An unique solvent assisted ‘green’ hydrotropic precipitation and response surface optimization for isolation of the dietary micronutrient β-sitosterol-D-glucopyranoside from Desmostachya bipinnata

Abstract

β-sitosterol-D-glucopyranoside, a phytosterol glycoside is well known as dietary micronutrient and food supplement. The present work focuses on the novel investigation of solvent assisted ‘green’ hydrotropic precipitation of this molecule from D. bipinnata, where the Box–Behnken optimized separation process improved the yield by 80.4% (purity: 99.6%) than the conventional extraction.

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Natural products find their extensive use in food stuffs because they enjoy the preference of the consuming population due to their plant origin and relative safety. Plant sterols are obligatory molecules in food stuffs, and β-sitosterol-D-glucopyranoside (BSG) forms an important ingredient of these phytosterols. BSG (Fig. 1) is found in fruits and vegetables, and the dietary intake of this compound is recommended because it acts like an essential micronutrient; moreover, it is a vital cell constituent.¹ It is also used along with β-sitosterol as a food supplement for older adults to enhance their immune function.² The commercially available Moducare®, Harzol® and Sitosterin® are food supplements that contain BSG as a vital ingredient.³ The dietary intake of BSG with other phytosterols has been evidently proved to improve immune system,⁴ in combating cancer and prostate abnormalities.¹ BSG is proved to be anti-microbial,⁵ antileukemic, antispasmodic, antitumour and hypoglycemic.⁶ They have been positively found to improve the health of HIV infected patients when taken as daily dietary supplement.⁷ Moreover, BSG has been proved to synergistically combat human pathogens when combined with other commercial antibiotics.⁵ It is proved that the oral absorption of BSG is not toxic to humans,⁸ and it has been evidenced that the daily oral supplementation of 60 mg β-sitosterol and 0.6 mg of its glucopyranoside (BSG) enhances T-cell proliferative response after 4 weeks.⁹ BSG combinations (Harzol™) have been used in Germany to treat benign prostatic hypertrophy (BPH), and it also has been proved to be adapted by humans to their dietary availability and incorporated them in their own metabolic needs over the course of evolution.¹⁰ Like Vitamin C, the lower availability of BSG and other sterols have to be dealt with supplements containing BSG and other sterols to counter the deficiency effects.¹¹

Fig. 1 β-sitosterol-D-glucopyranoside.

Because the oral absorption of BSG is low, it is imperative that to maintain a normal serum level of BSG in the humans having deficiency of BSG, enormous amount of fruits and vegetables need to be consumed, which becomes practically difficult. Therefore, dietary supplements containing BSG and sterols need to be administered, which necessitates the need for pure isolation of BSG from plants. However, the variety and abundance of other plant sterols in edible plant parts always results in meager yield of BSG through conventional extraction procedures. Therefore, non-conventional separation methods become necessary for rapid and better recovery of BSG. It was observed that the stem and roots of Desmostachya bipinnata (L.) Stapf. (Fam. Poaceae) contain significant amount of BSG. Therefore, a unique process that can provide rapid, pure and better yield of BSG has to be developed. The extraction of active components from plants has been a daunting task since decades because the process developed for the complete isolation of a molecule varies with respect to plant and target molecule. The conventional isolation of molecules from plant matrices involves solvent extraction and subsequent purification through column chromatography.¹² These techniques involve the handling of large volumes of harmful volatile solvents, which make the whole extraction process labour-intensive and time-consuming. Therefore, non-conventional isolation processes which are environmentally friendly and easy to operate are now being developed and established.

Hydrotropes are low molecular weight organic salts that have an interesting ability to solubilize water insoluble organic compounds into water. They achieve this feature by achieving a desirable concentration in aqueous solutions usually above their characteristic minimum hydrotrope concentration (MHC). Thus, at high concentrations of hydrotrope, solutes can be solubilized in water and could be later recovered as precipitates just by diluting the solution and decreasing the hydrotropic concentration below MHC. This provides an easy method to extract, enrich or concentrate compounds from plant matrices. The hydrotrope has an advantage of reusability because they are chemically inert during the extraction process.¹³ Initially developed in the 1950s, Response surface methodology (RSM) is now extensively applied to solve, model and enhance tedious optimization problems involving numerous influential factors.¹⁴ Box–Behnken design (BBD) is a well-known RSM method and effective design practice involving lower number of experimental runs and model fitting; thus, economizing the time and resources needed for experimental processes that are routinely used in many optimization studies.¹⁵ It is therefore widely applied for developing extraction processes of molecules from plants.¹⁶

The novel technique developed in the current study, specifically isolates the target molecule (BSG) with high purity from other impurities using a green process. The identification of influential factors and process parameters involved in hydrotropic extractions through RSM, which could aid in optimizing the extraction process, and to obtain the maximum recovery of target compounds, besides reducing the number of steps in the isolation of pure molecule, has also been attempted.

The initial solubility studies of BSG were performed in various concentrations of hydrotropic solutions of sodium p-toluenesulphonate (Na-PTS), Sodium cumene sulphonate (Na-CTS), and sodium salicylate (Na-Sal) (0.5–2.0 mol). The solubility experiments were carried out in a cylindrical glass vessel (50 mL) fitted with a six-bladed turbine impeller (i.d: 2 cm) with vigorous stirring for 5 h at 35 °C. The amount of BSG solubilized was analysed and plotted.† The stability of BSG at different temperatures was also evaluated.† Studies were performed with acetone, methanol, ethanol and acetonitrile for determining their efficiency in the precipitation of BSG from hydrotropic extract compared to water. The purity of the precipitated BSG was also analysed during each experiment.†

The authenticated† plant material (stem and roots) of D. bipinnata collected from river beds of River Cauvery in Thanjavur were suspended in a completely baffled cylindrical glass vessel (500 mL) fitted with six-bladed turbine impeller (i.d: 2 cm). The concentration of hydrotrope varied according to the optimization experiments. The suspension was vigorously agitated at 1000 rpm for 3 h. Samples were withdrawn at definite time intervals and analysed for the BSG content. At the end of the extraction, the clear solution containing the metabolites was filtered under vacuum. A slight yellow-coloured filtrate was obtained. The insoluble sticky residue was washed with 10 mL of hydrotropic solution, filtered and mixed with the filtrate. The filtrate was diluted with pure water to decrease the concentration of hydrotrope to the minimum hydrotropic concentration (MHC), which afforded the production of the precipitate. The precipitate was filtered, washed and analysed for the amount and purity of BSG using high performance thin layer chromatography (HPTLC).

For solvent assisted hydrotropic precipitation (SAHP), water was replaced with solvents to dilute the hydrotropic filtrate, which afforded the production of precipitates, which were later analysed for the amount and purity of BSG.

On the basis of the spectral data, Fig. S1 and S2,† the structure of the compound was identified and confirmed as β-sitosterol-D-glucopyranoside. All the spectral data were in complete concurrence with the literature.¹⁷ The BSG obtained from the final optimized process was analysed through HPLC and its purity was found to be 99.6% (Fig. S3†).

The influential parameters were identified from classical optimization experiments based on their effect on target response (yield of BSG). Consequently, only parameters, such as concentration of hydrotrope (mol), temperature (°C) and solid loading (%) (3 factor) at 3 levels (−1, 0, +1) from their scanned range, were considered for the Box–Behnken method based experimental design to obtain the standard set of experiments for RSM based modelling and optimization. 3 factors and 3 levels Box–Behnken design generated 15 sets of experiments/runs, which were carried out twice and the average is depicted in Table S1.†

The experimental data thus obtained were fitted in a second-order polynomial model and regression coefficients were determined as in eqn (1).

where Y is the predicted response factor, β₀ is the intercept and β_i, β_ii, and β_ij are regression coefficients for linear effects, regression coefficients for squared effects, and regression coefficients for interaction effects, respectively. X_i and X_j are the parameters.

A final run of the experiment with the RSM optimized parameters was performed and the yield of BSG was analysed using HPTLC.

To successfully understand the mechanism of hydrotropic extraction and to optimize the influential parameters, the knowledge of its solubility in different hydrotropic solutions at different temperatures and concentration is essential. The solubility of pure BSG in different hydrotropes as a function of hydrotrope concentration is given in Fig. S4.† The trend showed increase in the solubility of BSG with increase in hydrotrope concentration. Na-PTS (2.5 mol) exhibited the best performance in solubilizing BSG (0.88 g mL⁻¹) compared to Na-CS (0.6g mL⁻¹) and Na-Sal (0.26 g mL⁻¹). Based on these observations, Na-PTS, which is also considered as ‘green’ hydrotrope,¹⁸ was selected for further optimization and extraction studies because of its high solubilizing capacity of BSG.

The major disadvantage when this hydrotropic extraction technique¹⁹ is applied in phyto-molecule isolation is that when water is added to dilute the hydrotropic solution, along with target/desired compounds, other non-essential compounds also get precipitated, which lowers the purity of the desired metabolite. In the present study, dilution with water precipitated other low polar molecules along with BSG, which got solubilized in the extraction process due to the action of the hydrotrope. Now, to circumvent this problem, a new approach was developed and applied in which solvents, which are soluble in water and which solubilize hydrotropes, were used instead of water for dilution. The fact that Na-PTS is soluble in methanol, ethanol, and acetone makes them ideal for precipitation. Fig. S5† shows the yield of the precipitate and the purity of BS in the precipitate using various solvents for inducing precipitation in hydrotropic extract. Observations revealed that water has the highest yield (10.4 mg g⁻¹ DM) but the purity of BSG is less (34%). This was due to the fact that other low-polar metabolites were also precipitated along with BSG, which added to the precipitate amount. However, for methanol and ethanol, the purity of BSG was considerably high (67% and 72%, respectively) but the yield was low (3.4 and 3.8 mg g⁻¹ DM, respectively). This was due to the fact that BSG is partially soluble in both the alcohols, and thus a considerable amount of BSG dissolved in the solvent, while only small amount precipitates. Acetone exhibited the best performance for precipitating BSG (yield: 6.4 mg g⁻¹ DM; purity: 92%) because of two advantages; first, it dissolves low-polar compounds that are precipitated along with BSG during the dilution of hydrotrope; thus, precipitating pure BSG. This was possible because of the least solubility of BSG in acetone. Second, it readily decreased the concentration of Na-PTS below MHC because Na-PTS was easily soluble in acetone. Acetonitrile has an advantage of solubility with water but its capacity to precipitate water insoluble molecules like BSG is limited, substantiating its non-consideration to be an ideal solvent. Thus, acetone was chosen as an ideal solvent for the pure isolation of BSG through hydrotropic extraction.

Parameters, such as time of extraction, concentration of hydrotrope, temperature, solid loading, and agitation, were studied for their influence on the final yield, and the amount of solvent required for the precipitation was also studied for its influence on the purity of BSG. Experiments were performed by varying a primary parameter and analysing the yield with respect to time. In Fig. S6,† plots of agitation versus yield of BSG at different time intervals showed that over 1000 rpm the extraction yield remains constant. The trend depicts linearity in the increase of yield with the speed of agitation, until it reaches 1000 rpm. Therefore, 1000 rpm could be used as an optimized speed for extraction. From Fig. S6† it was observed that over three hours of extraction time, the yield remained the same in all the plots containing a different primary parameter such as temperature or solid loading. Thus, the total extraction time could be set to 3 h for the efficient extraction of BSG. The amount of solvent added to induce precipitation had a linear effect on precipitation. The solvent such as acetone was added to the filtrate obtained from hydrotropic extraction to decrease the hydrotropic concentration to MHC; thus, inducing the precipitation of non-water soluble compounds. It was observed that 2.85 mL of diluting solvent was required per mL of hydrotropic extract solution to decrease the concentration of the solution below MHC. MHC of Na-PTS was 0.35 mol. Therefore, this volume (2.85 mL) was made constant in all the extraction experiments. Similarly, MHCs of Na-CS and Na-Sal were 0.65 and 0.1 mol, respectively.²⁰ Due to clear linearity observed in their effects on extraction process, time, agitation and precipitation solvent amounts were fixed to be 3 h, 1000 rpm and 2.8 mL mL⁻¹ of Na-PTS extract solution, respectively, in all the extraction experiments. Fig. S6† also shows the effect of hydrotrope concentration over extraction of BSG. As concentration increased, the extraction yield also increased until a particular concentration (1.5 mol) and then it decreased mildly. Such an observed response might actually affect the extraction kinetics and efficiency. Similarly, BSG yield increased with increase in temperature until 45 °C and then decreased; thus, affecting the extraction efficiency. BSG was also found to be stable at 45 °C as analysed by HPTLC.

The amount of plant material loaded for extraction had direct effect on extraction yield. A solid loading greater than 10% led to a decrease in the yield. This might be due to the insufficiency of the hydrotrope to extract the optimum amount of BSG. Thus, 3 parameters were found to influence the extraction process significantly: concentration of hydrotrope, temperature, and solid loading. Thus, these 3 parameters were considered for RSM based modelling and optimization.

The amount of metabolites in each optimization step and experimental runs according to RSM model was analysed by high performance thin layer chromatography. The HPTLC profiles and the resulting chromatogram are given in Fig. 2. HPTLC method was developed and validated for the effective quantification of BSG in each sample to determine its purity obtained during the precipitation process. The mobile phase was methanol : chloroform 1 : 10 (%, v/v), which resulted in a sharp significantly resolved peak at the R_f values of 0.23 for BSG. Peaks of BSG from different process samples were identified by comparing their spots at their respective R_f = 0.23 values with those obtained by the chromatography of the standards under the same conditions as given in Fig. 2. The comparison of lane 1–3 depicts an increase in the amount of BSG with a minimum amount of other impurities in the precipitate obtained by acetone than water, as illustrated by the peaks. Lane 4 confirms the R_f value of BSG and it corresponded with the R_f value of BSG present in all experimental samples (lanes 1–3).

Fig. 2 High performance thin layer chromatography (HPTLC) analysis. Lane 1-methanolic extract from the stem and roots of D. bipinnata. Lane 2-precipitate obtained using conventional hydrotropic extraction. Lane 3-precipitate obtained using acetone assisted hydrotropic extraction. Lane 4-standard BSG.

Using the Box–Behnken experimental design, the second-order polynomial quadratic response equation (eqn (1)) was used to establish a mutual link between the response dependent variables and independent parameters. The link based on the coded factors was established according to the following equation:

Y₁ = 9.07 + 0.1X₁ + 0.56X₂ + 0.012X₃ + 0.58X₁X₂ + 0.075X₁X₃ − 0.5X₂X₃ − 0.48X₁² − 1.31X₂² − 0.46X₃² (2)

The Box–Behnken matrix and experimental results for hydrotropic extraction and the yield of BSG are summarized in Table S1.† Analysis of variance (ANOVA) was used to assess the statistical significance of quadratic model. The results of ANOVA for the amount of BSG are depicted in Table S2 and S3† whose statistical observations demonstrate that the regression model has a high coefficient of determination (R² = 0.998). Moreover, the R_adj² (0.994) value explains the significance of the model. There appears to be no significant difference between R² and R_adj² values, which is desirable for the model. In addition, low coefficient of variation was observed (0.88), which is usually desired, indicating the good reliability for the experiments carried out in the process. In the present study, F-values were greater and P values were considerably lesser, as depicted in Table S2,† implying that most of the coefficients obtained were significant in the model.

The coefficients and standard error are depicted in Table S3.† The corresponding F-values for the coefficients indicate that the temperature (X₂) produced the largest effect in extracting BSG in the process (F-value: 523.71, P < 0.0001). It was followed by the concentration of hydrotrope (X₁) (F-value: 16.55, P < 0.0001). Solid loading (X₃) had the least effect. The results of the lack of fit test for the models are depicted in Table S4† describing the variation in the data around the fitted model. In the present case, the F-value for lack of fit test was 1.75 and was not significant, implying that the models sufficiently described the obtained data. A three-dimensional response surface and contour graphs were plotted based on the obtained model equation to evaluate the interaction among the operational factors and to determine the optimum values of each parameter. The effects of influential parameters on yield of BSG are shown in Fig. 3. The yield of the metabolites increased with factor levels up to moderate level (0) and then decreased. For example, in Fig. 3, the interaction between the concentration of hydrotrope (A) and temperature (B) is plotted, where the yield of metabolites increases as A increases from 1 to 1.5 mol and then decreases when it extends to 2 mol. Similarly, as temperature (B) reaches 45 °C, the yield reaches the maximum and then decreases. This phenomenon was seen in all the surfaces drawn based on the interaction effects of different factors.

Fig. 3 Response surface plots for the yield of BSG showing the interaction of different process parameters.

Usually, numerical optimization method is used for optimization, in which a desirable value for each input factor and response can be selected.²¹ Using these conditions, the maximum achieved amount of BSG was 9.14 mg g⁻¹ DM with 1.97 mol of Na-PTS, at 49.5 °C and with 9.73% of solid loading at 1000 rpm agitation for 3 h. This result indicates an acceptable fit among the obtained data and the desirability of the model at all points. An additional experiment was carried out to confirm the amount of BSG produced under the optimized conditions, which was found to be 9.14 mg g⁻¹ DM. This was in accordance to the predicted value of 9.2 mg g⁻¹ DM, as in Table S5.† The final yield was 0.92%, which clearly substantiates a significant increase compared to the initial yield of 0.18%, as given in Table 1. The final purity of BSG through optimized SAHP was 99.6%. The colour and texture of the precipitates from different processes are shown in Fig. 4. The optimized yields depict an increase of 80.4% in the total recovery of BSG, further emphasizing the potential for the development and optimization of hydrotropic extraction procedure taking into account the process economics.

Table 1 Yield and purity of BSG from different methods^a

Methodology	Yield (%)	Purity^b (%)	Amount of BSG^c (%)	Increase in yield of BSG (%)
a HE – hydrotropic extraction using water, SAHP-solvent assisted hydrotropic precipitation.b Calculated through HPTLC, purity = 95% was considered as pure BSG.c Amount of BSG present in crude extract/precipitate calculated using HPTLC.
Conventional isolation	0.18	99	0.17	—
HE (water)	1.04	34	0.35	48
Optimized through one variable at a time (HE)	1.8	34	0.61	70
Optimized through RSM (HE)	2.1	34	0.72	75
SAHP (acetone)	0.8	99.6	0.8	77.5
SAHP (acetone) optimized through RSM	0.92	99.6	0.92	80.4

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Fig. 4 (A) Stem and roots of D. bipinnata. (B) Methanolic extract of D. bipinnata. (C) Hydrotropic precipitate using water (BSG = 34% pure). (D) Hydrotropic precipitate using acetone (BSG = 99.6% pure).

Conclusions

In the present study, a novel investigation of solvents in hydrotropic extraction of β-sitosterol-D-glucopyranoside (BSG) from D. bipinnata was optimized for the first time by the Box–Behnken experimental design and response surface methodology based model fitting and optimization in a batch mode ‘green’ extraction process. Analyses of the response surfaces were carried out as a function of the concentration of hydrotrope (X₁), temperature (X₂), and solid loading (X₃) and for the resulting model, ANOVA demonstrated a high correlation coefficient (R² = 0.998), indicating a good fit between the second order regression model and the experimental observations. The optimal conditions obtained through RSM, which produced the maximum amount of BSG (9.14 mg g⁻¹ of dry plant material) included 1.97 mol of sodium p-toluenesulphonate (Na-PTS), 49.5 °C and 9.73% of solid loading at 1000 rpm agitation for 3 h. Thus, it is illustrated that the standard experimental design and RSM based optimization was an efficient strategy for optimizing the operational parameters towards maximizing the recovery of BSG depicting an increase of 80.4%. The operational parameters optimized elucidate the lowest cost needed in extraction process, and thus provide an efficient, rapid and cost-effective method for the isolation and scaling up of the production of BSG from D. bipinnata.

Acknowledgements

The authors would like to thank the Management, SASTRA University, for providing the necessary facilities and the TRR funding. The financial support from the Department of Science and Technology, Government of India, under fast track scheme (SR/FT/CS-10/2011) is earnestly acknowledged.

Notes and references

1. K. H. Pegel, S. Afr. J. Sci., 1997, 93, 263–268.
2. Y. H. Ju, L. M. Clausen, K. F. Allred, A. L. Almada and W. G. Helferich, Nutr. Cancer, 2004, 134, 1145–1151.
3. (a) P. J. D. Bouic and J. H. Lamprecht, Alternat. Med. Rev., 1999, 4, 170–177; (b) O. Hallwachs, MMW Munch. Med. Wochenschr., 1981, 123, 1675–1676.
4. P. J. D. Bouic, A. Clark, J. Lamprecht, M. Freestone, E. J. Pool, R. W. Liebenberg, D. Kotze and P. P. van Jaarsveld, Int. J. Sports Med., 1999, 20, 258–262.
5. S. Subramaniam, M. Keerthiraja and A. Sivasubramanian, Rev. Bras. Farmacogn., 2014, 24, 44–50.
6. J. A. Duke, CRC Handbook of Medicinal Spices, Taylor & Francis, 2002.
7. P. J. D. Bouic, A. Clark, W. Brittle, J. H. Lamprecht, M. Freestone and R. W. Liebenberg, SAMJ, 2001, 91, 848–850.
8. (a) O. J. Pollack, Pharmacol. Ther., 1985, 31, 177–208; (b) K. Ohata, T. Nomura and M. Watanabe, US Pat., 4333926, 1982.
9. P. J. Bouie, S. Etsebeth, R. W. Liebenberg, C. F. Albrecht, K. Pegel and P. P. van Jaarsveld, Int. J. Immunopharmacol., 1996, 18, 693–700.
10. I. I. Brekhman and I. V. Dardymov, Annu. Rev. Pharmacol., 1969, 9, 419–430.
11. W. H. Ling and P. J. H. Jones, Life Sci., 1995, 57, 195–206.
12. (a) R. S. Satyan, M. Sakthivadivel, S. Shankar and M. G. Dinesh, Nat. Prod. Res., 2012, 26, 2232–2234; (b) G. Moorthy, S. Subramaniam, S. Murali, R. Muralidharan and A. Sivasubramanian, Der Pharm. Chem., 2014, 6, 129–134; (c) K. B. Ayaz Ahmed, S. Subramaniam, G. Veerappan, N. Hari, A. Sivasubramanian and A. Veerappan, RSC Adv., 2014, 4, 59130–59136.
13. (a) D. V. Dandekar and V. G. Gaikar, Sep. Sci. Technol., 2003, 38, 1185–1215; (b) G. Raman and V. G. Gaikar, Ind. Eng. Chem. Res., 2002, 41, 2966–2976; (c) G. Raman and V. G. Gaikar, Langmuir, 2003, 19, 8026–8032; (d) S. P. Mishra and V. G. Gaikar, Ind. Eng. Chem. Res., 2004, 43, 5339–5346; (e) S. P. Mishra and V. G. Gaikar, Sep. Sci. Technol., 2006, 41, 1115–1134.
14. (a) J. Prakash Maran and S. Manikandan, Dyes Pigm., 2012, 95, 465–472; (b) B. S. Kaith, R. Sharma, S. Kalia and M. S. Bhatti, RSC Adv., 2014, 4, 40339–40344.
15. (a) G. J. Swamy, A. Sangamithra and V. Chandrasekar, Dyes Pigm., 2014, 111, 64–74; (b) X.-Y. Qv, Y.-Y. Guo and J.-G. Jiang, RSC Adv., 2014, 4, 42202–42210; (c) C. Chellamboli and M. Perumalsamy, RSC Adv., 2014, 4, 22129–22140; (d) R. H. Myers, D. C. Montgomery and C. M. Anderson-Cook, Response surface methodology: process and product optimization using designed experiments, Wiley, 2009.
16. (a) J. He, H. Yan and C. Fan, RSC Adv., 2014, 4, 42608–42616; (b) X.-Y. Qv, Y.-Y. Guo and J.-G. Jiang, RSC Adv., 2014, 4, 42202–42210; (c) K. Selvam, M. Govarthanan, S. Kamala-Kannan, M. Govindharaju, B. Senthilkumar, T. Selvankumar and A. Sengottaiyan, RSC Adv., 2014, 4, 13045.
17. H. Kojima, N. Sato, A. Hatanot and H. Ogurat, Phytochemistry, 1990, 29, 2351–2355.
18. (a) A. Matlack, Introduction to Green Chemistry, Taylor & Francis, 2001; (b) B. S. Pacheco, C. F. P. Nunes, C. T. Rockembach, P. Bertelli, M. F. Mesko, M. Roesch-Ely, S. Moura and C. M. P. Pereira, Green Chem. Lett. Rev., 2014, 7, 265–270.
19. (a) V. G. Gaikar and M. M. Sharma, Sep. Technol., 1993, 3, 2–11; (b) D. Balasubramanian, V. Srinivas, V. G. Gaikar and M. M. Sharma, J. Phys. Chem., 1989, 93, 3865–3870; (c) M. B. Bhat and V. G. Gaikar, Langmuir, 1999, 15, 4740–4751; (d) M. B. Bhat and V. G. Gaikar, Langmuir, 2000, 16, 1580–1592.
20. D. Balasubramanian, V. Srinivas, V. G. Gaikar and M. M. Sharma, J. Phys. Chem., 1989, 93, 3865–3870.
21. M. Amini, H. Younesi, N. Bahramifar, A. A. Z. Lorestani, F. Ghorbani, A. Daneshi and M. Sharifzadeh, J. Hazard. Mater., 2008, 154, 694–702.

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Footnote

† Electronic supplementary information (ESI) available: Description of experimental procedure, statistical data of RSM, solubility studies, NMR spectra, HPLC chromatogram, classical optimization observations. See DOI: 10.1039/c4ra13923b

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