Chromatographic method for pre-concentration and separation of Zn(II) with microalgae and density functional optimization of the extracted species

Abstract

A novel wild strain of microalgae, Phormidium luridum containing Gloeothece rupestris and Chlorococcum infusionum (99 : 0.08 : 0.02), was studied for its ability to remove and retrieve Zn(II) from aqueous solutions in the presence of some commonly occurring ions (Na⁺, K⁺, Cl⁻, SO₄²⁻, ClO₄⁻, NO₃⁻) in their natural contamination concentration range (50–300 mg L⁻¹). The algae, which were previously collected from the river basin (Ajay), were grown on naturally occurring gravels in a glass column of nutrient enriched raw water media. Systematic studies of the sorption of Zn(II) (0.02 mg mL⁻¹) over a pH range of 4.5–7.5 identified a maximum removal extent of 104 μM g⁻¹ at neutral pH, mainly by adsorption at the surface layer. Zn(II) was retrieved by selective elution with 5 × 10⁻³ M HNO₃ solution. Initially, [Zn(H₂O)(OH)]⁺ (η_{[Zn(OH)(H2O)]⁺} = 1.25 eV) is adsorbed at the surface of the algae, which is built up of polysaccharides (η_[glucose] = 6.34 eV), before moving inside by the formation of a more stable complex with Phycocyanobilin2, which has similar hardness (η_{[Phycocyanobilin]} = 2.37 eV). The complex is stabilized by −52 195.48 eV mol⁻¹ through the formation of two strong intramolecular hydrogen bonds (–OH⋯O = 163.54 pm; HOH⋯O = 129.71 pm). Density functional theory optimization corroborates a stable [Zn(H₂O)(OH)]⁺–Phycocyanobilin2 tetrahedral complex.

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1. Introduction

Due to several industrial activities, natural water sources have become contaminated by metallic toxicants.¹ Owing to their tendency to (bio) accumulate throughout the food chain,^2–4 even at trace levels these non-biodegradable contaminants are extremely toxic to humans, as well as to the flora and fauna of the effluent-receiving bodies of water.⁵ It goes without saying that trace level monitoring and measurement of metallic toxicants in real samples poses a challenge to analytical chemists. However, the effect of the matrix has serious implications for sophisticated instrumental methods of analysis.⁶ Sample clean up through preconcentration and selective separation of an analyte is therefore usually necessary before it can be monitored or measured. During preconcentration, ultimately the target species is selectively gathered in a small volume from a large volume of sample of a complex nature. The problem of enrichment can be tackled by two consecutive processes: (1) exploiting selective sorption, the target species is adsorbed by the adsorbent from a large volume sample of low concentration and (2) the analyte is collected in a more concentrated form using a small volume of a selective eluent for its desorption. Small amounts of metal pollutant can, therefore, be quantified by coupling a preconcentration system to a sensitive, selective detection/estimation technique.^7,8 In this regard, the most widely used techniques include solvent extraction,⁹ coprecipitation,^10,11 ion exchange–extraction chromatography,^12,13 adsorption,¹⁴ cloud point extraction,¹⁵ electrochemical deposition,¹⁶ solid phase extraction (SPE).^17–19 However, these classic technologies are often inefficient or too expensive when heavy metals are present at trace level in a real sample with a large amount of matrix.²⁰ Moreover, these need a significant amount of hazardous solvents/chemicals which may increase environmental risks. It is therefore important to devise efficient biosorption methods to remove those toxic elements, with a further requirement of being environmentally-friendly. Metabolic specificity for a given metallic toxicant can be advantageous in bioremediation strategies using bioaccumulation.²¹ Sorption of heavy metals using cyanobacterium as biosorbents offers a potential alternative to conventional processing methods, mainly because of their low cost, strong metal binding capacity, high sorption efficiency in dilute effluents, environmentally-friendliness^22,23 and, more importantly, because of their self-maintained adsorbent beds.²¹ The analytical applicability of Phormidium luridum (microalgae) as a biosorbent for the recovery/removal of Zn(II) has been rationalized for two reasons. Firstly, the extensive use of zinc in galvanization and electroplating,^24,25 without proper downstream recovery, has led to contamination of soil and fresh water habitats. Although zinc is an essential element for activation of some enzymes in human cells, high levels of exposure (100–500 mg day⁻¹) influence apoptosis, causing neuronal death (LD₅₀ = 3 g kg⁻¹ body weight),²⁵ and long-term, high-dose zinc supplementation interferes with the uptake of copper, causing copper deficiency.²⁶ Secondly, a naturally occurring aqua zinc-species, [Zn(H₂O)(OH)]⁺ (η_{[Zn(OH)(H2O)]⁺} = 1.25 eV), will have a high chance of interacting (through the HSAB pathway²⁷) with the extractant (P. luridum) at its surface. The surface, being built up of polysaccharides (glucose is the basic unit of polysaccharides: η_[glucose] = 6.34 eV), makes a weak complex (Scheme 1) with the aqua zinc-species, [Zn(H₂O)(OH)]⁺. Subsequently, this aqua species, [Zn(H₂O)(OH)]⁺ moves inside by the formation of a more stable complex with Phycocyanobilin2 (Scheme 2), which has a close/comparable hardness (η_{[Phycocyanobilin2]} = 2.37 eV). Exploiting the weak complexation at the algal surface, Zn(II) in real samples may be quantitatively retrieved (Scheme 1) with the help of a selective eluent. On the other hand, the more stable complexing ability in vivo makes this an efficient removal strategy for zinc (Scheme 2) in effluent.

Scheme 1

Scheme 2

Turning to the application of cyanobacterium as biosorbent, zinc has been removed from aqueous solution using typical microalgae.^28–30 However, the selectivity was not been properly investigated in terms of the effect of the matrix and, more importantly, the mechanistic path has not been investigated. Our present study advocates a selective, rapid, ecofriendly and cost-effective method for the preconcentration, separation, recovery and removal of zinc from aqueous solution of a complex nature (i.e., comprised of coexisting ions in concentration ranges similar to their natural abundance) at near neutral pH (6.5–6.8) by P. luridum growing on natural gravels in nutrient enriched raw water media. More importantly, global hardness (η) is a defined quantum mechanical descriptor and is the cardinal index of chemical reactivity, as well as the stability of atoms and ions.³¹ A standard Density Functional Theory (DFT) calculation has thus been performed, not only to analyze the structure of the extractor site and the extractor–Zn(II) complex, but also to rationalize the sorption pathway in terms of hardness.

2. Experimental

2.1. Apparatus and reagents

pH measurements were carried out with a digital Elico L1-120 pH meter combined with a glass electrode. A temperature-controlled water-shaker-bath (Remi Instruments, Mumbai, India) was used for the batch adsorption study. Standardization of the Fourier Transform Infrared (FTIR) Shimadzu spectrophotometer (Model no. FTIR-8400S) was achieved using a standard KBr disc. The dried algae in its Zn(II)-loaded and unloaded forms were ground in a pestle and mortar and FTIR spectra of the algae samples were recorded in the range 4500–500 cm⁻¹ using sample : KBr pellets in a weight ratio 1 : 10. The amount of chlorophyll a was determined using a Shimadzu UV-visible spectrophotometer (Model no. UV-1800) at standard scanning settings of 630 and 664 nm using quartz cuvettes. The amount of zinc was estimated by atomic absorption spectrophotometer (AAS: Model no. AA 6300) with the following measurement conditions: wavelength: 217 nm, L233 Lamp: 10 mA, slit width: 0.7 nm, flame type: air–C₂H₂, flow-rate: 2.2 L min⁻¹, support gas: 15 L min⁻¹, Burner H: 7 mm. A thermostat was used to carry out the extraction at the controlled temperature. Column experiments were performed in a fixed bed reactor (height 28 cm, diameter 1.6 cm). 90% acetone was made using a saturated solution of magnesium carbonate hydroxide to remove any acid present. Different salt solutions were prepared from ZnSO₄, K₂SO₄, NaCl, Fe₂(SO₄)₃, Na₂SO₄, NaH₂PO₄ and NaF using raw water. Metal ions were estimated spectrophotometrically. Column experiments were run for a period of 2 months. All of the chemicals and solvents used in this work, unless otherwise stated, were of analytical grade (BDH, Mumbai, India/E Merck, Mumbai, India).

2.2. Identification of algae

The specific strain of microalgae was grown on agar plates in nutrient enriched BG 11 (+) culture medium at room temperature and high light intensity 25 mW cm⁻² from daylight fluorescent tube for 12 h a day, utilizing a standard procedure.³² P. luridum [Fig. 1(i a)] was identified²¹ within three days of its collection without fixation by comparing various standard monographs (Colony a mat, upper part deeply pigmented purple, or deep blue green, inner part grey-blue-green. Cells 1.7–2 μm wide, 1.8–4.7 μm long, quadrate or longer than wide; cross walls slightly narrowed, without adjacent granules. Sheath thin, soft, diffluent; end cell rounded, calyptra absent)^33–37 with our microscopic observation using a Olympus BX41 epifluorescence trinocular microscope fitted with digital camera, Nikon Coolpix 4500 at a magnification of 45 × 10. The growth of the algae gradually increases and it approaches a limiting value (2.33 g) after 60 days.

Fig. 1 Micrographs of P. luridum, (i a) pure algae, (i b) Zn(II) (>90 μg mL⁻¹) containing algae at 12 days and (i c) Zn(II) (>90 μg mL⁻¹) containing algae at 24 days; (iia) AFM topography of pure algae, and (iib) and (iic) AFM topography and its 3-D view of the algae contaminated with Zn(II) at three weeks.

2.3. Effect of Zn(II) on the morphological change of the microalgae

Algal suspensions were placed in a set of cuvettes containing Zn(II) solutions (5 mL) of a range of concentrations (20–200 mg L⁻¹). Micrographs of P. luridum (both the pure and algal cells under stressed conditions) at different time intervals (1–21 days) were recorded on an Olympus BX41 epifluorescence trinocular microscope fitted with a digital camera (Nikon Coolpix 4500 at a magnification of 45 × 10) to observe any morphological changes (Fig. 1(i a–i c)). Chlorophyll a of the algal cells was found to be affected from the 2^nd day at a concentration of [Zn(II)] ≥ 40 mg L⁻¹. This encouraged us to carry out a systematic investigation of the quantitative effect of Zn(II) on chlorophyll a content.

2.4. Systematic studies on the effect of Zn(II) on chlorophyll a content

A 5 mL culture sample containing Zn(II) of concentration 40–200 mg L⁻¹ was taken after 2–21 days. The algal cells were centrifuged at 4000 rpm for 5 min. The supernatant was removed and the algae cells were then re-suspended in 2.5 mL of distilled water to remove any salts that might have been retained and centrifuged again. This washing process was repeated thrice. The air dried pigments (0.05 g), after grinding in a pestle and mortar, were extracted in 2 mL 90% acetone. The suspensions containing ground cells were centrifuged again at 4000 rpm for 5 minutes. 0.5 mL of pigment extract was diluted with assay solvent (90% acetone) to make the volume up to 10 mL and the absorbance was recorded on a Shimadzu UV-visible spectrophotometer (Model no. UV-1800) at standard scanning settings of 630 and 664 nm using quartz cuvettes. The amount of chlorophyll a (as mg g⁻¹) was estimated (Table 1) using the following Jeffrey and Humphrey equation.³⁸A_xxx is the absorbance at xxx nm, after eliminating the sample absorbance at 750 nm to correct for turbidity and contaminating colored compounds,³⁸ against a blank of the solvent used.

Table 1 Effect of different concentrations of Zn(II) on the chlorophyll a level of microalgae [sample volume: 5 mL]

Zn(II) (mg L^−1)	Chlorophyll a (mg g^−1)	Reduction (%) at the 2^nd day^a
a Average of three determinations; values in parenthesis indicate the reduction (%) after three weeks.
40	82	—
80	80	2.44 (18)
100	78	4.88 (24)
120	72	12.19 (99)
150	61	25.61 (99)
170	49	40.24 (100)
200	20	75.61 (100)

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2.5. Systematic studies on the sorption of Zn(II)

Algal cells were found to be little affected (only 4–5% reduction in chlorophyll a) (Table 1) by Zn(II) on the 2^nd day up to concentrations of 20–60 mg L⁻¹. Systematic investigations were therefore performed (both batch and column method) on the sorption (at required time interval to attain the equilibrium) of Zn(II) at different initial concentrations (20–60 mg L⁻¹) over a pH range of 6.5–7.5. Here, Zn(II) was just adsorbed on the algal surface as a weak complex as per Scheme 1 at shorter time intervals.

2.5.1 Batch method. Batch equilibrium experiments have been carried out to find the optimum pH and contact time for quantitative sorption of Zn(II) on the algal surface. The flasks (250 mL) were shaken at a constant rate (150 rpm), allowing sufficient time for adsorption equilibrium. It was assumed that the shaking speed used allows all the surface area to come into contact with analyte over the period of the experiments. The study was performed at room temperature to represent natural conditions.
2.5.1.1 Adsorption isotherm. Systematic studies of the contact time–adsorption relationship (algae: 0.5 g; [Zn(II)]: 40 mg L⁻¹; sample volume: 100 mL) at room temperature show that sorption increases with contact time and reaches its limiting value at 8 minutes (Fig. 2a). Consequently, in order to calculate sorption isotherms,²¹ a total of 0.5 g of algae was suspended with constant stirring until equilibrium (10 min) in 100 mL Zn(II) solution of different initial concentrations (six sets: 40–60 mg L⁻¹) at pH 6.5–7.5. The amount of adsorbate, zinc(II), adsorbed per unit mass (q_e) in mg g⁻¹ was calculated using the following equation:

q_e = (C_i − C_e)V/M (2)

where C_i and C_e are the initial and equilibrium concentrations (mg L⁻¹), M is the mass (g) of the adsorbent, q_e (mg g⁻¹) is the amount of zinc(II) adsorbed per unit mass of the adsorbent algae and V is the volume (L) of the solution. The data from this batch experiment are shown in (Table 2). The goodness-of-fit of the isotherm to the Langmuir (eqn (4) and (5)) and Freundlich (eqn (6)) equations was examined using the correlation coefficient, R², and the residual root mean square error (RMSE),²¹ defined by eqn (3)where q_e (average of three determinations) is the experimental value (batch experiment), q_e(t) is the estimate from the isotherms (Fig. 2b and c) for corresponding q_e and m is the number of observations in the experimental isotherm. The smaller RMSE value indicates the better curve fitting.

Non-linear regression of Langmuir isotherm:

Linear regression of Langmuir isotherm:Here, q_e is the concentration of zinc on the algal surface (mg g⁻¹), Q₀ is the monolayer saturation concentration of zinc on the algal surface (adsorption capacity: mg g⁻¹), b is the Langmuir constant related to the binding energy of Zn(II) to the algal surface (L mg⁻¹), and C_e is the concentration of Zn(II) at equilibrium (mg L⁻¹).

Linear regression of Freundlich (eqn (6)) isotherm:

Here, the adsorption constants K_F and 1/n were the indicators of adsorption capacity and adsorption intensity, respectively. K_F is an empirical parameter that is composed of three components, a binding constant, a term related to the number of adsorption sites, and solution composition. Solution composition is constant for any given water sample. In practice, therefore, only the binding constant and the number of surface sites are true contributors to K_F. Binding energy decreases as the number of sites are filled and so is a constant only at low sorbent concentrations. The number of surface sites will depend on the cell surface composition. The parameter n is a measure of the affinity between the sorbent and the surface. Sorption ability increases with increase in n value.³⁹ Freundlich 1/n could be estimated based on the structure of the adsorbent cell surface and the density of carboxyl groups on that surface.⁴⁰ C_e is the equilibrium concentration (mg L⁻¹) of zinc(II) and q_e is the amount of Zn(II) adsorbed per unit mass of the adsorbent (mg g⁻¹). The square of standard deviations, S_R² (for six determinations) for both these regressions was taken to determine the F-value (eqn (7)).

Fig. 2 (a) Plot of contact time vs. q_e,(b) plot of C_e (mg L⁻¹) vs. C_e/q_e (g L⁻¹), (c) plot of log C_e vs. log q_e and (d) plot of volume of effluent (mL) vs. C/C₀ (g L⁻¹).

Table 2 Data of batch experiment, parameters of Langmuir and Freundlich isotherm and RMSE for the Zn(II) (C_e mg L⁻¹) sorption experiment at room temperature

Langmuir parameters; R^2 = 0.992						Freundlich parameters; R^2 = 0.980
Ce	qe (mg g^−1)	Q0 (mg g^−1)	b (L mg^−1)	qe(t)	RMSE		KF	qe(t)	RMSE
0.33	0.82	5.74 ± 0.04 (87.7 ± 0.04 μM g^−1)	0.515 ± 0.04	0.8343	0.0336	0.643	1.817	0.8902	0.1699
0.64	1.45			1.4237				1.3632
1.25	2.28			2.2493				2.0972
1.84	2.76			2.7945				2.6872
2.53	3.22			3.2497				3.3014
3.20	3.60			3.5745				3.8402

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2.5.2 Column method. Column chromatography is an effective method for sample clean-up that allows selective separation and preconcentration of an analyte.^12,13 The adsorption studies (Section 2.5.1) encouraged us to investigate the column chromatographic conditions required for the selective extraction of Zn(II) from a sample of large volume containing natural interferences and its selective elution using athe minimum possible volume of eluent, in order to retrieve enriched Zn(II) without any sort of algal damage.
2.5.2.1 Preparation of sorption bed. The adsorbent columns (0.8 × 28 mL) were packed with naturally occurring sands and gravels collected from the riverside. The microalgae, P. luridum, was added in the core of the column and nutrient-enriched raw water at neutral pH was continuously passed through the column. The growth of algae in the column could be clearly identified by the gradual change of color (green) of the adsorbent bed.
2.5.2.2 Effect of temperature on extraction. The extraction equilibrium constant (K_ex) has been calculated at different temperatures using the following equation:⁴¹

K_ex = E_R/[–RCOO](S)[H⁺] (8)

where [–RCOO](S) denotes the concentration of exchanger participating in the ion-exchange process and E_R is the ratio of extracted metal ions to unextracted metal ions. A plot of log K_ex vs. 1000/T gives a linear relationship (y = −0.4169X + 0.002; R² = 0.9796).

The effect of temperature on extraction of Zn(II) has also been investigated for the determination⁴¹ of different thermodynamic parameters at pH 6.5 using the standard van’t Hoff equation. The enthalpy change (ΔH) was evaluated from the plot of log K_ex vs. 1000/T. The free energy change (ΔG) and entropy change (ΔS) at room temperature (298 K) were also calculated.

2.5.2.3 Effect of pH on sorption. pH seems to be the most important parameter in the biosorptive process [i.e., biosorption = f(solution pH)]: pH affects the solution chemistry of the metals⁶ and the activity of the functional groups in the biomass as well. As a result of this the interaction of metallic ions with the active sites of the biomass is a function of solution pH.^42–44 As previously mentioned, up to a concentration of 40 mg L⁻¹, Zn(II) shows little or no impact on the amount of chlorophyll a (Table 1). Zn(II) up to this concentration in raw water was therefore passed through the column containing microalgae to investigate the pH–sorption relationship. Systematic studies on sorption by the algal cells at a pH range 2.5–7.5 from a solution of zinc(II) (20 mg L⁻¹) showed that Zn(II) could be quantitatively extracted at neutral pH range and at a flow rate of 2 mL min⁻¹ (Fig. S1†). After extraction, Zn(II) was stripped with 5 mL 0.005 M HNO₃ without any of damage to the algal cells and the amount was determined by atomic absorption spectrophotometer (AAS).
2.5.2.4 Break-through capacity (BTC) and preconcentration factor. The pH of the sorption bed (1 g algae) and the Zn(II) solution (20 mg L⁻¹) were adjusted to pH 6.5–7.5 with 0.1 M acetate buffer. The influent [Zn(II) solution (20 mg L⁻¹)] was passed through the column containing the biosorbent until saturation at a flow rate of 2.0 mL min⁻¹ (40–45 drops per min). The effluent (i.e. the column outlet solution) was collected for each respective influent and the amount of Zn(II) was estimated. The relationship between volume of effluent (mL) vs. C/C₀ (where, C and C₀ are the concentrations of effluent and influent, respectively) gives the maximum uptake capacity (i.e., the break-through point) of Zn(II) at room temperature and under other conditions of experimental set up (Fig. 2d). After attaining the break-through point, Zn(II) was retrieved by an eluent of small volume (V_eluent) to obtain the analyte in its enriched state. The preconcentration factor was determined to assesses the applicability of the extractor.
2.5.2.5 Effect of volume and flow rate of the influent [Zn(II) solution, containing common cations/anions as interference] on sorption. Zn(II) in a pure sample was found to be extracted on the algal surface and reached equilibrium quickly. Considering its analytical application in real samples, the extractability of Zn(II) (at shorter intervals of 10–15 minutes) was therefore systematically investigated under different flow rates and analyte volumes in the presence of some commonly occurring ions (Na⁺, K⁺, Cl⁻, SO₄²⁻, ClO₄⁻, NO₃⁻) in their natural contamination concentration (50–300 mg L⁻¹) ranges (Table 3).

Table 3 Effect of interfering anions on extraction of Zn(II) [column = 0.8 × 8 cm.; flow rate = 2.0 mL⁻¹ min⁻¹; Zn(II) taken = 40.4 μg; pH = 6.5]

	Retention (%)^a
Interfering ion conc. (mg L^−1)	50	100	150	200	250	300
a Average of five determinations.
Na^+	98.6	98.3	98.0	97.4	97.1	96.6
K^+	99.0	98.5	98.2	97.6	97.0	96.4
Cl^−	98.5	98.1	97.7	97.3	96.6	93.2
SO4^2−	97.6	97.3	97.1	96.9	96.1	92.3
ClO4^−	98.7	97.5	97.3	97.1	96.2	88.0
NO3^−	99.3	98.8	97.5	96.4	95.6	92.4
CH3COO^−	99.7	98.6	98.2	97.5	97.0	95.4

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2.5.2.6 Removal of Zn(II) from real samples. Interference of common contaminants (Na⁺, K⁺, Cl⁻, SO₄²⁻, ClO₄⁻, NO₃⁻) in their natural range of concentrations (50–300 mg L⁻¹) on the biosorption process was found to have little effect on the removal of Zn(II). The bio-removal of Zn(II) in some real water samples (pond water, thermal water and well water containing these possible interferences) was therefore investigated to judge the applicability of the method.

2.6. Computational methods

Density functional electronic structure theory has been used as an adjunct to experimental work to obtain insight into the selectivity of an exchange material towards a specific metal centre.⁴³ Single crystal XRD analysis was beyond our scope, as the ion-exchange material was an algal mass. In order to obtain the three dimensional structure and its hard–soft character, density functional investigations were thus performed. Standard density functional theory (DFT)⁴⁴ calculations for all the structures were carried out with Gaussian 09 package.⁴⁵ The geometries of the Phycocyanobilin2 moiety were fully optimized using the RSVWN^46,47 method and 3-21G^48–50 basis set, while the 6-31g (d) basis set has been utilized for the optimization of Zn-species. All the optimized structures have been characterized by frequency analysis as energy minima by the absence of imaginary frequencies. In addition, neutral bond order (NBO)^51–53 calculations of the optimized structures were performed to find the molecular orbitals. The energies of the optimized structures were calculated after the ZPE (zero point energy) and thermal corrections.

3. Results and discussion

3.1 Effect of bioaccumulated Zn(II) on chlorophyll a content

Systematic studies (Table 1) indicate that chlorophyll a content gradually decreases with increase in time and Zn(II) concentration. Up to 60 mg L⁻¹, there was no appreciable change in chlorophyll a content, but at a higher concentration of zinc(II) (>90 mg L⁻¹) the reduction was obvious (Fig. 1(i b)), and beyond three weeks the chlorophyll a content practically reached zero (Fig. 1(i c)). This indicates that living cells may not only have surface sorption, but also slower and metabolism dependent active uptake of zinc. Interestingly, the cell wall remains almost unperturbed. In normal cyanobacterial cells, the light-harvesting antenna Phycobilisome (PBSs) connect with the photosystems and transfer light energy to chlorophyll a, the photosynthetic light reaction center.^54,55 The reduction in chlorophyll a content may be due to the breakdown of chlorophyll a under stressed conditions, or from inhibition of chlorophyll a biosynthesis. The inhibition of chlorophyll a biosynthesis is well explained by the proposed reaction path (Scheme 2). The AFM images [Fig. 1(iia–iic)] of pure and contaminated algae confirm the loss of uniformity inside the cell under stressed condition.

3.2 Rationalization of the biosorption process

3.2.1 Characterization of the biosorbent. Exchange capacity is strongly influenced by the type and number of functional groups present on the surface of the adsorbent.⁵⁶ P. luridum is a sulfated heteropolysaccharide to which fatty acids and proteins are bound. The polysaccharide backbone is composed of uronic acids, rhamnose, mannose, and galactose.⁵⁷ The FTIR spectrum of the algae showed several intense peaks at around 3497.06–3580, 1572–2376.4 and 1028.8–1101.2 cm⁻¹ (Table 4; Fig. 3). The peak at 3497.1–3580 cm⁻¹ is attributed to –NH and –OH,^56,58,59 and –CH stretching vibrations may be attributed^56,59 to the absorption peak at 2928–3203.8 cm⁻¹. The absorption peaks at 1666.7 and 2376.4 cm⁻¹ could be assigned to –C=O groups.^56,58 Moreover, the presence of –C–O, –C–C and –C–OH may be confirmed by the absorption peak at 1028.8–1101.2 cm⁻¹.^56,60 The absorption peak at 831.55–900 cm⁻¹ could be assigned to –P–O, –S–O and aromatic –CH stretching vibrations.^56,60 After adsorption, the electronic structure of the adsorbent molecule is disturbed. Consequently, FTIR spectra indicate that nearly all IR bands were shifted after adsorption of Zn(II). However, the major shift was observed in –C=O group (2376.4 → 2348.4 i.e., 28 units and 1666.7 → 1628: i.e., 38 units). This clearly indicates the involvement of –C=O in the sorption process. The shifting of the peak positions in the Zn(II)-loaded algae at 1666.7 and 2376.4 cm⁻¹, which are assigned to the –C=O group, suggests⁶¹ the extraction of Zn(II) (Fig. 3(ii)). The theoretical FTIR (Fig. 3(i)) spectra of the protein fragment loaded with Zn(II) show peaks assigned to –NH stretching at 3560 cm⁻¹; –OH group (of HOH bonded to Zn(II) centre), not participating in hydrogen bonding, stretching at 3523.7 cm⁻¹; –OH group, participating in hydrogen bonding [bonded to Zn(II) centre] stretching at 2788.6 cm⁻¹; –CH stretching at 2946.3–3254.3 cm⁻¹; –COO⁻ group (complexed with Zn(II)) stretching at 1666.4 cm⁻¹ and bending at 1623.2 cm⁻¹; aromatic ring stretching at 1499.3–1591.3 cm⁻¹; –CH bending at 1198.3–1489.7 cm⁻¹, and –CH=CH– (alkene) stretching at 1706.6 cm⁻¹. This agrees with the experimental spectral data (Table 4).

Table 4 Assignment of FTIR peaks [*values in the parenthesis correspond to the FTIR spectra of the DFT optimized structure of the protein fragment in the absence of Zn(II)]

Experimental FTIR		Theoretical FTIR		Peak assignment
Peak positions (cm^−1)	Nature of the peak (intensity)	Peak positions (cm^−1)	Nature of the peak (intensity)
1028.8–1101.2	Broad, medium intensity	1198.34–1489.71 (1005–1462)*	Broad, medium intensity	–C–O, –C–C and –C–OH bending vibrations^56,60
1573.97–2374.45	Sharp, strong intensity	1666.37 (1748.50)*	Sharp, strong intensity	–C=O stretching vibrations^56,58
2928.04–3203.87	Sharp, strong intensity	2946.29–3254.33 (2939.57–3194.30)*	Sharp, strong intensity	–CH stretching vibrations^56,59
3497.06–3580.00	Sharp, strong intensity	3560 (3589.95)*and 2788.56–3523.66 (3167.30–3211.47)*	Sharp, strong intensity	–NH2 and –OH stretching vibrations^56,58,59

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Fig. 3 FTIR spectra of DFT optimized structure of (ia) protein fragment and (ib) protein fragment loaded with Zn(II), and (ii) experimental FTIR spectra of (a) free algae and (b) loaded with Zn(II).

3.2.2 Probable metal–ligand complexation. The cationic species, [Zn(H₂O)₅(OH)]⁺ and [Zn(H₂O)₆]²⁺, are present in equilibrium⁶² at neutral pH. A linear relationship (y = 1.109X + 1.6926; R² = 0.9889) with a slope of 1.109 between log K_d and log C_[algae] is obtained at pH 6.5, at fixed concentrations of acetate buffer solution and Zn(II) solution. The probable composition of the extracted species is thus 1 : 1 (metal : extractant).

3.2.3 Rationalization of 1 : 1 (metal : extractant) complexation in terms of DFT. The algae contain Phycocyanobilin2 as a unit protein of Phycobilisome (PBSs),⁶³ which contains two carboxylic acid groups (Fig. S2a†), both of which can participate in ion-exchange process independently. However, the 1 : 1 complexation (Section 3.2.2) requires the simultaneous participation of both these carboxylic acid groups for metal trapping. This indicates that Zn(II) has been trapped in the hydrogen-bonded dimeric core (Fig. S2b†). To elucidate the hardness behavior, the structure of the protein fragment (Phycocyanobilin2) was optimized by standard DFT (−26 692.32 eV mol⁻¹) calculations (Fig. S3a†) and the global hardness was calculated^23,64 (η = 2.37 eV) from the HOMO (−5.784 eV)–LUMO (−3.40879 eV) gap. The optimized structure suggests a stable, metal-trapping, hydrogen-bonded dimeric core (Fig. S3b†). The structures of [Zn(H₂O)₅OH]⁺ and [Zn(H₂O)₆]²⁺ were optimized by DFT methods [Fig. S4a(i) and S4b(i)†]. The mono positive [Zn(H₂O)₅OH]⁺ (−60 442.7 eV) complex is a soft acid [η_{[Zn(OH)(H2O)]⁺} = 1.25 eV; HOMO: Fig. S4a(ii)† and LUMO: Fig. S4a(iii)†] and it possesses comparable η values to [Zn(H₂O)₆]²⁺ ion (−60 468.8 eV) itself [η_{[Zn(H2O)6]²⁺} = 0.63 eV; HOMO: Fig. S4b(ii);† and LUMO: Fig. S4b(iii)†].⁶⁴ Mulliken atomic charges on the carboxylate oxygen (−0.484631, −0.509800, −0.488212, −0.508850) allow electrophilic attack by [Zn(H₂O)₅OH]⁺, the cationic species of zinc. Here, the mono positive hydroxo complex, [Zn(H₂O)₅OH]⁺, having comparable η values, is trapped inside the co-ordination sphere of a number of hard donor O-sites present in the hydrogen-bonded exchange core (inherent η = 1.25 eV) (Fig. 4). The DFT optimized structure (−78 887.8 eV mol⁻¹) of this zinc complex strongly suggests tetrahedral geometry, stabilized by −52 195.48 eV mol⁻¹ through the formation of two strong intramolecular hydrogen bonds (–OH⋯O = 163.54 pm; HOH⋯O = 129.71 pm). The strong absorption band at 3300 cm⁻¹ (for unloaded algae) suffers a shift at 3200–3500 cm⁻¹ as a broad band⁶ in the loaded FTIR spectrum (Fig. 3), thereby confirming the formation of two intramolecular H-bonds in the extracted species (Fig. 4).

Fig. 4 DFT optimized structure of tetrahedrally co-ordinated Zn(II) in Phycocyanobilin2.

Initially [Zn(H₂O)(OH)]⁺ (η_{[Zn(OH)(H2O)]⁺} = 1.25 eV) is adsorbed at the surface comprised of polysaccharides (η_[glucose] = 6.34 eV) of algae and forms a weak complex (fast: equilibration achieved at shorter time interval) (Scheme 1). Subsequently, it moves inside through the formation of a much more stable complex with Phycocyanobilin2 because of their similar hardness (η_{[Phycocyanobilin]} = 2.37 eV) (slow/metabolism dependent active path) (Scheme 2). Bearing this in mind, it has been suggested that [Zn(H₂O)₅(OH)]⁺, having suitable size, charge, and comparable hardness value (η_{[Zn(OH)(H2O)]⁺} = 1.25 eV) moves to the exchange site as per the following proposed pathway:

3.3 Adsorption isotherm

Langmuir and Freundlich isotherm models were fitted to the experimental data to investigate sorption behavior of the biosorbent at pH 6.5. An experimental linear plot (y = 0.1741X + 0.3381; R² = 0.9991; SD = 0.0091) of C_e/q_e versus C_e with a very high correlation coefficient close to unity for the adsorbent (Fig. 2b) suggests the validity of the Langmuir adsorption (chemisorptions) isotherm (eqn (5)). From the slope and intercept of the linear plot, Q₀ (maximum sorption g⁻¹) and b (Langmuir constant, considered as the energy parameter of adsorption) were found to be 5.74 ± 0.04 (mg g⁻¹) and 0.515 ± 0.04 (L mg⁻¹), respectively. The parameters of the Langmuir isotherm and Freundlich isotherm are given in Table 2. The lower RMSE value (Table 2) suggests improved goodness-of-fit for the Langmuir regression (RMSE = 0.0336) over the Freundlich (RMSE = 0.1698; y = 0.64349x + 0.2593; R² = 0.9926; SD = 0.033; Fig. 2c)⁶⁵ and disproves the Freundlich isotherm (eqn (6)). The calculated F value (13.6; eqn (7)) is significant with respect to the F_crit (5, 5) value (5.05 at α = 0.05). This clearly indicates that these two methodologies differ significantly (correlation ≪ 5%) in terms of correlation parameters, statistically. The dimensionless separation factor,²¹ R_L, was calculated from the Langmuir constant (b) by applying the following equation:

R_L = (1 + bC_i)⁻¹ (11)

where C_i (10–80 mg L⁻¹) is the initial solute concentration. Using an initial solute concentration range of 10–80 mg L⁻¹, the values of R_L (0.16–0.02) were calculated. The R_L values lie between 0 and 1, indicating a favorable exchange process.⁶⁶ It therefore becomes more and more difficult to adsorb the additional adsorbates using the Freundlich isotherm.

3.4 Effect of temperature, pH, volume and flow rate of the influent [Zn(II) solution, containing common cations/anions as interference] on sorption

Systematic studies on the effect of temperature on the extraction of Zn(II) (Section 2.5.2.3) gives the linear relationship (y = −0.4169X + 0.002; R² = 0.9796) for log K_ex vs. 1000/T and this yields different thermodynamic parameters. The positive ΔH (7.98 kJ mol⁻¹) and smaller ΔS (0.1916 kJ mol⁻¹) values suggest the endothermic nature of the extraction process.⁴¹ The higher negative value of ΔG (−49.16 kJ mol⁻¹) suggests the spontaneity and tendency towards chemisorption at equilibrium,⁴¹ and is in agreement with the Langmuir isotherm. Turning to the effect of pH on the sorption of Zn(II) on algae, sorption experiments in solutions of pH range 2.5–7.5 show that metal uptake increases with gradual increase in pH (Fig. S1†). This indicates that the sorption process is a function of [H⁺]. The exchange sites contain proton releasing groups and these lose more and more H⁺ with increased sorption of Zn(II). At low solution pH, difficult deprotonation of exchange sites and dissolution of metal ions results in poor sorption. Quantitative sorption was ensured at neutral pH range. Systematic studies on the effect of influent volume on sorption of Zn(II) (20 mg L⁻¹) indicate that sample volume up to 0.9 L does not influence the preconcentration factor. Zn(II) is adsorbed on the adsorbent from a large volume sample (250–1145 mL) of low concentration (20 mg L⁻¹) and is collected in a more concentrated form (286.95–352.79 mg L⁻¹) using a small volume (5 mL) of a selective eluent (0.01 M HNO₃) for its desorption. Complete retention of Zn(II) in the column was found up to a flow rate of 3.5 mL min⁻¹. Common ions like Na⁺, K⁺, Cl⁻, SO₄²⁻, ClO₄⁻, NO₃⁻ up to 250 mg L⁻¹ and CH₃COO⁻ up to 300 mg L⁻¹ (Table 3) did not interfere with the extraction.

3.5 Column BTC and preconcentration factor

BTC is an important column parameter in chromatography. It indicates the maximum uptake capacity of an exchange material and is expressed as mg g⁻¹ or μM g⁻¹. During our investigation on BTC of Zn(II) with respect to microalgae as exchange material, it was found that leakage of Zn(II) (20 mg L⁻¹) started above 345 mL (6.9 mg g⁻¹; i.e., BTC: 105.5 μM g⁻¹) of metal ion solution (Fig. 2d). The observed experimental BTC value was in good agreement with the Langmuir Q₀ value (5.74 ± 0.04 (mg g⁻¹), the monolayer saturation capacity. After saturation through extraction, Zn(II) was eluted from the column with 5 mL 0.005 M HNO₃ (an acid concentration where algal cells were found to be unaffected). During this continuous extraction, Zn(II) has been accumulated gradually in the column from its influent of lower concentration (20 mg L⁻¹) and after elution the effluent (5 mL) was found to be rich in Zn(II) with higher concentrations (1380 mg L⁻¹). This method therefore preconcentrates Zn(II) in the effluent with a preconcentration factor of 69 (v/v) on milligram levels.

3.6 Selection of stripping agents to retrieve Zn(II)

The elution process (back extraction) follows the reverse of the surface reaction (eqn (10); Scheme 3). It goes without saying that Zn(II) will be desorbed with H⁺. After sorption of Zn(II) at the surface of algal cells as a weak complex, it was stripped with demineralized water and various acids of different concentrations in order to select specific stripping agents. Systematic studies on stripping behavior involved quantitative elution of Zn(II) with HNO₃ and HCl of concentration ≥0.005 M and with CH₃COOH of concentration ≥0.01 M. During these experiments, it was found that 0.005 M HNO₃ gave the best stripping (least required volume (5 mL), high column efficiency in terms of plate numbers, N = 361 (ref. 12), and, moreover, that the cells remained unaffected), hence it was used as stripping agent in further experiments. Acetic acid dissociates weakly in aqueous solution and thus requires a relatively higher concentration compared to strong inorganic acids, like HCl or HNO₃, to achieve quantitative elution of Zn(II). Moreover, low levels of the mineral acids elute Zn(II) from the exchanger bed through the formation of nitro,⁶² [Zn(NO₃)]⁺ and corresponding chloro cations. After stripping, the column was washed thoroughly with water to prevent any damage to algal cells.

Scheme 3 Extraction and elution of Zn(II) on microalgae surface.

3.7 Proposed equation of elution profile

The experimental elution profile shows a maximum at 3 minutes and thisagrees well with the theoretical profile (Fig. 5). Plot of log f(N_i) vs. log t_i and log[log f(N_i)] vs. log t_i gave two linear segments (y = 3.477 + 0.245; R² = 0.987 and y = −3.663 + 2.547; R² = 0.929). The parameters m, n, and λ of the theoretical equation (eq. (12)) have been determined from the slope and intercepts of these linear segments as per equations (eqn (13) and (14)):

f(N_i) = (t_i)^me^−λ(t_i)n (12)

where t_i is the interval of time and f(N_i) is the amount eluted at an interval of time t_i.

log f(N_i) = m log t_i, as t → 0 (short time limit) (13)

log[log f(N_i)] = −log λ − n log t_i, as t → ∞ (long time limit) (14)

Fig. 5 Plot of recovery (%) vs. time (minutes) for (a) experimental curve and (b) theoretical curve.

The f(N_i) values were obtained from the experimental elution curve, considering f(N_i) = (t_i)^m as t → 0 and f(N_i) = e^−λ(t_i)m as t → ∞

Initially, the first term of eqn (12) increases rapidly with time and, after a certain time interval, the second term dominates with its rapidly decreasing tendency. The parameter, m, is related to sorption (metal character) and the parameters λ and n are very much related to desorption process (H⁺ character).

3.8 Optimization of preconcentration factor and desorption constant

Preconcentration factor (PF) is an important analytical parameter for sample clean-up. It depends on the recovery (%) and analyte volume (V_i) as follows These two parameters have an inverse relationship on PF. This necessitates its optimization with respect to these two variables. Systematic studies on the effect of volume on recovery of Zn(II) from feed solutions of large sample size (250–1145 mL) show that the recovery (%) decreases with an increase in volume of the influent. The maximum PF is 68.5 ± 0.5. It remains the same up to a sample volume of 945 mL, which suggests its analytical applicability. A plot of V_s (volume of influent sample, mL) vs. PF gives a linear section (y = −0.003X + 70.39; R² = 0.989) (Fig. 6) and the slope of this section yields the desorption constant K_desorption = 3 × 10⁻³.^12,13 The parameter λ (= 0.002–0.003) of the proposed equation (eqn (12)) for elution profile is in good agreement with this experimental desorption constant [K_desorption = 3 × 10⁻³].

Fig. 6 Plot of V_svs. PF.

3.9 Effectiveness and utility of the proposed method

The effectiveness of the proposed method was judged by separating Zn(II) from some water (raw, thermal and tap water) samples by applying the proposed method (Table 6). After recovery from real samples, Zn(II) was determined by AAS. A high degree of preconcentration (300 mL to 5 mL) (>60 fold v/v; PF = 46.8 w/w), with subsequent removal and recovery (>78%) of Zn(II), and low standard deviation (<0.4) for real samples were obtained (Table 5).

Table 5 Removal of Zn(II) in water samples [sample volume = 300 mL]

Sample	Water
	Metal ion	Added (μg)	Found^a (μg)	Relative error (%)
a Average of five determinations.
Raw water	Zn(II)	—	1.7	—
		40.4	40.1	4.75
Thermal water	Zn(II)	—	0.4	—
		40.4	41.4	1.47
Well water	Zn(II)	—	1.4	—
		40.4	43.5	4.07

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3.10 Analytical performance in comparison to other matrices

The sorption process on the algal surface follows the Langmuir adsorption isotherm with a high adsorption coefficient Q₀ (5.74 ± 0.04 mg g⁻¹) in water. Q₀ is the amount of zinc on the algal surface for the monolayer saturation and it represents the adsorption capacity (i.e., BTC, mg g⁻¹) of the microalgae. The value of this adsorption capacity (mg g⁻¹) is comparable to that of other matrices (Table 6).

Table 6 Comparison of adsorption capacity (Q₀: mg g⁻¹) with other adsorbents

Adsorbent material	Langmuir Q0 (adsorption capacity: mg g^−1)	References
P. luridum containing G.rupestris, and C. infusionum (99 : 0.08 : 0.02)	5.74 ± 0.04	This work
Azadirachta indica bark	33.49	67
Hazelnut shells cells	1.78	68
Algae	26.12	69
Fungi	9.81	70
Immobilized dead algal cells	9.38	71

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4. Conclusions

The algae (P. luridum, G. rupestris, and C. infusionum) grown on naturally occurring gravels shows significant adsorption of [Zn(H₂O)(OH)]⁺, a species of Zn(II) present in real samples. The developed method yields a high degree of preconcentration (>60 fold v/v; 46.8 w/w) with subsequent removal amd recovery (>78%) of Zn(II) with low standard deviation (<0.4) for real samples. Initially, Zn(II) is adsorbed at the surface, which is built up of polysaccharides of the algae, as a weak complex and subsequently it moves inside the H-bonded core of Phycocyanobilin2 by forming a more stable 1 : 1 complex through soft–soft interactions. The tetrahedral Zn–Phycocyanobilin2 complex, stabilized by two strong intramolecular H-bonds, is characterized by FTIR analysis and supported by reliable density functional calculation. Zn(II) has been quantitatively retrieved, exploiting the Zn(II)–glucose weak complexation at the algal surface. The algae are available in tropical countries like India and are also cheap. The filter bed works at neutral pH and room temperature. The filter bed needs no treatment or activation, because the algae on the bed take up their nutrients from the raw water itself and grow on the bed. The bed is thus self-maintained. The Gaussian nature of the elution profile suggests reversibility of sorption equilibrium.

Acknowledgements

One of the authors (Monalisha Mondal) gratefully acknowledges the facilities provided by the department of chemistry, Visvs-Bharati, Santiniketan.

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Footnote

† Electronic supplementary information (ESI) available. See DOI: 10.1039/c5ra01867f

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