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A Novel Approach for Modification of Biosorbent by Silane Functionalization and its Industrial Application for Single and Multi-Component Solute System

  • Numrah Nisar , Omamah Ali , Atif Islam , Aftab Ahmad , Muhammd Yameen , Abdul Ghaffar EMAIL logo , Munawar Iqbal , Arif Nazir EMAIL logo and Nasir Masood
Published/Copyright: February 23, 2019

Abstract

The potential of an economically cheap raw material (rice husk) was evaluated in the present study to remove dyes including reactive yellow 15 (RY15) and reactive red 241 (RR241) in single and multi-component systems. The adsorbent was modified and functionalized chemically using glycidoxypropyltrimethoxysilane, sulfur and silane to enhance the removal efficiency of pollutants. The modified rice husk was evaluated by scanning electron microscope (SEM) and Fourier transform Infrared Spectroscopy (FTIR). Batch adsorption study showed that the modified rice husk with silane graft (RHSi) had highest removal efficiency of both dyes with 20% more removal compared to raw rice husk. The sorption correlated well with Langmuir, Freundlich, SIPS and Redlich-Peterson models for adsorption. Highest sorption was obtained at 10 mg L−1 of dye, 50 °C, 200 mg g−1 of adsorbent dose and pH 4. The mixture of two dyes poorly fit to the original Langmuir but fit best to the Langmuir-like model. This indicates that competitive Langmuir-like model considers that the capacities of adsorbents are equal. Results showed that the components compete for the available binding sites on adsorbent surface. It was also indicated that silane grafting can offer comparatively more binding sites compared to the raw rice husk and single-solute isotherm parameters cannot used for multi-component solute system.

Nomenclature

A

Cross sectional area (cm2)

A

Clark model parameter

aR

Redlich-Peterson model parameter (L μg−1)

b

Constant in SIPS model (L mg−1)

b

Langmuir model constant (L mg−1)

CB

Effluent concentration at breakthrough point (mg L−1)

Ce

Equilibrium dye concentration in solution (mg L−1)

Ci

Initial dye concentration in solution (mg L−1)

D

Mutual diffusion coefficient

Do

Intra-diffusion coefficient of solute

F

Linear flow rate (cm h−1)

Ka

Sorption rate constant in BDST model (L mg−1 h−1)

k1

Lagergren model constant (min−1)

k2

Rate constant of the second-order equation (g mg−1 min−1)

KF

Freundlich constant (L g−1)

KR

Redlich-Peterson model parameter (L mg−1)

kTH

Thomas model rate constant (mL min−1 ⋅ mg−1)

n

Dimensionless parameter in Freundlich model

NO

Sorption capacity in BDST model (mg L−1)

Q

Volumetric flow rate (mL min−1)

qo

Sorption capacity in Thomas model (mg g−1 of biomass)

q′max

Maximum sorption capacity in SIPS model (mg g−1)

qB

Sorption capacity in BET model (μg g−1)

qe

Equilibrium sorption capacity (mg g−1)

qmax

Maximum sorption capacity (mg g−1)

qt

Adsorption capacity after time (t) (mg g−1)

qtotal

Total amount of metal ions loaded into the column (mg L−1)

r

Clark model parameter (min−1)

R2

Determination coefficient

ttotal

Total time (min)

V

Volume of adsorbate solution (L)

Veff

Total volume of the effluent (mL)

W

Weight of biosorbent used (gram)

X

Amount of solute at equilibrium (mg)

X1

Amount of solute 1 (mg)

X2

Amount of solute 2 (mg)

Z

Bed depth of the column (cm)

ZO

Critical bed depth (cm)

θ

Fraction of the surface

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Received: 2018-07-04
Accepted: 2019-01-18
Published Online: 2019-02-23
Published in Print: 2019-11-26

©2019 Walter de Gruyter GmbH, Berlin/Boston

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