2.1 Materials

Neem leaves (A. indica) were collected from the institute campus of Indian Institute of Technology, Roorkee, India. All the chemicals and reagents were of analytical reagent grade and used without additional purification. The stock solutions of As(III) and As(V) were prepared by dissolving NaAsO₂ and Na₂HAsO₄, 7H₂O, purchased from Himedia Laboratories Pvt. Ltd. Mumbai, India, in 1 L of double distilled water, respectively. All other necessary chemicals used in the experiments, were purchased from Himedia Laboratories Pvt. Ltd. Mumbai, India. Glassware utilized for experimental purposes was washed in 10% nitric acid and rinsed with deionized water for removing any probable interference by other metals.

2.2 Microorganism and growth medium

The microorganism utilized was the arsenic-resistant bacterium C. glutamicum MTCC 2745 (Microbial Type Culture Collection and Gene Bank (MTCC), Chandigarh, India). Culture media were prepared as per the guidelines of microbial type cell culture (MTCC). Composition of growth medium and cultivation conditions are exhibited in Table 1.

2.3 Acclimatization

The revived culture was initially grown in MTCC prescribed growth media in a 250 mL round bottom flask tightly closed with cotton plug as follows:

C. glutamicum MTCC 2745 was cultivated in 250 mL flask containing 100 mL of the growth media with As(III) and As(V). The cultures were acclimatized to As(III) and As(V) individually exposing the culture in a series of shake flasks.

The bacterial inoculum was prepared by transferring a loop full of bacterial culture from the nutrient agar tubes to the flask containing sterilized growth media, incubated at 30 °C for 24 h with moderate agitation (120 rpm) in an incubator cum orbital shaker. Then the acclimatization of C. glutamicum MTCC 2745 in arsenic environment was carried out as follows (Mondal et al., 2008):

After 24 h the synthetic medium in the flask had turned milky specifying significant bacterial growth in the flask. Appropriate amount of arsenic (As(III) or As(V)) was added into the flask having 100 mL sterilized growth media to acquire a concentration of 50 mg/L of arsenic. Firstly growth of C. glutamicum MTCC 2745 was inhibited and the growth started after 2 h. After 24 h of incubation at 30 °C with moderate agitation (120 rpm), 5 mL of the arsenic resistant bacterial inoculum was periodically added in a series of 250 mL flasks containing 100 mL of arsenic containing sterilized growth media (As(III) or As(V) concentration, 100, 200, 500, 800, 1000, 1200, 1500 and 1800 mg/L) under sterile conditions in a laminar hood chamber. After 24 h later, another fresh growth media containing arsenic (As(III) or As(V) concentration, 2000 mg/L) were also inoculated with 5 mL of the last culture (As(III) or As(V) concentration, 1800 mg/L) to ensure that the bacteria were already adapted to both As(III) and As(V). For inoculum, a further subculturing was performed and all the inoculum transfers were done in exponential phase (OD value ∼1 at 600 nm).

2.4 Methods

3.1 Determining adsorption kinetic parameters by nonlinear regression

The kinetic parameter sets are calculated by nonlinear regression because of the inherent bias affecting after linearization. This delivers a mathematically laborious method to estimate kinetic parameters utilizing the original kinetic equation (Khan et al., 1996; Ncibi, 2008; Hadi et al., 2012). Usually Gauss–Newton methods or Levenberg–Marquardt based algorithms (Edgar and Himmelblau, 1989; Hanna and Sandall, 1995) are used. The biosorption kinetic data of arsenic onto C. glutamicum MTCC 2745 immobilized on surface of NL/MnFe₂O₄ composite were analyzed by nonlinear curve fitting analysis using professional graphics software package OriginPro (8.5.1 version) for fitting the kinetic models.

The optimization method needs the selection of a Goodness-of-Fit Measure (GoFM) with the aim of esteeming the fitting of the kinetics to the experimental data. In the current study, six GoFM (Residual Sum of Squares (SSE), reduced Chi-square test (Reduced χ²), coefficient of determination (R²), Adjusted R-square $({\bar{R}}^2)$ , R value (R) and Root-MSE value) were employed for assessing isotherm parameters using the OriginPro software by considering 95% confidence interval (The details are provided with Supplementary materials).

The adjusted coefficient of determination $({\bar{R}}^2)$ , which generally takes into account the number of variables and sample size in the model, is deliberated superior to the coefficient of determination (R²), since it revises the overestimation by R² (Warrens, 2008). While dealing with small samples, specifically it is more exact than R².

3.2 Adsorption kinetic modelling

Biosorption kinetics reveals the rate of adsorbates bonding on the surface of the biological materials. Kinetics studies deliver the vital information about the probable mechanism of biosorption that includes the diffusion (bulk, external, and intraparticle) and chemical reactions. In general, it is supposed that adsorbate transport happens in the few following steps. The first step includes the transport of adsorbate in the bulk of the solution, second step comprises the external diffusion (the substrates diffuse from the bulk solution to the external surface of the biosorbent), the third step was because of the transport of the adsorbate across the boundary layer, the fourth step involves the transfer of compounds in the pores to the internal parts of the biosorbent and finally uptake of molecules by the active sites, and the fifth step comprises biosorption and desorption of adsorbate (Plazinski et al., 2009; Michalak et al., 2013). In many experimental biosorption systems, the influence of transport in the solution is rejected by fast mechanical mixing, so, it is not supposed to be involved in governing of the overall sorption rate and can be overlooked, as a rule (Plazinski et al., 2009). With the purpose of inspecting dynamic biosorption behavior of As(III) and As(V) onto immobilized bacterial cells i.e. governing the current biosorption process mechanisms and the probable rate limiting steps for example mass transport and/or chemical biosorption processes, kinetic models have been utilized for fitting the experimental data. Fourteen kinetic models were employed in the current research supposing that concentrations on the adsorbent surface are equal to the measured concentrations.

There are many models for kinetics of biosorption at the interface of solid/solution. Fractional power model (FP), pseudo first order (PFO) and pseudo second order (PSO) are common empirical models, however their major drawback is that they may simply define the kinetics of adsorption at some restrictive situations (Haerifar and Azizian, 2013). Elovich is a two parametric semi-empirical model and fractional power (FP), Ritchie second order and exponential (EXP) kinetic models are two parametric empirical models to analyze kinetic data at near to equilibrium. As well other empirical models for instance Avrami, modified pseudo second order (MPSO) and mixed 1, 2 order model (MOE) equations have been recommended for modelling the adsorption kinetics at the interface of solid/solution. These models are mainly three parametric equations.

The prior kinetic models of adsorption at the interface of solid/solution can be generalized by taking into consideration the fractal-like methodology i.e. time dependence of adsorption rate coefficient. A physical significance of the fractal-like idea has been considered for adsorption kinetics onto surfaces of solid that is energetically heterogeneous. The fractal-like study exhibits that the kinetics of adsorption at interface of the solid/solution in a real system with various kinds of surface sites and with various affinities for adsorption can be demarcated by a fractal-like methodology. Based on this study, the history of process can influence the process besides the achieved rate coefficient of adsorption is a function of time. Table 2 presents representative kinetic models for a biosorptive reaction (The details of adsorption kinetic modelling are provided with Supplementary materials).

3.3 Adsorption mechanistic modelling

The scavenging of adsorbate species from the liquid by the solid phase is taken place in three successive steps as follows (McKay et al., 1981; Singh and Pant, 2006; Al-Degs et al., 2008). The three stages tangled in the mechanism of biosorption process are as follows:

1. Firstly the adsorbate mass transfer from the aqueous phase onto the biosorbent surface i.e. film diffusion or surface diffusion takes place.

2. Secondly internal diffusion of adsorbate via either a pore diffusion model or homogeneous solid phase diffusion model i.e. particle diffusion occurs.

3. The third stage is the biosorption of adsorbate onto the surface sites. Due to its very fast in nature, it cannot be considered for the rate determining step.

So as to know the rate controlling step, the following different models (Table 3) were applied using the experimental data of kinetic study (The details of mechanistic model equations are provided with the Supplementary material).

3.4 Adsorption thermodynamic modelling

The entropy and Gibbs free energy parameters should be measured with the intention of deciding whether the processes will happen spontaneously. Thermodynamic parameters for example ΔG⁰, ΔH⁰ and ΔS⁰ can be calculated utilizing equilibrium constant while the temperature varies (Table 4) and their evaluation gives an insight into the possible nature of adsorption (the details of thermodynamic equations are provided with Supplementary material).

3.5 Adsorption activation energy

The adsorption activation energy (E_a) was calculated by considering the equilibrium constants under the different experimental conditions (Table 4) (The detailed equation is provided with Supplementary material).

4.1 Effect chemical treatment on biosorption

The acid treated neem leaves itself has the lower capacity to adsorb As(III) and As(V). Its main function was to provide a template with high specific area for MnFe₂O₄ loading. Untreated neem leaves (NL), utilized in water treatment facilities, occupies mainly negatively charged surface due to hydroxyl group at neutral pH and therefore was not a good biosorbent for negatively charged/neutral arsenic. The hydroxyl groups can offer chemical reaction sites and adsorb iron and manganese ions to grow MnFe₂O₄ particles. The reason may be that the template can prevent MnFe₂O₄ particles from aggregating in biosorption process and enhance the effective biosorption area, resulting in the highly enhancement of biosorption capacity (Mohan and Pittman, 2007). Loading of MnFe₂O₄ increased the positive charge density on the biosorbent surface by neutralizing negative surface charge and creating positive charge in its place (Mondal et al., 2009). Mondal et al. (2007a, 2010) have reported that impregnation of Ca on the surface of GAC also increased the positive charge on the surface of GAC and finally improved the adsorption capacity of GAC. By comparing the arsenic adsorption capacity of MnFe₂O₄ with and without the template in Table 5, it was observed the adsorption capacities of MnFe₂O₄ loading on the acid treated GAC are much higher than the bare ones. Hereby, the introduction of acid treated GAC template can efficiently improve the adsorption capacity. The reason may be that the template can prevent MnFe₂O₄ particles from aggregating in adsorption process and enhance the effective adsorption area, resulting in the highly enhancement of adsorption capacity. A similar finding has been found out for the loading of Fe₃O₄ on pure wheat straw (Tian et al., 2011).

4.2 Effect of contact time

Fig. 1 shows the effect of contact time on the % removal of As(III) and As(V) employing immobilized bacterium. The time needed to grasp equilibrium for sequestering of both As(III) and As(V) was 260 min. For further increase in time, no significant enhancements was detected in eliminating arsenic. Thus, further biosorption/bioaccumulation studies were performed for a contact time of 260 min.

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Figure 1

Effect of contact time on As(III) and As(V) removal in SBB studies (C₀: 50 mg/L; T: 30 °C; pH: 7.0; M: 1 g/L) (Error bars represent means ± standard errors from the mean of duplicate experiments).

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From the results it is again understandable that in all the systems, the saturation time does not be governed by the adsorbate concentration in the solution. The change in the rate of removal might be owing to the fact that initially all sites of surfaces of immobilized bacterial cells are definitely obtainable and also the concentration gradient of adsorbate is very high. At optimum pH, the rapid kinetics of interaction of adsorbate-immobilized bacterial cells might be recognized to increase availability of the active sites of the surface of immobilized bacterial cells. Thus the removal of adsorbate was rapid in the early stages and gradually drops with the interval of time until equilibrium in each case. The reduction in removal of metal ion at the later stage of the process was owing to the decreasing of concentration of metal ions (Mishra et al., 2010). So the curves found were single, smooth and continuous leading to equilibrium and suggested the probability of monolayer coverage of the adsorbate onto the surface of immobilized bacterial cells (Ranjan et al., 2009).

4.3 Biosorption kinetic studies

Evidence on the kinetics of adsorbate uptake is substantial to fix optimum operating conditions for full scale batch process. As a non-linearizable kinetic model and with the purpose of comparing its fitting ability to the previous considered models, a nonlinear regression analysis was accomplished to the 14 adsorption kinetic models. Table 6 shows the values of kinetic constants of all the models for the biosorption/bioaccumulation of both As(III) and As(V) by immobilized bacterial cells. The results exhibited that there was no noticeable relationship between the kinetic data for both As(III) and As(V) (Fig. 2(a and b) with low correlation coefficients and high error values indicating that these models (fractional power, pseudo first order, Elovich and exponential) are not appropriate in the current case.

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Figure 2

Kinetic modelling of (a) As(III) and (b) As(V) biosorption/bioaccumulation onto the immobilized bacterial cells (t: 5–500 min; C₀: 50 mg/L; M: 1 g/L; pH: 7.0; T: 30 °C) (Error bars represent means ± standard errors from the mean of duplicate experiments).

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On the basis of maximum correlation coefficients (R, R² and ${\bar{R}}^2$ ) and lowest error values (SSE, reduced χ² and Root-MSE), the superior and perfect fitting of the experimental results was found using Fractal-like mixed 1, 2 order for As(III) (Fig. 2(a)) among all the tested kinetic models.

In case of Fractal-like mixed 1, 2 order model the adsorption rate coefficient is deliberated a function of time by utilizing the fractal-like idea. One of the possible physical meanings of fractal-like kinetics was that adsorption of As(III) occurred at solid/solution interface. In this approach it was showed that by passing time, various paths for adsorption of As(III) on surface appear (Haerifar and Azizian, 2012a, 2012b).

In case of As(V) on the basis of maximum correlation coefficients (R and R²) and the lowest error value (SSE), the superior and perfect fitting of the experimental consequences was found using Brouser–Weron–Sototlongo (Fig. 2(b)) among all the verified kinetic models while on the basis of maximum correlation coefficient ${\bar{R}}^2$ and the lowest error values (reduced χ² and Root-MSE), the better and perfect demonstration of the experimental results was attained utilizing Fractal-like pseudo second order kinetic model (Fig. 2(a and b)) among all the well-known kinetic models.

Returning to the theory beyond the best fitting model (i.e. BWS), the biosorption/bioaccumulation phenomenon of both As(III) and As(V) on immobilized bacterial cells would be governed by chemisorption interactions type, clarifying that the rate controlling step might be chemical adsorption including valency forces via exchange or sharing of electrons between As(III) or As(V) anions and immobilized bacterial cells. Also the BWS model expresses another significant data which is the time significant to adsorb half the maximum amount (τ_nBWS,α).

As shown in Table 6, with respect to initial arsenic concentration, 8.64232 min and 10.97291 min (the lowest value) were adequate to immobilized bacterial cells to reach half of the As(III) and As(V) uptake capacities, respectively, which is important as well as valuable parameter for computing the reaction speed.

As for the BSW model itself, it has a good fitting behavior and more implicitly, it states such quality data (i.e. adsorption capacity nearest to experimental value, q_e(BWS), and the time of half reaction, τ_nBWS,α) which are esteemed aimed at industrial treatment design purposes (Ncibi et al., 2014).

Following adsorption kinetic data with the Fractal-like pseudo second order model recognize that the adsorption rate coefficient is a function of time; furthermore the adsorption path on the active site varies with time (Haerifar and Azizian, 2012b).

On the basis of good correlation coefficient (R, R² and ${\bar{R}}^2$ ) and low error values (SSE, reduced χ² and Root-MSE) it can be established that other kinetic models for example pseudo second order, Avrami, modified second order, Ritchie second order, Fractal-like pseudo first order and Fractal-like exponential models also showed good fitting of biosorption/bioaccumulation kinetic data for both As(III) and As(V) on immobilized bacterial cells.

The value of good correlation coefficients (R, R² and ${\bar{R}}^2$ ) and low error values (SSE, reduced χ² and Root-MSE) for pseudo second order model estimates that possible route or mechanism of biosorption/bioaccumulation of arsenic (As(III) or As(V)) on immobilized cells is chemisorption.

4.4 Final remarks on biosorption/bioaccumulation kinetic studies

The value of correlation coefficient (R, R² and ${\bar{R}}^2$ ) and error values (SSE, reduced χ² and Root-MSE) for the Fractal-like mixed 1, 2 order kinetic model was better than that observed using the other kinetic models for As(III). The value of correlation coefficient (R and R²) and error value (SSE) for the Brouser–Weron–Sototlongo model was better than achieved using the other kinetic model for As(V) indicating a complex mechanism of biosorption/bioaccumulation. But based on the obtained correlation coefficient $({\bar{R}}^2)$ and error values (reduced χ² and Root-MSE) the Fractal-like pseudo second order model exhibited the best fit to the biosorption/bioaccumulation kinetic data of As(V) among all the models signifying mechanism of biosorption/bioaccumulation models followed multiple kinetic order. Thus the kinetics of As(V) biosorption/bioaccumulation utilizing immobilized bacterial cells as a biosorbent can be well clarified by the Brouser–Weron–Sototlongo as well as Fractal–like pseudo second order kinetic models.

Among the models the pseudo-second-order model also possessed a good fitness with experimental kinetic data. This tendency comes as an suggestion that the rate limiting step in biosorption/bioaccumulation of arsenic (either As(III) or As(V)) is chemisorption involving valence forces through the sharing or exchange of electrons between immobilized bacterial cells and arsenic (either As(III) or As(V)) ions (Guo et al., 2008; Miretzky et al., 2008), complexation, coordination and/or chelation (Yu et al., 2007; Lu and Gibb, 2008).

It is significant for determining the rate at which both As(III) and As(V) are biosorbed/bioaccumulated on the surface of immobilized bacterial cells that is significant for designing fixed bed adsorption column. Utilizing the biosorption/bioaccumulation rate, kinetic constants are estimated to describe the equilibrium capacity of immobilized bacterial cells and mass transfer coefficient at various aqueous phase concentrations. Amount of As(III) or As(V) biosorbed/bioaccumulated on solid surface is calculated using the kinetic equation which is vital for esteeming the concentration of the aqueous phase in fixed bed column operation. The key design factors of fixed bed adsorption column, the breakthrough time in addition to the shape of breakthrough curve are reliant on biosorption/bioaccumulation rate. For the faster biosorption/bioaccumulation rate, breakpoint time is reached earlier also the breakthrough curve shape is steeper.

The descriptive models from the best to worst for As(III) and As(V) were sorted according to GoFM values and shown Tables S1 and S2 of Supplementary material, respectively.

So at this point, the fitting “ambiguity” influenced by the correlation coefficient (R, R² and ${\bar{R}}^2$ ) and error values (SSE, reduced χ² and Root-MSE) was for As(V), because the correlation coefficient (R and R²) and error values (SSE) established the Brouser–Weron–Sototlongo as best fitting model (highest correlation coefficient and lowest error values) whereas correlation coefficient $({\bar{R}}^2)$ and error values (reduced χ² and Root-MSE) exhibited that the Fractal–like pseudo second order kinetic model is the best fitting model (highest correlation coefficient and lowest error values). So, for overcoming this doubt, it would be modest and practical for comparing the theoretically estimated q_e values with the experimental ones.

According to correlation coefficient ${\bar{R}}^2$ values the fitness of the models for all kinetic models is almost equivalent to each other. So based on equivalent adsorption capacity, the orders followed by the models in decreasing manner are shown in Table S3 of Supplementary material.

4.5 Biosorption mechanistic studies

4.5.1

4.5.1 Intraparticle diffusion model

Outcomes of intraparticle model for both As(III) and As(V) are shown in Table 7. Fig. 3(a and b) stated the multi-linear nature of intraparticle model. As the plot did not pass through the origin, so intraparticle diffusion was not the single rate monitoring step. Therefore there were three processes governing the rate of biosorption/bioaccumulation, though only one was rate monitoring in any certain time range. The intraparticle diffusion rate constant k_int2 for both As(III) and As(V) was evaluated from the slope of the second linear portion ((Fig. 3(a and b)) and Table 7). The multi-linear curve of the intraparticle model with intercept C_int2 stated the fact that both intraparticle diffusion of adsorbate through the mesoporus openings filled with liquid and film/external mass transfer across the thickness of boundary layer were the rate monitoring steps in the biosorption/bioaccumulation of both As(III) and As(V) kinetics on the surface of immobilized bacterial cells. The value of intercept C_int acquired through the model showed the value of thickness of boundary layer of liquid adjoining the immobilized bacterial cells (Kavitha and Namasivayam, 2007).

Table 7 Mechanistic constants of studied models for As(III) and As(V) biosorption/bioaccumulation onto C. glutamicum MTCC 2745 immobilized on surface of NL/MnFe₂O₄ composite.

Mechanistic models	Parameters	Values for As(III)	Values for As(V)
Intraparticle diffusion model	kint1 (mg/g min0.5)	5.7974	5.98548
	Cint1 (mg/g)	1.48906	2.17863
	kint2 (mg/g min0.5)	0.87058	0.85048
	Cint2 (mg/g)	30.38403	33.13512
	${\bar{R}}_1^2$	0.98605	0.98382
	${\bar{R}}_2^2$	0.99438	0.98725
Determination of rate limiting step	D1 (cm2/s)	1.14465E−05	1.13736E−05
	D2 (cm2/s)	4.9428E−06	5.23936E−06
Dumwald–Wagner model	kDW (1/min)	0.02800448	0.01379497
	${\bar{R}}^2$	0.97582	0.96049
Richenberg model	${\bar{R}}^2$	0.95259	0.96049
McKay plot	kM1 (1/min)	0.03499	0.03607
	kM2 (1/min)	0.01385	0.01395
	${\bar{R}}_1^2$	0.94449	0.94822
	${\bar{R}}_2^2$	0.9343	0.93809
Bangham’s model	kb (L/g)	24.53996494	25.29204454
	αb	0.3992	0.42769
	${\bar{R}}^2$	0.9382	0.96011
Diffusion coefficient	Dp (cm2/s)	1.35896E−07	1.37905E−07
	Df (cm2/s)	1.50427E−07	2.40163E−07
Diffusivity	De (m2/s)	4.64E−14	4.95E−14
	${\bar{R}}^2$	0.95191	0.96055

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Figure 3

Intraparticle diffusion modelling of (a) As(III) and (b) As(V) biosorption/bioaccumulation onto the immobilized bacterial cells (t: 5–500 min; C₀: 50 mg/L; M: 1 g/L; pH: 7.0; T: 30 °C) (Error bars represent means ± standard errors from the mean of duplicate experiments).

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The explanation of the random data points found in Fig. 3(a and b) and Table 7 specified that intraparticle mechanistic model had been appropriate to cost-effectively and proficiently describe the biosorption/bioaccumulation of both As(III) and As(V)) on the surface of immobilized bacterial cells in terms of linear regression coefficient Adjusted R-square $({\bar{R}}^2)$ , ranging between 0.98382 and 0.99438 in both case. Larger value of intercepts achieved for second linear portion i.e. C_int2 recommended that the film diffusion had played an important role as the rate monitoring step (Rengaraj et al., 2007).

4.5.3

4.5.3 Dumwald–Wagner model

The plot (Fig. 4(a and b)) of log (1 − F²) versus t has conveyed almost linear curves $({\bar{R}}^2⩾0.96049)$ for the sequestering of both As(III) and As(V) immobilized bacterial cells, respectively, but did not pass through the origin suggesting that the diffusion of adsorbate into pores of the immobilized bacterial cells was not the single rate monitoring step in both cases. Table 7 displays the evaluated outcomes of Dumwald–Wagner model. In the current study the linearity of the plots intersected the origin of coordinates; thus film diffusion process was the rate monitoring step.

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Figure 4

Dumwald–Wagner modelling of (a) As(III) and (b) As(V) biosorption/bioaccumulation onto the immobilized bacterial cells (t: 5–500 min; C₀: 50 mg/L; M: 1 g/L; pH: 7.0; T: 30 °C) (Error bars represent means ± standard errors from the mean of duplicate experiments).

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4.5.4

4.5.4 Richenberg model or Boyd plot

The outcomes of the corresponding model for both As(III) and As(V) are displayed in Table 7 and Fig. 5(a and b), respectively. From the plots of B_bt versus t, it was observed that the plots had dynamic linear form with a high correlation coefficient (Adjusted R-square $({\bar{R}}^2)$ ) for both As(III) and As(V) at examined temperature and but did not pass through origin which had chosen the current biosorption/bioaccumulation processes to be monitored by film diffusion mechanism.

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Figure 5

Richenberg modelling of (a) As(III) and (b) As(V) biosorption/bioaccumulation onto the immobilized bacterial cells (t: 5–500 min; C₀: 50 mg/L; M: 1 g/L; pH: 7.0; T: 30 °C) (Error bars represent means ± standard errors from the mean of duplicate experiments).

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4.5.5

4.5.5 Film diffusion mass transfer rate equation or McKay plot

The values achieved for ln(1 − F) as a function of time t, were plotted in Fig. 6(a and b) for As(III) and As(V), respectively and the outcomes of the respective model for both As(III) and As(V) are publicized in Table 7. The rate constant of the initial fast process (k_M1) was evaluated from the slope of the first straight line (Fig. 6(a and b)). As can be understood from Fig. 6(a and b), the rate constant of the slow process (k_M2) was achieved from the slope of the second linear portion. It is clear that the initial fast process was controlled by film diffusion. Also the values of k_M2 are smaller than the values of k_M1 for both As(III) and As(V). Thus the attained values of k_M2 were indication of a pore diffusion mechanism in the second stage of the biosorption/bioaccumulation (Atun and Hisarli, 2003). The presence of two straight lines for both As(III) and As(V) specified that two processes i.e. film diffusion and pore diffusion had involved in these processes.

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Figure 6

McKay plot of (a) As(III) and (b) As(V) biosorption/bioaccumulation onto the immobilized bacterial cells (t: 5–500 min; C₀: 50 mg/L; M: 1 g/L; pH: 7.0; T: 30 °C) (Error bars represent means ± standard errors from the mean of duplicate experiments).

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The plots were about linear for both As(III) and As(V), but it did not yield perfect linearity. Thus pore diffusion was not the rate monitoring step. In the current study film diffusion was the rate monitoring step.

4.5.6

4.5.6 Bangham’s model

The results of the respective model for both As(III) and As(V) are shown in Table 7 and (Fig. 7(a and b)). The goodness of fit of curve for Bangham’s model was related in terms of correlation coefficient Adjusted R-square $({\bar{R}}^2)$ . The double logarithmic plot (Fig. 7(a and b) for As(III) and As(V), respectively) as specified by above equation did not return perfect linear curves and some data were random $({\bar{R}}^2⩽0.96011)$ for the scavenging of As(III) and As(V) by immobilized bacterial cells revealing that the diffusion of adsorbate within pores of the immobilized bacterial cells was not only the rate monitoring step (Weber and Morris, 1963), film diffusion also had influence on the rate monitoring step.

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Figure 7

Bangham modelling of (a) As(III) and (b) As(V) biosorption/bioaccumulation onto the immobilized bacterial cells (t: 5–500 min; C₀: 50 mg/L; M: 1 g/L; pH: 7.0; T: 30 °C) (Error bars represent means ± standard errors from the mean of duplicate experiments).

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4.5.8

4.5.8 Determination of diffusivity

From the slope π²D_e/r² of the plot of ln[1/(1 − F²)] versus t (Fig. 8(a and b) and Table 7), the value of diffusion coefficient, D_e as evaluated, was found to be 5.44 × 10⁻¹⁴ m²/s and 5.63 × 10⁻¹⁴ m²/s for As(III) and As(V) biosorption/bioaccumulation on the surface of immobilized bacterial cells, respectively. For the current study, the value of D_e falls within the range of 10⁻⁹–10⁻¹⁷ m²/s, so the system was chemisorption system. The values of the diffusion coefficient, D_e, shown in Table 7 fell well within the magnitudes reported in the literature (Naiya et al., 2009; Singha and Das, 2011).

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Figure 8

Diffusivity of (a) As(III) and (b) As(V) biosorption/bioaccumulation onto the immobilized bacterial cells (t: 5–500 min; C₀: 50 mg/L; M: 1 g/L; pH: 7.0; T: 30 °C) (Error bars represent means ± standard errors from the mean of duplicate experiments).

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4.6 Final remarks on biosorption/bioaccumulation mechanistic studies

Adsorption kinetics mechanism can determined from the mechanistic study. The above considered models for biosorption/bioaccumulation of both As(III) and As(V) indicated that two processes i.e. film diffusion (diffusion of adsorbate through the solution to the external surface of biosorbent or boundary layer diffusion of adsorbate) and pore diffusion (diffusion of the adsorbate from the surface film into the pores) were tangled in the current biosorption/bioaccumulation processes for both As(III) and As(V) and pore diffusion was not the single rate governing step. Generally, film diffusion controlled the rate monitoring step in both cases. The uptake of arsenic (As(III) or As(V)) species from the liquid to the solid phase was carried out in three consecutive steps (Al-Degs et al., 2008). Firstly, film diffusion occurred. Secondly, pore diffusion took place. The third step is the biosorption which is being very rapid in nature and cannot be taken into account for the rate determining step (Singh and Pant, 2006).

4.7 Effect of temperature

The temperature has two main effects on the biosorption/bioaccumulation process. Temperature dependence of the biosorption/bioaccumulation system directs the biosorption/bioaccumulation as endothermic or exothermic. Rising the temperature is known for increasing the diffusion rate of the adsorbate, owing to the drop in the solution viscosity. Similarly varying the temperature will change the equilibrium adsorption capacity of the immobilized bacterial cells for a specific biosorbent (Nouri et al., 2007).

The influence of temperature on the removal efficiency of As(III) and As(V) was examined in the range of 20–50 °C throughout the equilibrium time. The consequences of influence of temperature have been exposed in Fig. 9. It was observed from the Fig. 9 that with a little increase in temperature from 20 to 30 °C, the biosorption/bioaccumulation of arsenic (As(III) or As(V)) ions on immobilized bacterial cell surface increased. After 30 °C temperature, the removal of arsenic (As(III) or As(V)) ions by immobilized bacterial cell decreased with the increase in temperature. For As(III) and As(V), % removal decreased from 88.26087% to 76.95652% and 92.53846% to 83.30769%, respectively, with increase in temperature from 30 to 50 °C. Temperature influences the interaction between the biomass and the metal ions, generally by impacting on the stability of the metal-sorbent complex and the ionization of the cell wall moieties (Sag and Kutsal, 1995).

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Figure 9

Effect of temperature on As(III) and As(V) removal in SBB studies (C₀: 50 mg/L; pH: 7.0; M: 1 g/L; t: 260 min) (Error bars represent means ± standard errors from the mean of duplicate experiments).

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The temperature of the biosorption solution could be vital for energy dependent mechanisms in metal binding process (Green-Ruiz et al., 2008). Energy independent mechanisms are less expected to be influenced by temperature because the processes responsible for biosorption are mainly physico-chemical in nature (Kacar et al., 2002; Ozdemir et al., 2009). The results acquired in the current study indicated that the metal ion sorption in SBB system was exothermic. Kacar et al. (2002) and Ozdemir et al. (2009) reported in their work about the exothermic behavior of metal ion sorption on the bacterial surface. The authors correlated their research outcomes as an energy independent mediated sorption of metal ions.

This can also be clarified by the spontaneity of the biosorption/bioaccumulation process. This decrease in scavenging efficiency might be due to many issues: the relative increase in the avoidance tendency of the arsenic ions from the solid phase of immobilized bacterial cells to the bulk liquid phase; deactivating the surface of immobilized bacterial cells or destructing some active sites onto the surface of immobilized bacterial cells because of bond ruptures (Meena et al., 2005; Romero-Gonźalez et al., 2005) or due to the weakening of adsorptive forces between the adsorbate species and the active sites of the immobilized bacterial cells and also between the adjacent molecules of adsorbed phase for high temperatures or movement of immobilized bacterial cells with higher speed, so, lower interaction time with the active sites of immobilized bacterial cells was obtainable for them (Yadav and Tyagi, 1987; Roy et al., 2014).

4.8 Biosorption thermodynamic studies

The evaluated values of the thermodynamic parameters from the plot of ln k_d versus 1/T (Fig. 10(a and b)) are shown in Table 8. The equilibrium constant k_d was evaluated, while the temperature was altered between 20 and 50 °C for both As(III) and As(V). The maximum scavenging of adsorbate was attained at 30 °C in both cases. The scavenging efficiency initially increased with increasing the temperature from 20 to 30 °C. Then it declined with rising the temperature from 30 to 50 °C. The ΔH⁰ values achieved for the biosorption/bioaccumulation of both As(III) and As(V) were negative owing to the exothermic nature of the biosorption/bioaccumulation process. The value achieved for As(V) biosorption/bioaccumulation was more than the value attained for As(III). A negative value of ΔG⁰ specified the spontaneous nature of the biosorption/bioaccumulation process, though the negative value of ΔS⁰ exhibited a decrease in the randomness at the solid/solution interface throughout the biosorption/bioaccumulation process (Ngah and Hanafiah, 2008). Higher negative value of ΔG⁰ at a temperature of 30 °C, as was achieved in the study, decided more driving force for biosorption/bioaccumulation at 30 °C (Crini and Badot, 2008). The values of ΔG⁰ achieved in the current research were between −21.35 to −22.48 KJ/mol and −22.46 to −23.74 KJ/mol for As(III) and As(V), respectively. So it stated that the mechanism of present biosorption/bioaccumulation process had happened via ion exchange and/or surface complexation mechanism.

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Figure 10

Thermodynamic modelling of (a) As(III) and (b) As(V) biosorption/bioaccumulation onto the immobilized bacterial cells (T: 20–50 °C; C₀: 50 mg/L; pH: 7.0; M: 1 g/L; t: 260 min) (Error bars represent means ± standard errors from the mean of duplicate experiments).

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4.9 Effect of initial arsenic concentration on biosorption/bioaccumulation kinetics

To analysis the influence of initial concentration on kinetic studies, a series of contact time experiments for both As(III) and As(V) was performed at various initial concentration (50–2000 mg/L) at temperature of 30 °C. (Fig. S2(a and b) of Supplementary material) showed the contact time important for both As(III) and As(V) with initial concentration of 50–1000 mg/L for achieving equilibrium was 260 min. However for both As(III) and As(V) with higher initial concentration (>1000–2000 mg/L), higher equilibrium time of 340 min was required. As can be seen from Fig. S2(a and b) of Supplementary material, the amount of the biosorbed/bioaccumulated both As(III) and As(V) on the surface of immobilized bacterial cells changed with time and at some point in time achieved a constant value further than no more As(III) or As(V) was removed from solution. At the moment the amount of the both As(III) and As(V) desorbing from the biosorbent was in a state of dynamic equilibrium with the amount of both As(III) and As(V) being biosorbed/bioaccumulated on the surface of immobilized bacterial cells. The time necessary for accomplishment of this state of equilibrium is called the equilibrium time. Thus the rate of biosorption/bioaccumulation decreased with time till it regularly tending to a plateau owing to the constant decline in the concentration driving force.

4.10 Determination of initial sorption rate

From Fig. 11(a and b) and Table 9, it is noticeable that the pseudo second order rate constants (k_PSO) were observed to drop and the initial sorption rates (h) were agreed to rise with higher initial concentration of both As(III) and As(V). The initial sorption rate was larger for higher initial As(III) and As(V) concentration as the resistance to uptake both As(III) and As(V) reduced as the mass transfer driving force enhanced.

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Figure 11

Determination of the initial sorption rate for biosorption/bioaccumulation of As(III) and As(V) onto the immobilized bacterial cells (C₀: 50–2000 mg/L; t: 5–500 min; pH: 7.0; M: 1 g/L; T: 30 °C) (Error bars represent means ± standard errors from the mean of duplicate experiments).

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The computed q_e(PSO) values recognized just appropriate with the experimental data and high correlation coefficient (R, R² and ${\bar{R}}^2$ ) and low error values (SSE, reduced χ² and Root-MSE) publicized that the model can be utilized for the whole biosorption/bioaccumulation process and allowed the chemisorption of both As(III) and As(V) on immobilized bacterial cells.

4.11 Effect of temperature on biosorption/bioaccumulation kinetic

Temperature is a notable factor governing the biosorption/bioaccumulation process. The influence of temperature onto the of biosorption/bioaccumulation of both As(III) and As(V) by immobilized bacterial cells was done from 30 to 50 °C at C₀ is 50 mg/L and NL/MnFe₂O₄ composite loading is 1 g/L. A declining biosorption rate of both As(III) and As(V) with rising temperature from 30 to 50 °C acknowledged the process to be exothermic (Fig. S3(a and b) of Supplementary material). This is considered before concerning thermodynamic parameters in Section 4.7.

4.12 Biosorption activation energy

Biosorption/bioaccumulation rate constants k_PSO of both As(III) and As(V) were evaluated from experimental data at a different temperatures supposing nonlinear form of pseudo second order kinetics. Parameters of Arrhenius equation were fitted utilizing these rate constants for estimating temperature independent rate parameters and biosorption/bioaccumulation type. A plot of ln k_PSO versus 1/T showed a straight line with slope −E_a/R (Fig. 12 and Table 10). The magnitude of activation energy for As(III) and As(V) biosorption/bioaccumulation on immobilized bacterial cells was 10.18 KJ/mol and 10.22 KJ/mol signifying that both the biosorption/bioaccumulation of As(III) and As(V) onto the surface of immobilized bacterial cells was activated chemisorption.

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Figure 12

Determination of the activation energy for As(III) and As(V) biosorption/bioaccumulation onto the immobilized bacterial cells (T: 30–50 °C; t: 5–500 min; C₀: 50 mg/L; pH: 7.0; M: 1 g/L) (Error bars represent means ± standard errors from the mean of duplicate experiments).

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4.13 Characterization

4.13.1

4.13.1 SEM-EDX analysis

Fig. 13(a and b) exhibited the morphology of As(III) and As(V) acclimatized C. glutamicum MTCC 2745 bacterial cells, respectively. From the figure, it is obvious that they were basically rod-like shape. The SEM images of the prepared fresh NL/MnFe₂O₄ composite (Fig. 13(c)) and As(III) acclimatized C. glutamicum MTCC 2745 immobilized on surface of NL/MnFe₂O₄ composite at stage of unloaded and loaded with As(III) (Fig. 13(d and e)) and As(V) acclimatized C. glutamicum MTCC 2745 immobilized on surface of NL/MnFe₂O₄ composite at stage of unloaded and loaded with As(V) (Fig. 13(f and g)) were also shown. It can be understood from Fig. 13(c), manganese ferrite (MnFe₂O₄) particles with numerous diameters were arbitrarily distributed onto the acid treated NL surface. It is clear from Fig. 13(d and f) that most of the active sites of NL/MnFe₂O₄ composite were shielded owing to the formation of biofilm on it (Mondal et al., 2008). A change in surface morphology from being smooth to rough and existence of pores specified the As(III) and As(V) biosorption/bioaccumulation onto the surface and pores of NL/MnFe₂O₄ composite providing it a rough texture (Fig. 13(e and g)). The corresponding EDX spectra of the As(III) and As(V) acclimatized bacteria and the unloaded and loaded immobilized bacterial cells were collected and shown in Fig. 13(a–g). The presence of iron, manganese and oxygen onto the unloaded composite surface and iron, manganese and oxygen, arsenic on the surface of loaded immobilized bacterial cells was shown clearly. This outcome again recognized the attendance of MnFe₂O₄ particles onto the acid treated NL surface in addition to biosorption/bioaccumulation of arsenic onto the surface of immobilized bacterial cells.

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Figure 13

Scanning electron micrographs (SEM) and EDX of (a) As(III) acclimatized living cells of C. glutamicum MTCC 2745 at loaded stage, (b) As(V) acclimatized living cells of C. glutamicum MTCC 2745 (original magnification, 5000×), (c) fresh NL/MnFe₂O₄ composite, (d) As(III) acclimatized C. glutamicum MTCC 2745 immobilized on NL/MnFe₂O₄ composite at unloaded stage, (e) As(III) acclimatized C. glutamicum MTCC 2745 immobilized on NL/MnFe₂O₄ composite at loaded stage, (f) As(V) acclimatized C. glutamicum MTCC 2745 immobilized on NL/MnFe₂O₄ composite at unloaded stage and (g) As(V) acclimatized C. glutamicum MTCC 2745 immobilized on NL/MnFe₂O₄ composite at loaded stage (original magnification, 500×).

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Figure 13

Scanning electron micrographs (SEM) and EDX of (a) As(III) acclimatized living cells of C. glutamicum MTCC 2745 at loaded stage, (b) As(V) acclimatized living cells of C. glutamicum MTCC 2745 (original magnification, 5000×), (c) fresh NL/MnFe₂O₄ composite, (d) As(III) acclimatized C. glutamicum MTCC 2745 immobilized on NL/MnFe₂O₄ composite at unloaded stage, (e) As(III) acclimatized C. glutamicum MTCC 2745 immobilized on NL/MnFe₂O₄ composite at loaded stage, (f) As(V) acclimatized C. glutamicum MTCC 2745 immobilized on NL/MnFe₂O₄ composite at unloaded stage and (g) As(V) acclimatized C. glutamicum MTCC 2745 immobilized on NL/MnFe₂O₄ composite at loaded stage (original magnification, 500×).

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4.13.2

4.13.2 FT–IR analysis

The adsorption capacity of heavy metal on various adsorbents depends on the presence of several active functional groups onto the surface of adsorbent. The Fourier Transform Infrared spectra (FT–IR) study of fresh NL/MnFe₂O₄ composite as well as As(III) acclimatized C. glutamicum MTCC 2745 immobilized on surface of NL/MnFe₂O₄ composite at unloaded and metal loaded stage (Fig. 14(a)) and fresh NL/MnFe₂O₄ composite plus As(V) acclimatized C. glutamicum MTCC 2745 immobilized on surface of NL/MnFe₂O₄ composite at unloaded and metal loaded stage (Fig. 14(b)) at optimized batch experimental condition were observed for identifying the function groups responsible mainly for the process of biosorption/bioaccumulation. Tables S4 and S5 of Supplementary material specify the wavenumber for the many functional groups present in the fresh NL/MnFe₂O₄ composite and As(III) acclimatized C. glutamicum MTCC 2745 immobilized on surface of NL/MnFe₂O₄ composite at As(III) unloaded and loaded stage and fresh NL/MnFe₂O₄ composite and As(V) acclimatized C. glutamicum MTCC 2745 immobilized on surface of NL/MnFe₂O₄ composite at As(V) unloaded and loaded stage, respectively. Surface —OH and —NH groups were main active functional groups answerable for biosorption/bioaccumulation as the wavenumber shifted from 3430.796 cm⁻¹ to 3436.582 cm⁻¹ (As(III)) and from 3436.582 cm⁻¹ to 3426.977 cm⁻¹ (As(V)) which may be probably owing to the complexation of —OH groups with As(III) or As(V) ions (Pangnanelli et al., 2000; Ray et al., 2005; Allievi et al., 2011; Singha and Das, 2011). Some researchers have also specified that after the adsorption arsenic on the Fe—Ce and Fe—Mn adsorbents, the peak of hydroxyl groups reduced or vanished (Zhang et al., 2005, 2007). Aliphatic C—H stretching may be responsible for biosorption/bioaccumulation of As(III) and As(V) onto NL/MnFe₂O₄ composite as wavenumber shifted from 2919.69 cm⁻¹ to 2924.651 cm⁻¹ and from 2921.673 cm⁻¹ to 2919.69 cm⁻¹, respectively, possibly owing to the complexation of C—H stretching vibration of alkyl chains. Aldehyde C—H stretching may be responsible for biosorption/bioaccumulation of As(III) and As(V) onto NL/MnFe₂O₄ composite as wavenumber shifted from 2854.176 cm⁻¹ to 2852.093 cm⁻¹ and from 2854.176 cm⁻¹ to 2852.093 cm⁻¹, respectively. Tables S4 and S5 of Supplementary material also display the responsibility of aliphatic acid C⚌O stretching for As(III) and As(V) biosorption/bioaccumulation by shifting the wavenumber from 1728.992 cm⁻¹ to 1735.647 cm⁻¹ and from 1737.576 cm⁻¹ to 1729.612 cm⁻¹, respectively (Singha and Das, 2011). The next biosorption/bioaccumulation peaks at 1640.93 cm⁻¹ shifted to 1635.969 cm⁻¹ for As(III) and 1640.93 cm⁻¹ shifted to 1635.366 cm⁻¹ for As(V), perhaps due to the complexation of amide group (N—H stretching and C⚌O stretching vibration) with As(III) and As(V) ions (Seki et al., 2005). Wavenumber shifted from 1629.58 cm⁻¹ to 1631.008 cm⁻¹ (As(III)) and from 1630.388 cm⁻¹ to 1620.465 cm⁻¹ (As(V)) which gave the reactivity of unsaturated group like alkene for the biosorption/bioaccumulation process. Tables S4 and S5 of Supplementary material also exhibit the intense bands at 1527.37 cm⁻¹ and 1554.369 cm⁻¹ which shifted to 1532.403 cm⁻¹ (As(III)) and at 1548.583 cm⁻¹, shifted to 1517.727 cm⁻¹ (As(V)), respectively, that indicated the responsibility of aromatic —NO₂ group for the biosorption/bioaccumulation process, respectively. Another shift was detected from 1449.302 cm⁻¹ to 1459.845 cm⁻¹ (As(III)) and from 1449.302 cm⁻¹ to 1452.158 cm⁻¹ (As(V)), corresponding to the complexation of nitrogen with As(III) and As(V) ions of the N—H group (Kumari et al., 2006; François et al., 2012). Wavenumber shifted from 1428.837 cm⁻¹ to 1438.76 cm⁻¹ (As(III)) and from 1428.837 cm⁻¹ to 1439.38 cm⁻¹ As(V) assigned the reactivity of alkane group for the biosorption/bioaccumulation process (Baig et al., 2010). Wavenumber shifted from 1154.729 cm⁻¹ to 1164.651 cm⁻¹ (As(III)) and from 1162.884 cm⁻¹ to 1164.651 cm⁻¹ (As(V)) assigned the reactivity of sulphonyl chloride stretching for the biosorption/bioaccumulation process (Baig et al., 2010). Wavenumber 1116.6 cm⁻¹ shifted to 1118.14 cm⁻¹ and 1110.814 cm⁻¹ shifted to 1112.743 cm⁻¹ assigned for C—S stretching for the biosorption/bioaccumulation of As(III) and As(V), respectively. The peaks at 1061.08527 cm⁻¹ (As(III)) and 1056.124 cm⁻¹ As(V) may be attributed to the C—N stretching vibrations of amino groups which shifted to higher frequency and appeared at 1051.031 cm⁻¹ and 1052.959 cm⁻¹, respectively, due to the interaction of nitrogen from the amino group with As(III) and As(V) ions (Baciocchi et al., 2005; Giri et al., 2011). The other weak biosorption/bioaccumulation peak shifted from 890.543 cm⁻¹ to 833.488 cm⁻¹ (As(III)) and from 890.543 cm⁻¹ to 906.047 cm⁻¹, corresponding to the O—C—O scissoring vibration of polysaccharide (Merroun et al., 2005; Pokhrel and Viraraghavan, 2007).The band at 599.763 cm⁻¹ (Fig. 14(a)) and 603.62 cm⁻¹ (Fig. 14(b)) could be attributed to the existence of Fe—O bond (McCafferty, 2010; Ren et al., 2012), but then it shifted to 610.853 cm⁻¹ after biosorption/bioaccumulation of As(III) (Fig. 14(a)) and to 593.977 cm⁻¹ after biosorption/bioaccumulation of As(V) (Fig. 14(b)), respectively. A typical peak at 565.05 cm⁻¹ (Fig. 14(a)) and 590.388 cm⁻¹ (Fig. 14(b)) could be assigned to Mn—O bond (Kohler et al., 1997; Parida et al., 2004) and it had a different variability to 574.884 cm⁻¹ (Fig. 14(a)) and 532.265 cm⁻¹ (Fig. 14(b)) for biosorption/bioaccumulation of As(III) and As(V), respectively. The change in wavenumber of Me—O bonds after biosorption/bioaccumulation of As(III) and As(V) indicated that both Fe—O and Mn—O bonds were responsible for both MnFe₂O₄–As(III) and MnFe₂O₄–As(V) (Li et al., 2010; Ren et al., 2012). Presence of As(III) and As(V) on the immobilized bacterial cells can be assured from the bands appeared at 782.016 cm⁻¹ (Fig. 14(a)) and 828.527 cm⁻¹ (Fig. 14(b)), respectively (Mondal et al., 2007b; Zhang et al., 2009; Aryal et al., 2010). It has to be cited here, that a clear band was very hard to be got in the case of As(III), compared with the distinctive band of As(III) found at 782.016 cm⁻¹ and As(V) found at 828.527 cm⁻¹. This may be because of different mechanisms involved in As(III) and As(V) biosorption/bioaccumulation. It should be distinguished that the As—O band after biosorption/bioaccumulation of arsenic was not clearly observed because of the broad overlapping peaks in this region (Li et al., 2010).

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Figure 14

FT–IR spectra of (a) fresh NL/MnFe₂O₄ composite (MNL), As(III) acclimatized C. glutamicum MTCC 2745 immobilized on NL/MnFe₂O₄ composite before and after As(III) biosorption/bioaccumulation, (b) fresh NL/MnFe₂O₄ composite (MNL), As(V) acclimatized C. glutamicum MTCC 2745 immobilized on NL/MnFe₂O₄ composite before and after As(V) biosorption/bioaccumulation.

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4.14 Viability of bacteria after immobilization

Biosorbent containing (5% v/v) C. glutamicum MTCC 2745 cells was placed on the nutrient agar plates and incubated at 30 °C. After 24 h at this temperature, bacterial cells were detected spreading away from the cut edge of the biosorbent and colony like growth (small areas of butter-textured growth) was observed on the surface of the biosorbent.

The synthetic medium in the flask had turned milky also specifying significant bacterial growth in the flask. This indicated that the bacterial cells survived the immobilization process. Scanning electron micrograph of the bacteria after 24 h of growing in the liquid medium (Fig. 15) is shown.

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Figure 15

Scanning electron micrographs (SEM) and EDX of (a) As(III) acclimatized living cells of C. glutamicum MTCC 2745 after cutting, (b) As(V) acclimatized living cells of C. glutamicum MTCC 2745 after cutting (original magnification, 10,000×).

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