Journal of Chemistry

Volume 2018, Article ID 2124845, 12 pages

https://doi.org/10.1155/2018/2124845

## Kinetic Study of the Bioadsorption of Methylene Blue on the Surface of the Biomass Obtained from the Algae *D. antarctica*

^{1}Department of Chemistry, Sciences Faculty, Research Group in Porous Solids and Calorimetry, University of the Andes, Bogota 111711, Colombia^{2}Departamento de Química, Facultad de Ciencias, Universidad Nacional de Colombia, Bogota 111321, Colombia

Correspondence should be addressed to Juan Carlos Moreno-Pirajan; oc.ude.sednainu@oneromuj

Received 9 March 2018; Revised 17 April 2018; Accepted 22 April 2018; Published 14 June 2018

Academic Editor: Carlos A. Martínez-Huitle

Copyright © 2018 Jhonatan R. Guarín et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### Abstract

Currently, there is a great pollution of water by the dyes; due to this, several studies have been carried out to remove these compounds. However, the total elimination of these pollutants from the aquatic effluents has represented a great challenge for the scientific community, for which it is necessary to carry out investigations that allow the purification of water. In this work, we studied the bioadsorption of methylene blue on the surface of the biomass obtained from the algae *D. antarctica*. This material was characterized by SEM and FTIR. To the data obtained in the biosorption experiments, different models of biosorption and kinetics were applied, finding that the best fit to the obtained data is given by applying the pseudo-second-order models and the Toth model, respectively. It was also determined that the maximum adsorption capacity of MB on the surface of the biomass is 702.9 mg/g, which shows that this material has great properties as a bioadsorbent.

#### 1. Introduction

Water pollution by various industries is the main problem the world is facing these times. Among these pollutants are the dyes [1, 2]; their world production per year is approximately 7 × 10^{5} MT, and around 10 to 15% of the dyes used are dumped in waste water [3]. Synthetic dyes are more difficult to remove than natural dyes [4], and this is due to their complex aromatic structure, which gives them stability against air and light [1]. They can easily transport within the aqueous environment due to their high solubility in water [5]. They affect the aquatic autotrophs by restricting their photosynthetic efficiency because only limited sunlight is allowed to penetrate due to their colour; their toxic effect spreads along the food chain, and they are conserved for long periods deteriorating animal and human health [1].

Methylene blue (MB) is a cationic dye with broad applications such as dye for paper, hair, and cotton and filters for medical surgery [2] among others. This pollutant not only deteriorates water quality but also significantly affects the environment and human health [6]. It has been shown that, in humans, it causes vomiting, lightheadedness, cyanosis, jaundice, tissue necrosis [2], increased heart rate, vomiting, shock, and tetraplegia [7]. Therefore, there is a need to eliminate this dye present in wastewater or industrial effluents to ensure a safer environment [2]. This and the other dyes are difficult to degrade biologically, so the studies aimed at removing these contaminants present in aqueous solution are important and must be carried out [8, 9] to reduce environmental damage and human health.

Various technologies, including adsorption, flocculation, membrane filtration, electrolysis, biological treatments, oxidation [10], sedimentation, membrane separation, reverse osmosis [8], and photocatalytic degradation [11], have been adopted to remove dyes from sewage water. Among the mentioned treatments, adsorption has some advantages because the adsorbents are inexpensive, are available, are simple to use, and have high efficiency [8] and their design is simple [3]. However, the total removal of MB from the wastewater has not been achieved; therefore, it is necessary to continue with the studies to discover new bioadsorbents [6].

Many adsorbents have been studied to reduce the concentration of the dyes present in aqueous solutions, among which the activated carbon stands out for its high efficiency; however, its manufacture and regeneration involve a high cost. So, they have discovered and applied other natural adsorbents such as natural coal, chitin, chitosan, fly ash, wood sawdust, and rice husk [8].

Adsorption using biomass is considered a potential technique for the removal of contaminants present in water, and the advantage of using this adsorbent is that it is more economical than commercial adsorbents [12]. The scope of this research is to perform the kinetic study of the MB adsorption on the surface of the biomass obtained from the algae *D. antarctica* and to determine the capacity of adsorption of the contaminant (MB) by the bioadsorbent. To understand the mechanism of adsorption of this process, different kinetic and adsorption models were applied to the obtained data. Additionally, traditional instrumental techniques were used to characterize the bioadsorbent.

#### 2. Materials and Methods

##### 2.1. Preparation of the Biomass

Biomass brown alga was collected from the Chilean coast, for preparing samples of fresh alga washed with distilled water to remove impurities, and dried at 40°C using an oven (Memmert, Germany) for 72 hours; once the drying process was finished, the material was cut into small pieces, before being grounded, and the dried biomass was sieved to a particle size of 500–1000 *μ*m. This material was used in all experiments [13].

##### 2.2. Characterization

In order to evaluate the properties of the biomass surfaces obtained from the algae *D. antarctica*, which allow MB adsorption to be effective, this material was characterized by the techniques provided below.

###### 2.2.1. Infrared Spectroscopy

The data of the IR spectra of the biomass before and after the adsorption of MB were recorded using an instrument SHIMADZU IRTracer-100. The pressed granules were prepared by grinding the biomass and mixing it with KBr in an agate mortar. The spectral data were recorded at wavenumber values between 4000 and 500 cm^{−1}.

###### 2.2.2. Scanning Electron Microscopy

This technique was used to observe the morphology of the biomass surface before and after the MB adsorption process in a JEOL JSM-6490LV unit. For the SEM analysis, the sample obtained after the MB adsorption process was separated from the solution and dried at a temperature of 120°C for 5 h. Before carrying out this analysis, the surface of the biomass was coated with gold using the sputtering method to obtain a conductive surface.

##### 2.3. Studies of the Biosorption of the Function of the pH

For the determination of the optimum pH of biosorption, methylene blue solutions of 50 ppm were prepared, whose pH was adjusted to values of 3, 5, 7, 9, and 11, after which the biomass was added in a ratio of 1 g/L, the samples were left in constant agitation for a period of 15 hours, and the MB concentration was determined at the beginning and end of the bioadsorption process by UV-Vis spectroscopy at a wavelength of 664 nm in a GENESYS 5 spectrophotometer.

##### 2.4. Studies of Adsorption Kinetics

To prepare the kinetic studies, solutions of 25, 50, 100, 150, and 200 ppm of MB were prepared. According to the results obtained in Section 3.2, the optimum pH value of adsorption must be above 5; therefore, the pH of the solutions was adjusted to a value of 10 using 0.1 M·HCl and NaOH solutions. After this, the biomass was added in a ratio of 1 g/L, the samples were left in agitation, and aliquots were taken at 0, 5, 10, 15, 30, 60, 120, 240, 360, 480, and 560 minutes, to track the decrease in MB concentration present in the solution. Using (1), the values of *q*_{t} were determined for the different kinetic experiments carried out:where is the amount of MB adsorbed per gram of the sample (mg/g) in time () of the adsorption process, is the initial concentration of the solution (mg/L), is the concentration of the solution in time () of the adsorption process (mg/L), is the initial volume of the solution, and is the biomass added to the different solutions [14].

##### 2.5. Studies of Equilibrium in the Solid-Liquid Interface

To understand the mechanism of adsorption of methylene blue on the surface of the biomass, solutions were prepared with initial concentrations of 25, 50, 100, 150, 200, 400, 600, 800, 100, and 1400 ppm of this contaminant; the pH of the solutions that were in the concentration range of 25 to 200 ppm was adjusted to a value of 10, and the pH value of the solutions that were in the concentration range of 400 to 1400 ppm was not adjusted since the pH value of these solutions was above 5. In Section 3.2, it was determined that, at basic pH values, the adsorption capacity of MB on the surface of the biomass is constant, so it was decided not to make adjustments to the pH value of these solutions.

The samples were left in agitation for 18 hours; using UV-Vis spectroscopy, the concentration of these solutions was determined at the beginning and at the end of the process. Using (2), the MB’s adsorption capacity was determined by the biomass when the solution is in equilibrium at the end of this process:where is the amount of MB adsorbed per gram of the sample (mg/g) at equilibrium and is the concentration of MB in equilibrium (mg/L). The data obtained were adjusted to the models of Freundlich, Langmuir, Redlich–Peterson, Sips, and Toth, to understand the mechanism of adsorption of MB which takes place on the surface of biomass [14].

##### 2.6. Thermodynamic Studies of the Kinetics of Adsorption

Speed laws are essential in any study of biosorption because they provide an exact expression during the duration of the reaction [15]. Then, the models used in the present study are described below.

###### 2.6.1. Pseudo-First-Order and Pseudo-Second-Order Models

There are several models of kinetics, but in general, the most used and compared ones are the pseudo-first-order and pseudo-second-order kinetic models. The pseudo-first-order kinetic model was proposed for the first time at the end of the 19th century by Lagergren, and the speed constant when using this model is denoted as *K*_{1} [16]. The pseudo-second-order kinetic model was introduced for the first time in the mid-80s, but its recognition increased in the year of 1999 when Ho and McKay [17] took data from experiments reported in the literature and determined that the best fit to the data coming from all the systems studied was given by applying the pseudo-second-order model. After this publication came to light, the speed constant *K*_{2} has become more popular since in most studies, it has been found that the data obtained fit this model; for this reason, the original article has more than 6000 citations, a figure that has increased exponentially over the course of the time [18], and the equations of these two models are presented below.

A pseudo-first-order model is given as follows:where is the concentration of the adsorbed phase at a certain time of the adsorption process, is the concentration of the adsorbed phase at the end of equilibrium with the solid present in suspension, is the time that has elapsed since the process of adsorption began, and *k*_{L} is the Lagergren constant (s^{−1}). The pollutant adsorption rate is proportional to the time that has elapsed since the adsorption process began; for *T* = 0, the value of *q*_{t} = 0; once equilibrium has been reached, the value of *q*_{t}≈*q*_{e} [19].

A pseudo-second-order model is given as follows:

When *t* approaches zero, the bioadsorption velocity *q*_{t}/*t* becomes the initial bioadsorption velocity, and the data obtained in the kinetic study are adapted to the pseudo-second-order model by plotting the graph of *t*/*q*_{t} versus *t.* The linear relationship obtained will allow the calculation of *q*_{e}, *k*_{2}, and without previously knowing any parameter [20].

###### 2.6.2. Modified Pseudo-First-Order Model

This kinetic model is useful when the experimentally obtained data do not conform to the pseudo-first-order and pseudo-second-order kinetic models and the model of intraparticle diffusion. In this new model, the pseudo-first-order equation is modified by the speed constant as observed in the following equation [21]:

Since *q*_{t} < *q*_{e}, this equation implies that the velocity constant *k*_{1} is minimal when equilibrium has been reached [21].

###### 2.6.3. Elovich Model

It has been found that Elovich’s empirical adsorption model has broad applicability for numerous adsorption systems. This model is based on the assumption of energetic heterogeneity of the adsorption sites in the form of rectangular distribution [22].

The kinetic model of Elovich is reported as follows:where is the initial adsorption rate of the Elovich equation (mg·g^{−1} min^{−1}) and is the adsorption constant of the model (g·mg^{−1}) [15]; it is related to the adsorption energy [23].

The Elovich equation can be linearized by assuming *αβt* >> *t* and that *Q* = 0 at *t* = 0 and that *Q* = *Q*_{t} for a time *t* = *t*_{t} [24]. Under these conditions, a graph of *q*_{t} versus ln (*t*) shows a linear relationship with a slope of (1/*β*) and an intercept of (1/*β*) ln (*αβ*) [15].

This equation has been used by some authors to describe the kinetics of adsorption of contaminants in natural adsorbents, prepared or modified, which found that the best behavior of the data obtained is given when applying this model. But in spite of the utility of the Elovich equation in the estimation of the biosorption kinetics, the study of other kinetic models must be carried out, since these can present, in some cases, marginally superior correlation coefficients in the kinetics of adsorption of chemical substances [15].

This equation is also used to describe reaction mechanisms such as solute diffusion in the solution or interface phase, surface activation, and deactivation. It is adequate to elucidate the process with significant changes of activation energy. In addition, the Elovich equation can also reveal the irregularity of data that other dynamic equations have ignored [25].

###### 2.6.4. Intraparticle Diffusion Model

According to chemical reaction fundamental theory, intraparticle diffusion becomes a limiting factor to the overall reaction rate when the catalyst particle size is too large and/or the intrinsic reaction rate is too fast compared to the diffusion rate of reacting molecules inside the catalyst pores. The degree of inhibition resulting from the overall velocity depends on the combination of particle size and shape, intrinsic reaction velocity, and diffusion rate [26].

According to literature [26], if the rate-limiting step is intraparticle diffusion, then the amount adsorbed at any time *t* should be directly proportional to the square root of the contact time *t* and pass through the origin.

The intraparticle diffusion model is reported as follows:where is the intraparticle diffusion rate constant (mg/g/min^{−0.5}) [14].

The graph of *q*_{t} against 0.5 log *t* should produce a straight line with a positive intercept for the adsorption process controlled by intraparticle diffusion. The constant *K* is determined from the intersection with the *Y*-axis, and the high values of this parameter are related to a great adsorption speed [27].

###### 2.6.5. Film Diffusion Model

The film diffusion model is reported as follows:where (1/min) and are the constants of the film diffusion model [28].

In order to minimize the error distribution between experimental equilibrium data and values obtained by isotherm correlations, different error functions are generally applied. This goal of minimizing the error distribution is achieved by finding the minimum value of certain error functions or maximizing them depending on the definition of the selected error function. Therefore, choosing an error function seems indispensable in order to evaluate the best fit isotherm to the experimental equilibrium data [7]. In the present investigation, five different error functions (Table 1) were used to establish with certainty the isotherm of the kinetic model that presents the best adjustment of the adsorption of methylene blue on the surface of the algae *D. antarctica*.