Fluoride removal from aqueous solutions using alginate beads modified with functionalized silica particles

Zare, K.; Banihashemi, Aliakbar; Javanbakht, Vahid; Mohammadifard, Hossein

doi:10.1016/j.molstruc.2021.132217

Cited by 11 publications

(2 citation statements)

References 56 publications

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“…Alginate, extracted from brown seaweed, is one of the most extensively studied natural anionic polysaccharides comprising guluronic acid and β-D-mannuronic acid units. [1,[14][15][16][17][18][19][20] It has wide applications in food and biomedical fields due to its stabilizing properties, nontoxicity, high gelation, viscosity, biodegradability, and biocompatibility. The presence of a negatively charged carboxyl group makes it a promising adsorbent for cationic dyes and heavy metals.…”

Section: Introductionmentioning

confidence: 99%

“…Conversely, the application of natural polymer‐based hydrogel beads as adsorbents has fascinated researchers due to low interfacial tension and various functional groups that can trap ionic dye, making polymer capable of high adsorption capacity. Alginate, extracted from brown seaweed, is one of the most extensively studied natural anionic polysaccharides comprising guluronic acid and β‐D‐mannuronic acid units [1,14–20] . It has wide applications in food and biomedical fields due to its stabilizing properties, nontoxicity, high gelation, viscosity, biodegradability, and biocompatibility.…”

Section: Introductionmentioning

confidence: 99%

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Investigation of Bamboo Leaves as an Alternative Source of Silica: Extraction, Characterization and Its Application as an Adsorbent for Methylene Blue Sequestration

2022

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The present study examines an alternative method for extracting silica from natural waste such as bamboo leaves (BL) via thermal combustion, followed by acid treatment and alkaline extraction. The physico-chemical properties of extracted silica were studied by comprehensive characterization tools. FESEM revealed that extracted silica is highly porous and interconnected. EDX, XRD and FTIR study confirmed the purity, amorphous nature and functional groups of extracted silica. The major interest of this paper was to functionalize extracted silica with alginate and to optimize the parameters such as pH (at 5), and equilibrium time (60 min) for the removal of methylene blue (MB) from aqueous solutions. The kinetic data was fitted well in the pseudo-second order model and the maximum adsorption capacity was found to be 54.35 mg/g. The favorability of the Langmuir isotherm suggested that the adsorption system was dominated by the monolayer adsorption process with uniform adsorption sites present on the surface. The morphological changes due to MB adsorption on prepared composites were authenticated by FTIR and DFT calculations. Therefore, the present investigation emphasizes the suitability of silica extraction from bamboo leaves waste over chemical precursors to synthesize adsorption composites.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Investigation of Bamboo Leaves as an Alternative Source of Silica: Extraction, Characterization and Its Application as an Adsorbent for Methylene Blue Sequestration

2022

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The robust fluoride-free superhydrophobic thermal energy storage coating for efficient energy storage and thermal management

Qin,

Kong,

et al. 2024

J Mater Sci

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Application of artificial neural network for prediction of fluoride removal efficiency using neutralized activated red mud from aqueous medium in a continuous fixed bed column

Giri

Mishra

2022

Environ Sci Pollut Res

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The present research work approaches the removal of uoride from aqueous medium using neutralized activated red mud (NARM) in a continuous xed bed column. Arti cial neural network (ANN) technique was applied effectively for optimization of the model for the practicability of the removal process. The consequences of various experimental variables like bed length, adsorbate concentration, experimental time and adsorbate solution ow rate studied to know the breakthrough point and saturation times. The highest removal potentiality of NARM was considered to be 3.815 mg g − 1 of F − in the bed height of 15 cm, starting concentration 1ppm, susceptible time 120 minutes, adsorbate solution ow rate 0.5 mLmin − 1 , and constant room temperature, respectively. Bohart-Adams and Thomas models were considered to describe the xed bed column effect to the bed height and adsorbate concentrations. The experimental data were applied a back propagation (BP) learning algorithm programme with four-seven-one architecture model. The arti cial neural network model was considered to be functioning correctly as absolute relative percentage error, which is 0.671 throughout the learning period. Differentiation between the predicted out comes from ANN model and actual results from experimental analysis affords a high degree of correlation (R 2 = 0.998) stipulating that the model was able to predict the adsorption e ciency. Experimented adsorbent materials was characterized using different instrumental analysis that is SEM-EDS, FTIR and XRD.

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Fluoride removal from aqueous solutions using alginate beads modified with functionalized silica particles

Cited by 11 publications

References 56 publications

Investigation of Bamboo Leaves as an Alternative Source of Silica: Extraction, Characterization and Its Application as an Adsorbent for Methylene Blue Sequestration

Investigation of Bamboo Leaves as an Alternative Source of Silica: Extraction, Characterization and Its Application as an Adsorbent for Methylene Blue Sequestration

The robust fluoride-free superhydrophobic thermal energy storage coating for efficient energy storage and thermal management

Application of artificial neural network for prediction of fluoride removal efficiency using neutralized activated red mud from aqueous medium in a continuous fixed bed column

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