review

Cited by 1,176 publications

References 113 publications

Predicting the capability of carboxylated cellulose nanowhiskers for the remediation of copper from water using response surface methodology (RSM) and artificial neural network (ANN) models

Predicting the capability of carboxylated cellulose nanowhiskers for the remediation of copper from water using response surface methodology (RSM) and artificial neural network (ANN) models

NanoCrystalline Cellulose isolated from oil palm empty fruit bunch and its potential in cadmium metal removal

Carboxylated carbon nanotubes as an efficient and cost-effective adsorbent for sustainable removal of insecticide fenvalerate from contaminated solutions

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