Removal of methylene blue dye from aqueous ...

Environmental Science and Pollution Research https://doi.org/10.1007/s11356-018-2280-z

RESEARCH ARTICLE

Removal of methylene blue dye from aqueous solution using immobilized Agrobacterium fabrum biomass along with iron oxide nanoparticles as biosorbent Swati Sharma 1 & Abshar Hasan 1 & Naveen Kumar 2 & Lalit M. Pandey 1 Received: 19 January 2018 / Accepted: 8 May 2018 # Springer-Verlag GmbH Germany, part of Springer Nature 2018

Abstract A nano-biosorbent for the removal of methylene blue (MB) was prepared by encapsulating iron oxide nanoparticles (NPs) and Agrobacterium fabrum strain SLAJ731, in calcium alginate. The prepared biosorbent was optimized for the maximum adsorption capacity at pH 11, 160 rpm, and 25 °C. Adsorption kinetics was examined using pseudo-first-order, pseudo-second-order, and intra-particle diffusion (IPD) models. The kinetic data agreed to pseudo-second-order model indicating chemisorption of MB, which was also explained by FTIR analysis. The adsorption rate constant (k2) decreased and initial adsorption rate (h, mg g−1 min−1) increased, with an increase in initial dye concentration. The dye adsorption process included both IPD and surface adsorption, where IPD was found to be a rate-limiting step after 60 min of adsorption. The adsorption capacity was found to be 91 mg g−1 at 200 mg L−1 dye concentration. Adsorption data fitted well to Freundlich isotherm; however, it did not fit to Langmuir isotherm, indicating adsorbent surfaces were not completely saturated (monolayer formed) up to the concentration of 200 mg L−1 of MB. Thermodynamic studies proposed that the adsorption process was spontaneous and exothermic in nature. Biosorbent showed no significant decrease in adsorption capacity even after four consecutive cycles. The present study demonstrated dead biomass along with NPs as a potential biosorbent for the treatment of toxic industrial effluents. Keywords Biosorbent . Immobilized . Methylene blue . Adsorption . Intraparticle diffusion . Isotherm

Introduction Dyes and their byproducts in the effluent waste stream are gradually destructing and disrupting the aquatic ecosystems by altering the chemistry of water. In the past few years, severe damage has been caused due to this untreated discharge, comprising 10–15% dyes in the effluent from textile, paper production, tanning leather, and food-processing industries, as well as from various dyes used for hair coloring products.

Responsible editor: Guilherme L. Dotto * Lalit M. Pandey [email protected] 1

Bio-interface and Environmental Engineering Lab, Department of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Guwahati, Assam 781039, India

2

AMITY Institute of Biotechnology, Amity University Campus, Sector-125, Noida, Uttar Pradesh 201303, India

Dyes are the most detrimental contaminant as they are toxic, carcinogenic, mutagenic, and nondegradable and have a tendency to be quite stable for an extended period in the environment. Methylene blue (MB) is an aromatic-cationic dye of synthetic origin and is used extensively in textile industry. Exposure to MB can lead to skin damage and burning sensation in the eyes, whereas its ingestion can cause nausea, vomiting, and detrimental effects such as methemoglobinemia (Hameed and Ahmad 2009). Several physiochemical methods have been used to treat these colored contaminants, namely cloud point extraction, coagulation, membrane filtration, chemical oxidation, and various other adsorption techniques (Gautam et al. 2014; Soylak et al. 2012). Adsorption, from the viewpoint of economic feasibility, easy availability, and high efficiency, has come up with a strong solution (Silva et al. 2017b). Based on the above viewpoints, biosorption is the most eco-friendly technique to remediate dye contaminants in an efficient manner (Sharma et al. 2018). Many types of research have recognized bacteria and algae as well as fungi

Environ Sci Pollut Res

(yeast) and their biomass as excellent biosorbents (Cid et al. 2015; Deng et al. 2006; Dotto et al. 2015; Silva et al. 2017a). Among these, bacteria are extensively studied for biosorption because of their abundant availability, ubiquitous nature, and low cost. Dead biomass is preferred over live biomass as they are not affected by the native toxicity of wastewater and do not need a nutrient supply for growth maintenance (Machado et al. 2009). Nanoparticles have gained tremendous attention in recent studies in various sectors of research like environmental bioremediation (Peres et al. 2017; Tiwari et al. 2017), drug delivery (Saxena et al. 2017), and tissue engineering (Hasan et al. 2018; Hasan et al. 2017; Roy et al. 2018) and in various other sectors of electronics. Their unique characteristics of super magnetism and large surface area have made them an excellent biosorbent candidate. Biomass encapsulated magnetic nanoparticles (MNPs) have few advantages over conventional biosorbents, as nanoparticles increase the available surface area of adsorption and provide the advantage of easy recoverability due to their superparamagnetism (Arsalani et al. 2010). Encapsulation and immobilization add to the mechanical strength and adsorption capacity of the adsorbent. Hence, an amalgamation of these techniques together improves the overall efficiency of the biosorbent. In the present work, we utilized an isolated strain, Agrobacterium fabrum SLAJ731 (Tiwari et al. 2017) for the removal of a synthetic dye, MB. A nano-biosorbent was prepared by encapsulating the biomass along with iron oxide nanoparticles (NPs) in calcium alginate. Batch experiments were undertaken using synthetic MB solution to determine the adsorption capacity and reusability of the above biosorbent. To gain an enhanced knowledge of the biosorption mechanisms, adsorption kinetics and thermodynamic studies were performed.

Materials and methods Materials Iron(II) chloride tetrahydrate (Cat no. A16327) and iron(III) chloride hexahydrate (Cat no. A16231) were purchased from Alfa Aesar, India. Methylene blue was purchased from Sigma. All other reagents were of analytical grade supplied from HiMedia, India. All sets of experiments were conducted using double-distilled water (18 MΩ, Millipore system).

Synthesis of MNPs Co-precipitation method was opted for the synthesis of magnetic nanoparticles as reported previously (Kaur et al. 2014; Nair et al. 2015). Briefly, 100 mL deoxygenated water was added to 1.04 g of FeCl2·4H2O and 2.64 g of FeCl3·6H2O and

gently mixed at room temperature. Later, the solution was vortexed at 600 rpm using a mechanical stirrer (Remi, India) maintained at 80 °C under reducing environment (by purging N2 gas). The desired hydrolysis of iron precursors to magnetite nanoparticles (MNPs) was confirmed by the formation of black precipitate upon adding drops of 25% NH4OH, a reducing agent. This synthesis of nanoparticles was performed for 2 h for complete reduction of iron salts to nanoparticles. The obtained precipitates (under the influence of external magnetic field) were repeatedly washed with distilled water until the pH reached 7 and were kept for drying overnight.

Preparation of biomass Agrobacterium fabrum SLAJ731 was isolated from a core sample of Assam Oil reservoir and was found to be highly lead (Pb) tolerant up to 2900 mg/L and exhibited an excellent Pb adsorption capacity of 197.02 mg g−1 (Tiwari et al. 2017). Glycerol stock of this previously isolated strain was used to prepare 1% inoculum by growing it overnight in Luria-Bertani (LB) media at pH 7.4 and 37 °C. Later, biomass was separated by centrifugation at 10,000 rpm for 20 min at 4 °C. The biomass pellet was rinsed thoroughly with distilled water and kept overnight for drying and later lyophilized to form a dry powder.

Preparation and characterization of biosorbent An equal ratio of synthesized iron oxide MNPs (1 g) and lyophilized biomass (1 g) was mixed evenly in 2% (w/v) sodium alginate solution (in such a way that all the contents are evenly mixed without any lump formation). This solution was then slowly dropped (using the peristaltic pump) at a uniform rate in 3.5% calcium chloride solution (w/v) and MNPbiomass-calcium alginate (MBCaAb) beads were formed. The vigorous premixing of lyophilized biomass and iron nanoparticle before encapsulation by calcium alginate ensured the stability of beads upon repetitive usage (Arıca et al. 2004; Yadav and Jadhav 2005). These MBCaAb beads were kept overnight so that the beads get suitably hardened after encapsulation. Later, these beads were cleaned with distilled water to get pH 7 and preserved at 4 °C for further use. The size of the prepared beads was determined by volume displacement method (Sun and Griffiths 2000). Concisely, 2 mL of water was taken in a measuring cylinder and 10 beads were added to it. The change in volume was used to calculate the average volume of the 10 beads. From the volume data thus obtained, the size of individual bead was calculated. Further, the moisture content of beads was analyzed based on the following formula: M% ¼

Initial weight−Final weight 100 Initial weight

ð1Þ


where initial weight stands for the weight of wet bead after removing the surface water using filter paper. Final weight was calculated by drying beads at 75 °C until no significant change in weight was observed after successive drying. Field emission scanning electron microscopy (FESEM, Zeiss, Model: Sigma) was used for morphology analysis of the prepared beads. EDX analysis was performed to analyze the elemental composition of the biosorbent and FTIR was performed to understand the functional groups involved in MCaAb beads responsible for the biosorption process.

Batch adsorption studies The experiments were conducted to look into the key adsorption variables namely pH, temperature, initial dye concentration (C0), and contact time. Briefly, 1 g L−1 MBCaAb beads (dry weight) was added individually to different methylene blue dye concentrations (C0) 25, 50, 100, and 200 mg L−1 respectively in a 250-mL conical flask, incubated at constant stirring at 160 rpm and 25 °C (Scigenics, Orbitek-LE model). Optimization of pH for dye biosorption was studied in the range from 3 to 12 (using 0.1 N NaOH and HCl). Further, experiments were performed at optimized pH. Batch experiments were carried out at 25, 30, 37, and 45 °C temperatures for 3 h to evaluate the role of temperature on biosorption (thermodynamic parameters). In each analysis, samples were collected at various time intervals to study the amount of adsorption based on a decrease in optical density (O.D.) of the methylene blue solution at 665 nm. The adsorption capacity of biosorbent was determined based on the equation as follows (Tiwari et al. 2017; Xu et al. 2012): qt ¼

ðC 0 −C t Þ V W

ð2Þ

where qt stands for adsorption quantity (mg g−1), W is the weight of adsorbent (g), V is the volume of solution (L), and C0 and Ct stand for the initial concentration and concentration at time t, of dye in the solution, respectively. These concentrations were determined based on the optical density of the solution at different time intervals. All the studies were performed in triplicate.

Biosorbent reusability studies Study of regeneration and reusability of adsorbent is important to understand economic feasibility of adsorbent. In this study, dye adsorbed beads were washed with distilled water to get rid of loosely bound dye molecules from the surface. To remove adsorbed dye, the beads were added to 20 mL of 0.05 M HCl maintained at pH 3, 37 °C for 30 min at 150 rpm to ensure complete desorption without leaching. Later, the supernatant was collected and its O.D. was measured at 665 nm to obtain

the concentration of desorbed (adsorbed) dye. The desorbed beads were rinsed several times with distilled water to reach pH 7. This completed the first cycle (Tiwari et al. 2017; Xu et al. 2012) of biosorption. These beads were again added to a fresh 200 mg L−1 MB solution for the next batch adsorption study as mentioned in the above section BBatch adsorption studies.^ The above process of adsorption-desorption was repeated for four times consecutively to investigate the recycling efficiency (reusability) of the biosorbents. After the fourth cycle, the desorbed beads were subjected to lyophilization and later studied using EDX and FTIR to investigate the relative elemental distribution and surface functional groups.

Results and discussion Characterization of biosorbent The size of chemically prepared iron oxide nanoparticles was found to be in the range of 10–20 nm with the saturation magnetization (Ms) of MNPs of 48.325 emu g−1 (Tiwari et al. 2017). The biosorbent (entrapped biomass and iron oxide nanoparticles) beads were dark in color with a moisture content of 94.75 ± 0.29%. The beads were examined for their size (diameter) based on volume displacement method, which was found to be 3 mm. These results were similar to the results obtained for beads synthesized by co-precipitation method as stated in the literature (Tiwari et al. 2017). Figure 1 shows the shape and morphology of the biosorbent beads. FESEM image showed the presence of MNPs and biomass in alginate, which were confirmed by the presence of C, O, Ca, and Fe compounds in EDX spectra (Fig. 11).

Effect of pH on MB biosorption The pH of solution acts as a critical factor in biosorption phenomenon. This could be attributed to the speciation and ionization of biosorbates as well as variation in biosorbent surface charge with a change in solution pH (Deniz and Kepekci 2017). As shown in Fig. 2, there was a sigmoidal rise in MB adsorption with the change in pH range from 2.0 to 12.0 suggesting an increase in adsorption with an increase in pH. Lower adsorption at acidic pH could be due to electrostatic repulsion between the positive surface charge of biosorbent and dye cations. Also, the competitive effect of H+ ions in the surrounding solution also decreased the affinity of dye cations towards the binding site of the biosorbent (Etim et al. 2016). In contrast, negatively charged surface sites on the biosorbent increase with an increase in alkaline pH. This leads to increase in electrostatic attraction between the cationic dye and biosorbent thereby increase in adsorption rate until all the binding sites were occupied, where the adsorption rate got

Environ Sci Pollut Res Fig. 1 a Snap of MNP-biomasscalcium alginate (MBCaAb) beads and b FESEM image of MBCaAb beads surface

saturated (Amin 2009). Xie et al. (2015) reported similar results on MB removal by magnetic baker’s yeast. We have used this optimized pH 11, for further experiments.

Kinetic studies of MB biosorption The role of contact time and initial dye concentration on the adsorption capacity (qt) of biosorbent were investigated using varying concentrations of 25, 50, 100, and 200 mg L−1 of MB at various contact times as shown in Fig. 3. The results revealed a two-step adsorption process. A significantly fast biosorption occurred in the initial 60 mins of contact time, followed by a slow biosorption as it reached the equilibrium within 120 min. No further improvement in adsorption capacity was observed with an increase in contact time affirming the saturation of adsorption sites. The maximum adsorption capacity was found to be 91 ± 0.2 mg g−1 at 200 mg L−1 of MB concentration. It was observed that as the initial dye concentration increases, there was an increase in adsorption capacity. This trend was due to a direct relation between driving forces for mass transfer with the initial dye concentration. Since the residual dye concentration was more at the higher initial dye concentration, it caused increased mass transfer rate at the

Fig. 2 Effect of pH on the adsorption capacity of the biosorbent

surface of the adsorbent (Deniz and Kepekci 2017; Etim et al. 2016; Shu et al. 2015). During the initial step of biosorption, dye molecules, from bulk solution, rapidly reached the boundary layer of highly porous adsorbent by mass transfer. In the further step, once all the external sites were occupied, diffusion occurred within the interior porous structure of adsorbent from the outer boundary layer (Gautam et al. 2015a; Han et al. 2011). The rate constant and order of adsorption reaction were analyzed based on fitting of experimental data to pseudo-first-order and pseudo-second-order kinetic models. Pseudo-first-order kinetic model This kinetic model is used to study kinetic process in a liquid-solid system based on adsorbate capacity. Linearized pseudo-first-order rate equation is expressed as follows (Lagergren 1898): lnðqe −qt Þ ¼ lnðqe Þ−k 1 t

ð3Þ

where k1 is the first-order rate constant (min−1) and qe and qt are the adsorbed amounts (mg g−1) of MB dye at equilibrium and at time Bt^ respectively.

Fig. 3 Effect of contact time on adsorption capacity at different initial dye concentrations


Fig. 4 Pseudo-first-order kinetic fitting for MB biosorption

Fig. 5 Pseudo-second-order kinetic fitting for MB biosorption

In Fig. 4, the slope and intercept of the graph of ln (qe–qt) versus t were used to obtain the kinetic parameters, k1 and qe as listed in Table 1. From the graph, it was observed that experimental and calculated value for qe varied significantly at all different initial dye concentrations. In addition, the R2, i.e., correlation factor value obtained was very low explaining the inapplicability of pseudo-first-order kinetic model fitting. Similar results were reported in previous studies describing the unsuitability of pseudo-first-order model in adsorption of pollutants by biosorbents (Gautam et al. 2015c; Ghaedi et al. 2014; Roosta et al. 2014).

order kinetic model was more suitable for the present study of adsorption. Previous studies suggested a similar trend of increase in h values with increase in initial dye concentrations. This can be explained as in case of high initial dye concentration, more dye molecules can bind adsorbent surface in lesser time span due to the increased mass transfer rate (Ho and McKay 1998; Silva et al. 2017b).

Intra-particle diffusion analysis

t 1 t ¼ þ qt k 2 q2e qe

ð4Þ

Adsorption is a sequential multi-event process, where initially dye molecules undergo film diffusion (boundary layer diffusion), next adsorption of dye occurs on the adsorption sites available on the surface of adsorbent, and lastly, diffusion of dye into the interior porous sites of sorbent beads often termed as intraparticle diffusion (Duran et al. 2011). Weber and Morris (1963) explained intraparticle diffusion phenomenon as follows:

h ¼ k 2 q2e

ð5Þ

qt ¼ K p t 1=2 þ C

Pseudo-second-order kinetic model The linearized second-order kinetic model (Günay et al. 2013; Ho and McKay 1999) for adsorption is stated as follows:

where qe (mg g−1) and qt (mg g−1) are the amount of MB adsorbed at equilibrium and time t, respectively. Pseudosecond-order rate constant is k2 (g mg−1min−1) and h stands for initial adsorption rate (mg mg−1 min−1). This kinetic model predicted the chemisorption along with physisorption process involved in adsorption of dye on biosorbent. A linear plot of t/qt versus t was plotted (Fig. 5) and qe and k2 values were tabulated. From the obtained R2 values, as tabulated, it was observed that pseudo-second-

Table 1 Pseudo-first-order and pseudo-second-order kinetic constants for MB dye adsorption at different initial concentrations

C0 (mg L−1)

25 50 100 200

qe (mg g−1)

10.14 21.65 45.21 90.68

ð6Þ

where qt represents adsorption capacity (mg g−1) at time t (min), Kp is the IPD rate constant for time t (mg g−1 min-1/2), and C stands for intercept and is a constant (mg g−1). Figure 6 shows the amount of MB dye adsorbed on unit mass of biosorbent (qt) with t1/2. Studies suggested that if the graph was linear in nature and passes through origin, then adsorption was solely based on IPD, making it a ratelimiting step (Yu et al. 2015). Multi-linear nature of the curve represented that adsorption process involves more than

Pseudo first order

Pseudo second order

k1 (min−1) until 305 min

R2

k2 (g mg−1 min−1)

h (mg g−1 min−1)

R2

1.34 × 10−2 2.15 × 10−2 0.85 × 10−2 1.17 × 10−2

0.87 0.96 0.82 0.89

9.18 × 10−3 5.07 × 10−3 5.04 × 10−3 2.70 × 10−3

0.94 2.38 10.31 22.22

0.99 0.99 0.99 0.99


the most studied and accepted equilibrium isotherms for adsorption of metal ions from the liquid phase are Langmuir (1918) and Freundlich (1906) isotherms.

Langmuir isotherm: Langmuir isotherm is expressed as follows: Ce Ce 1 ¼ þ qe qm K L qm

ð7Þ

1 1 þ K LCo

Fig. 6 Intraparticle diffusion kinetics for MB biosorption

RL ¼

intraparticle diffusion. There was a rapid adsorption of dye on the external surface of the MBCaAb beads, which was represented by the initial curved portion of the graph. It was followed by a straight line representing a slow IPD process (Dotto and Pinto 2012; Tiwari et al. 2017). Table 2 lists the rate constants K initial and K intra values of the adsorption process. Intercept value indicated the thickness of film and boundary layer effect. The negative value signified that there was no involvement of IPD during the initial adsorption process. Kinitial and Kintra values were found to increase with increase in dye concentration; however, Kintra values were found to be rate limiting. Upon comparing the K and C values from the obtained data, it was concluded that the adsorption of dye includes both IPD and surface adsorption. Summarily, initial adsorption was kinetic controlled due to high er bu lk con centratio n followed by intraparticle diffusion, which was found to be rate limiting.

where qm (mg g −1) represents the maximum adsorption capacity, KL (L mg−1) represents the Langmuir constant which defines the affinity of binding sites, RL is the dimensionless constant separation factor, and C0 (mg g−1) is the initial dye concentration. Langmuir isotherm assumes homogenous monolayer adsorption phenomenon where when a molecule adsorbs on the binding site, that site gets unavailable for further binding to occur, leading to a monolayer formation. The possibility of such phenomenon to occur is predicted based on the RL value. It is favorable when the RL value is between 0 and 1. Fitting the experimental data to the Langmuir model resulted in the value of RL > 1 (shown in Table 3) and R2 = 0.44 (shown in Fig. 7), indicating the inappropriateness of Langmuir isotherm for the present adsorption study. This suggested that the binding surfaces were not completely saturated (monolayer formed) up to the studied concentration of 200 mg L−1 of MB, indicating the expected adsorption capacity would be higher than the maximum adsorption capacity obtained (91 mg g−1) of the adsorbent.

Equilibrium isotherms for MB biosorption:

Freundlich isotherm

Adsorption isotherm investigates the capacity and behavior of adsorption. It is important to analyze the experimental adsorption data in terms of equilibrium isotherm. Some of

Freundlich isotherm is used to investigate heterogeneous surface adsorption, which is not constrained to monolayer formation. A linearized form of Freundlich isotherm is expressed as:

Table 2 Diffusion rate constants for MB dye adsorption on biosorbent analyzed using intraparticle diffusion (IPD) model

Concentration (mg L−1)

Kinitial (mg g−1 min−1/2)

C (mg g−1)

ð8Þ

R2

Initial 60 min

Kintra (mg g−1 min-1/2)

C (mg g−1)

R2

8.855 19.669 33.061 78.457

0.74 0.77 0.95 0.86

After 60 min 25 50 100 200

1.144 2.492 4.473 9.604

0.048 0.169 −0.378 0.058

0.99 0.99 0.99 0.99

0.056 0.106 0.534 0.895

Environ Sci Pollut Res Table 3 Langmuir isotherm and Freundlich isotherm constants for MB dye adsorption on MBCaAb beads

Temperature

310 K

1 lnqe ¼ lnK F þ lnC e n

Langmuir model KL (L mg−1)

qm (mg g−1)

RL

R2

KF (L g−1)

1/n

R2

− 0.52 × 10−3

− 800

1.013 to 1.116

0.44

0.33

1.045

0.99

ð9Þ

−1

where KF (L g ) and n are Freundlich constants. KF denotes the concentration of adsorbed ions in solution at equilibrium and n stands for the adsorption intensity factor. If the 1/n value stands between 0 and 1, it signifies that adsorption is favorable, and if it is more than 1, it signifies multilayer cooperative adsorption (Fytianos et al. 2000). By fitting the experimental data in the Freundlich model (as shown in Fig. 8), the R2 value and 1/n were obtained as 0.99 and 1.045, respectively (Table 3). The value for 1/n = 1.045 indicated that adsorption was favorable and cooperative in nature and the adsorption capacity was linearly related to MB concentration up to 200 mg L−1. Therefore, the maximum adsorption capacity was expected to be greater than 91 mg g−1. Similar results were obtained for the adsorption of MB on activated carbon surfaces, cane bark powder, and Chitosan/ Spirulina bio-blend films used as adsorbent (Enenebeaku et al. 2017; Santhi and Manonmani 2009; Silva et al. 2017a).

Thermodynamic studies of MB biosorption process Thermodynamic variables, i.e., free energy (ΔG0), enthalpy (ΔH0), and entropy (ΔS0), were determined to understand the feasibility and spontaneity of adsorption process based on the following equations (Gautam et al. 2015b; Günay et al. 2013): ΔGo ¼ −RT lnK c

ð10Þ

ΔGo ¼ ΔH o −T ΔS o

ð11Þ

Fig. 7 Langmuir isotherm for adsorption of MB dye

Freundlich model

logK c ¼

ΔS o ΔH o − 2:303R 2:303RT

ð12Þ

where R stands for gas constant (8.314 J mol−1 K), T (K) is the absolute temperature, and Kc (L g−1) is calculated as qe/Ce and it represents standard thermodynamic equilibrium constant. Enthalpy and entropy values were calculated (Table 4) from the slope and intercept of log Kc versus 1/T plot (Fig. 9). The values for ΔG° indicated that the adsorption was spontaneous with an increase in temperature; − ΔH° explained the adsorption to be exothermic in nature and ΔS° explained that randomness of the solution at adsorbent surface increased during the adsorption process. An exothermic ΔH° value implied that the sorption process involved either physical or chemical bond formation (Sevim et al. 2011). On the other hand, the positive value for the change in entropy (ΔS°) showed that there was an increase in the randomness of dye molecules on the adsorbent-adsorbate interface suggesting its increased affinity towards the adsorbent surface. This increased randomness may have caused a decrease in overall viscosity of the solution, which in turn would have led to increased adsorption process. The similar result was observed in methylene blue adsorption on the surface modified yeast acting as biosorbent (Xia et al. 2015).

Biosorbent reusability studies Reusability of adsorbent is an important parameter from the economic and environmental perspectives. An ideal adsorbent should retain its activity even after multiple repeats. Reusability of biosorbent was checked after four consecutive cycles of adsorption and desorption and its adsorption

Fig. 8 Freundlich isotherm for MB dye adsorption

Environ Sci Pollut Res Table 4 Effect of temperature in thermodynamic studies for MB adsorption on MBCaAb beads

Qe

ΔG (kJ mol−1)

ΔH (kJ mol−1)

ΔS (J K−1)

R2

298 303

44.59 ± 0.13 43.63 ± 0.10

− 15.11 − 15.31

− 3.82

37.92

0.98

310 325

42.43 ± 0.22 40.42 ± 0.10

− 15.59 − 15.86

Temperature (K)

efficiency remained about 85% (Fig. 10). This decrease could be due to some loss of dye during the repeated experiment and irreversible dye adsorption. Hence, these results showed the good possibility of using the biosorbent for remediation of effluents from industries and wastewater treatment due to its reusability and magnetic property (makes it easily separable). Various reported studies based on calcium alginate beadencapsulated biomass has shown similar results (Aichour et al. 2018; Bilal and Asgher 2015; Daâssi et al. 2014; Duarte et al. 2013).

EDS and FT-IR analyses In order to understand the mechanism involved in the interaction of methylene blue with the biosorbent, EDX and FTIR analyses were performed for naïve MCaAb beads, adsorbed beads, and desorbed beads after the fourth cycle. The EDX analysis as shown in Fig. 11 explained the elemental distribution of biosorbent in the initial stage and after the fourth cycle. The EDX analysis reported the presence of C, O, Fe, and Ca in the relative abundance of 45 ± 2, 41 ± 2, 12 ± 3, and 5 ± 0.6% respectively, for naïve beads, which became 60 ± 6, 21 ± 4, 11 ± 2, and 0.2 ± 0.1% respectively after the fourth cycle. Moreover, the desorbed bead also showed adsorption of

Fig. 9 Thermodynamic studies of the adsorption of MB

methylene blue dye, wherein 8 ± 2% for N and 4 ± 1.5% for S were obtained after the fourth repeat. This increase in the relative abundance of C, N, and S suggested the biosorption of dye onto the surface of beads. No significant decrease in the content of Fe suggested the stability of bead structure up to four cycles. Similarly, the involvement of various functional groups in the biosorption process was determined using FTIR analysis of naïve bead, adsorbed bead, and desorbed bead after the fourth cycle (Fig. 12). The shifts in the peak position from naive beads to adsorbed beads viz. 3394 to 3419 cm−1 suggested the involvement of –OH groups and 1625 to 1610 cm−1 represented the involvement of –NH bond. Likewise, the shift from 1415 to 1400 cm−1 represented the involvement of –COOH groups. These peak shifts showed the electrostatic attraction between the cationic MB dye and the –OH and –NH2 groups of biosorbent. In addition, peak shift from 570 to 590 cm−1 represented the involvement of Fe–O nanoparticles in the adsorption of methylene blue. This could be due to the electrostatic interaction between negatively charged iron oxide nanoparticle at pH 11 and cationic dye, forming a complex during biosorption. Similarly, there could be involvement of H-bond between iron oxide nanoparticle and methylene blue dye, as reported in literature as well (Fangwen et al. 2009). Furthermore, few literatures reported that iron oxide nanoparticles undergo surface adsorption as well as oxidation during the process of removal of methylene blue from the solution (da Silva et al. 2017). Hence, based on the EDX and FTIR result, we could conclude that the

Fig. 10 Reusability of biosorbent after successive four cycles


Fig. 11 EDS analysis of MBCaAb biosorbent a naïve beads (i.e. before dye adsorption) and b dye desorbed beads after fourth adsorption-desorption cycles

biosorption of MB dye onto biosorbent surface was based on chemisorption due to the electrostatic attraction between the cationic dye and the biosorbent surface along with physisorption (Dotto et al. 2012).

Conclusion

Fig. 12 Functional group analysis using FTIR for naïve beads (black), adsorbed beads (red), and desorbed beads (blue). Dotted lines show the functional groups involved during the biosorption process

In summary, MNP-biomass-alginate (MBCaAb) beads were prepared by encapsulation of MNPs along with dead SLAJ731 biomass in calcium alginate. The effect of major adsorption variables, namely pH, initial dye concentrations, contact time, and temperature was experienced based on the adsorption capacity of the biosorbent. The most influential parameter was found to be pH of the solution, which was optimized at pH 11. The adsorption of MB onto this biosorbent was examined and was found to be spontaneous, exothermic, and pseudo-second kinetics. The adsorption process occurred rapidly, attaining an equilibrium within first 60 min. Freundlich isotherm was observed to be suitably fit


for the equilibrium biosorption data. The maximum adsorption capacity was found to be more than 91 to 200 mg L−1 of MB concentration, and the biosorbent could also be reused up to four times without losing its efficiency. The FTIR analysis explained the chemisorption of MB on beads. The study pointed out the application of highly efficient and recyclable MBCaAb beads for the environmental protection. Acknowledgements The authors would like to acknowledge the Department of Biosciences and Bioengineering, Indian Institute of technology Guwahati, for providing us a generous chance to be a part of this institute, and Central Instrument Facility (CIF), IIT Guwahati, for allowing access to various facilities that augmented the work.

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