Selective removal of transition metal ions from aqueous solution by metal–organic frameworks

Yutian Zhang, Xudong Zhao, Hongliang Huang, Zhengjie Li, Dahuan Liu* and Chongli Zhong
State Key Laboratory of Organic–Inorganic Composites, Beijing University of Chemical Technology, Beijing 100029, China. E-mail: liudh@mail.buct.edu.cn

Received 26th May 2015 , Accepted 19th August 2015

First published on 19th August 2015


Abstract

Water stable Zr-based metal–organic frameworks (MOFs) with different functional groups were used for selective removal of Cu2+ over Ni2+ from aqueous solution. Due to the unique chelation effect of two carboxyl groups on the adjacent organic ligand as well as the Jahn–Teller effect, UiO-66(Zr)–2COOH exhibits the highest selectivity (up to about 27) for Cu2+/Ni2+ in aqueous solution among the reported adsorbents as far as we know. In addition, the removal process is fast with less than 60 min for equilibration, and the stability and regenerability are good. These results may be helpful not only for the efficient treatment of wastewater containing heavy transition metal ions, but also for metal enrichment and recycling.


1. Introduction

With the rapid development of industry, the pollutants in water are receiving more and more concern. Among them, heavy transition metal ions contamination has become a world-wide environmental problem. These ions can enter into the human body through inhalation, ingestion and skin adsorption to induce various diseases.1 Therefore, wastewater containing heavy metal ions should be treated before being released to the main stream of water, which is a great contribution to public health and environmental sustainable development. Up to now, several methods have been applied for the capture of heavy metal ions from water, including chemical precipitation,2 electrochemical treatment,3 filtration,4 electro-deposition,5,6 and adsorption,7–11 where adsorption process is considered as one of the most attractive methods with low operation cost and efficient capture ability. However, although various kinds of adsorbents have exhibited good performance, the study on the selective adsorption and separation ability for these metal ions is very rare,12,13 which is of great importance for the recycle of these industrial resources.

As a new class of porous materials constituted by metal ions or clusters with organic ligands, metal–organic frameworks (MOFs) have been explored to be excellent adsorbents for adsorption and separation, in both gas14–16 and liquid17–22 phases. Great efforts were made focusing on further improving the performance of MOFs.23 The introduction of metal ions may be an efficient way to increase the number of active sites of materials,24 fully utilizing their intrinsic features including special pore structure and high specific surface area. In this respect, it is instructive to investigate the selective capture of heavy metal ions using MOFs. On the one hand, wastewater can be treated using this kind of adsorbents. On the other hand, the selectively entrapped heavy metal ions in MOFs may be enriched and then recycled through providing additional active sites on the frameworks. Therefore, as a demonstration, we employed several stable MOFs to selectively capture Cu2+ and Ni2+ from aqueous solutions in this study. So far, the related work on the selective removal of heavy metal ions is very limited in MOFs,25 where the selectivity is too low to meet the practical requirement. Moreover, the information obtained in this work may also be useful for removal of Cu2+ from the nickel electrolysis anolyte, which is still a challenging and intriguing task in electrolytic nickel refining process.26

2. Experimental section

2.1 Reagents and solutions

All reagents of analytical grade (ZrCl4, terephthalic acid (BDC), benzene-1,2,4,5-tetracarboxylic acid (BTEC), 2-bromoterephthalic acid (Br-BDC), 1,2,4-benzenetricarboxylic acid (1,2,4-BTC), 1,3-propanesultone (1,3-PS), N,N′-dimethylformamide (DMF), acetone, trichloromethane) were purchased from J&K Chemical (Beijing, China), Sinopharm Chemical Reagent Beijing Co., Ltd or Aladdin (Shanghai), and trichloromethane was further purified using distillation technology. The stock solutions of Cu2+ and Ni2+ were prepared using their nitrate salts, Cu(NO3)2·3H2O and Ni(NO3)2·6H2O. All solutions were prepared using double distilled water.

2.2 MOFs preparation

Considering that the adsorption is performed in aqueous solution, the adsorbents should be water stable. Therefore, a series of MOFs with different functional groups were selected on the basis of UiO-66(Zr), which have exhibited excellent stability.27 UiO-66(Zr)–X (X = H, Br, NH2, NH–(CH2)2–SO3H, 2COOH) were synthesized according to the previously reported procedures.28–30 UiO-66(Zr)–COOH was synthesized and activated according to literatures with modifications.31 The functionalized terephthalic acids (1.8 g, 8.6 mmol) along with ZrO(NO3)2·2H2O (1.0 g, 4.3 mmol), benzoic acid (15.8 g, 129.4 mmol) in DMF (30 mL) were placed in a Teflon lined autoclave and heated at 423 K for 24 h. After the solution was cooled down to room temperature, the white precipitate was collected by filtration, washed with DMF and acetone with the Soxhlet extraction, and dried under vacuum at 353 K.

2.3 Instruments

Power X-ray diffractions of the MOFs were recorded on a D8 Advance X diffractometer with Cu Kα radiation (λ = 1.5406 Å) from 3° to 50° (0.02° per step). The BET data were measured on specific surface and pore size analysis instrument using nitrogen adsorption by 3H-2000PS2 static volume method at 77 K. The concentrations of metal ions were detected by inductive coupled plasma emission spectrometer (ICP). The air constant temperature oscillator was used to react at 303 K.

2.4 Adsorption experiments

Batch adsorption experiments were conducted using 10 mg of absorbent with 10 mL solution in a 20 mL glass bottle. The solution contained heavy metal ions mixture (the ratio of mass is 1[thin space (1/6-em)]:[thin space (1/6-em)]1) and was shaken in a speed of 130 rpm at 303 K. For the study of the effect of interfering ions, the concentration of interfering ion varied from 50 to 1000 mg L−1. The kinetic parameters of the adsorption were collected with the contact time of 5–600 min. Adsorption isotherms were obtained with Cu2+ or Ni2+ concentration up to about 60 mg L−1. To confirm the effect of pH on the stability and adsorption, solutions with different pH ranging from 2.0 to 6.0 were prepared using 0.1 mol L−1 NaOH or HCl. All the experiments were repeated for at least 3 times to determine the accuracy and veracity of the experimental data. For competitive experiments, selectivity αi,j can be calculated using eqn (1),
 
image file: c5ra09897a-t1.tif(1)
where qi and qj are the amounts (mg g−1) of metal ions i and j adsorbed per gram of MOF, and cj and ci are the equilibrium concentrations (mg L−1) of metal ions j and i in aqueous solution. The accuracy of selectivity calculated using eqn (1) decreases in cases where the relative concentration differences between solutions with and without adsorbent approach the experimental error.32

2.5 Recycling experiments

After the typical adsorption test, in order to regenerate the metal-binding property, UiO-66(Zr)–2COOH with adsorbed metal ions was dispersed into 10 mL of 0.25 M hydrochloric acid solution for at least three times. Then, the solids were collected using a centrifuge and washed repeatedly with excessive amount of deionized water (pH = 7) to neutralize the acidic condition.33 After drying in an oven at 75 °C, the solids were re-added into the fresh solution with metal ions to investigate the recovered separation capacity.

3. Results and discussion

Fig. 1 shows the XRD patterns of as-synthesized MOFs. It is obvious that they are in good agreement with those reported in literature.34 The N2 adsorption data at 77 K indicate that the BET of these MOFs decrease with the increase of functional group size, as listed in Table 1. At the first step, the adsorption of pure component was investigated and the results are shown in Fig. 2, as a function of the initial metal ion concentration (C0) in the solutions. It can be seen that the functional group plays an important role on the uptake of Cu2+. The groups of –2COOH, –NH–(CH2)2–SO3H, and –NH2 can improve the adsorption capacity compared to the pristine UiO-66(Zr), among which –2COOH exhibits the best performance. It should be noted that UiO-66(Zr)–COOH hardly adsorbs Cu2+. This may be attributed to the fact that it is hard for single carboxyl group to coordinate to Cu2+. Recent work indicated that the uncoordinated free carboxyl group chelated Cu2+ with the help of carboxyl group on the ligand,25 which contributes greatly to the high adsorption capacity of transition metal ions.35 In UiO-66(Zr)–COOH, there are very few free carboxyl groups besides the one on ligand. In contrast, carboxyl groups in the adjacent ligand are close to each other in UiO-66(Zr)–2COOH, showing similar chelation effect with Cu2+ as uncoordinated free carboxyl group. Thus, the adsorption behavior of Cu2+ in UiO-66(Zr)–COOH is totally different from that in UiO-66(Zr)–2COOH. For Ni2+, most of these MOFs have poor adsorption capacities, except for UiO-66(Zr)–2COOH, while it is still very low compared to Cu2+. This may be ascribed to the difference in coordination ability for these two transition metal ions. According to the Jahn–Teller effect theory, Cu2+ undergoes a significant Jahn–Teller distortion in contrast to Ni2+, leading to the stronger coordination ability.36,37 As a result, UiO-66(Zr)–2COOH can entrap more Cu2+ than Ni2+ using carboxyl groups.
image file: c5ra09897a-f1.tif
Fig. 1 PXRD patterns for UiO-66(Zr)–X (X = H, Br, NH2, COOH, NH2–(CH2)2–SO3H, and 2COOH): (a) as-synthesized, (b) after adsorption.
Table 1 BET surface areas and pore volumes of six functional Zr-MOFs
MOFs BET surface areaa (m2 g−1) Pore volumeb (cm3 g−1)
a Calculated from N2 adsorption isotherms at 77 K in range of P/P0 = 0.005–0.05.b Calculated at N2 adsorption amounts at P/P0 = 0.95.
UiO-66(Zr) 1204 0.6
UiO-66(Zr)–NH2 1079 0.4
UiO-66(Zr)–Br 966 0.5
UiO-66(Zr)–COOH 653 0.4
UiO-66(Zr)–NH–(CH2)2–SO3H 690 0.3
UiO-66(Zr)–2COOH 488 0.2



image file: c5ra09897a-f2.tif
Fig. 2 Adsorption uptakes of Cu2+ (a) and Ni2+ (b) in different MOFs as a function of the initial metal ion concentration.

On the basis of data for single components mentioned above, competitive adsorption experiments in Cu2+/Ni2+ system were performed in UiO-66(Zr)–2COOH to further investigate the selectivity for these metal ions. As illustrated in Fig. 3, the selectivity increases with the increase of the initial ion concentration, which can reach up to 26.96 on the condition that the initial concentration is about 50 mg L−1. To the best of our knowledge, such separation performance for the Cu2+/Ni2+ system in aqueous solution is much better than all the adsorbents reported so far, as shown in Table 2.


image file: c5ra09897a-f3.tif
Fig. 3 Adsorption uptakes (a) and selectivity (b) of the Cu2+/Ni2+ system in UiO-66(Zr)–2COOH as a function of the initial metal ion concentration.
Table 2 Comparison of adsorption and selectivity in UiO-66(Zr)–2COOH with those in other reported adsorbents in aqueous solution
Material Adsorption capacity (mg g−1) Cu2+/Ni2+ selectivity Ref.
Cu2+ Ni2+
a The max adsorption capacity ratio of single metal ion adsorption.
CHB 15.38 8.68 2.63 38
RDS-50 83.33 71.43 1.17a 39
Clay 28.00 21.30 1.31a 40
Peat moss 7.52 5.94 1.41 41
Modified chitosan 66.70 15.30 4.36a 42
Clinoptilolite 5.24 1.12 12.22 43
(MAAm-co-AA)/MMT 27.10 13.60 2.10 44
MMT 3.11 2.80 1.11a 45
Nature zeolite 9.81 5.99 1.79 46
Nature zeolite (with Ca2+) 8.84 4.75 2.05 46
[Zn(trz)(H2betc)0.5]·DMF 32.01 3.12 11.02 25
UiO-66(Zr)–2COOH 11.04 0.52 26.96 This work


To further analyze the separation performance, the adsorption kinetics for the Cu2+/Ni2+ system is also studied. Fig. 4 shows the effect of contact time. It is obvious that adsorption for these two ions can reach equilibrium in less than 60 min. In addition, the experimental data were fitted using pseudo-first-order model and pseudo-second-order model,

 
Pseudo-first-order model: ln(QeQt) = ln[thin space (1/6-em)]Qek1t (2)
 
image file: c5ra09897a-t2.tif(3)
where Qe and Qt (mg g−1) are the adsorption capacity for equilibrium and at time t (min) respectively, k1 and k2 are rate constants of the pseudo-first-order model and pseudo-second-order model respectively. The kinetic parameters are given in Table 3. It can be seen that the experimental data fitted well with pseudo-second-order model, indicating the rate-limiting step may be the chemisorption process.47 This further confirms that these transition metal ions are captured through chelation effect discussed above.


image file: c5ra09897a-f4.tif
Fig. 4 Effect of contact time on the adsorption (a) and selectivity (b) of Cu2+/Ni2+.
Table 3 Kinetic parameters of the adsorption of Cu2+ and Ni2+ in UiO-66(Zr)–2COOH
  Pseudo-first-order-model Pseudo-second-order-model
k1 (min−1) Qe,cal (mg g−1) R2 k2 (g mg−1 min−1) Qe,cal (mg g−1) R2
Cu2+ 0.0022 2.4081 0.2349 0.0139 11.3507 0.9993
Ni2+ 0.0062 64.3030 0.9135 0.8974 0.4813 0.9996


Previous studies have demonstrated that the adsorption process of metal ions would be influenced by the pH value of the initial solution (pH0).48 Therefore, the measurements were further performed at different initial pH values. From Fig. 5a, the adsorption capacity for Cu2+ increases with the pH0 changing from 3.1 to 6.0, while for Ni2+ the change is not evident. As a result, the selectivity increases and remains nearly constant with the increasing pH0 from 4.0 to 6.0 (Fig. 5b). In order to further explore the potential adsorption mechanism of Cu2+ in UiO-66(Zr)–2COOH, the pH value of the solution before and after (pHf) adsorption was detected. As shown in Fig. 5c, pHf is lower than pH0 and keeps nearly constant, indicating that the amount of H+ produced in solution increases with the increase of the pH0. Due to the chelation between carboxyl groups and heavy metal ions, adsorption should be occurred with the ion exchange mechanism, as illustrated in eqn (4). The –COOH group transforms into –COO through ionization process in solution at the first step. The electrostatic attraction might also accelerate the migration of Cu2+ and promote the adsorption process. However, according to the Le Châtelier's principle, the lower solution pH can restrain the above response and the adsorption of Cu2+.49

 
MOF − 2COOH + Cu2+ = MOF − 2(COO)Cu + 2H+ (4)


image file: c5ra09897a-f5.tif
Fig. 5 Effect of pH0 on the adsorption (a) and selectivity (b) of Cu2+/Ni2+ in UiO-66(Zr)–2COOH; the change of pH before and after the adsorption (c).

In aqueous medium, there are several kinds of other metal ions, such as Zn2+, Mg2+, Ca2+. Bearing these in mind, we further investigated the influence of the interfering ions in this study. The concentrations of interfering metal ions were equal to the initial concentrations of target metal ions.50 As can be seen from Table 4, these three metal ions (Zn2+, Mg2+, Ca2+) only induce a slight decrease of adsorption of Cu2+ and Ni2+, and do not significantly interfere the selectivity of Cu2+/Ni2+ under the experimental conditions. It may be due to the specific Jahn–Teller effect for Cu2+. In contrast, for the other reported adsorbents, for example nature zeolite, it is found that Ca2+ in the solution leads to an obvious decrease in the uptake of Cu2+ and Ni2+ and an increase in the selectivity of Cu2+/Ni2+.46 To further study such effect, we increased the concentration of interfering ions by taking Ca2+ as an example. The results in Table 4 revealed that the effect is still not evident.

Table 4 Effects of the interfering ions on the adsorption and selectivity of Cu2+/Ni2+
Metal ions Concentration (mg L−1) Adsorption capacity (mg g−1) Selectivity
Cu2+ Ni2+
11.04 0.52 26.96
Zn2+ 50 10.61 0.49 27.21
Mg2+ 50 10.96 0.51 27.24
Ca2+ 50 10.79 0.50 27.24
Ca2+ 1000 10.67 0.48 27.95


From the practical point of view, an excellent adsorbent should have good regenerability and reusability besides high adsorption capacity and selectivity. Thus, the regeneration of UiO-66(Zr)–2COOH was further investigated. Through the simple regeneration processes using hydrochloric acid solution and deionized water, the Cu2+ and Ni2+ were washed out and UiO-66(Zr)–2COOH recovered the metal ion binding performance. As can be seen from Fig. 6, the selectivity changes a little after five cycles and the variation is within 2.0%. In addition, the PXRD patterns of the samples after adsorption and after desorption are displayed in Fig. 7, indicating its good stability. The above results show that UiO-66(Zr)–2COOH can be used as a recyclable adsorbent for the separation of heavy metal ions.


image file: c5ra09897a-f6.tif
Fig. 6 Selectivity of Cu2+/Ni2+ in adsorption–desorption cycles in UiO-66(Zr)–2COOH.

image file: c5ra09897a-f7.tif
Fig. 7 PXRD patterns of as-synthesized UiO(Zr)-66–2COOH, and the samples after adsorption and after desorption (the 5th cycle).

4. Conclusions

In this work, two typical transition heavy metal ions, Cu2+ and Ni2+, were adsorbed using water stable Zr-MOFs with different functional groups. UiO-66(Zr)–2COOH exhibited high selective capture performance of Cu2+ from aqueous solution, due to the chelation effect of two carboxyl groups on the adjacent organic ligand as well as the significant Jahn–Teller distortion. The selectivity in aqueous solution is highest among the adsorbents so far. In addition, the stability and regenerability are good. The results may provide not only an efficient approach for the treatment of wastewater with heavy metal ions contamination, but also a method for metal enrichment and recycling in MOFs.

Acknowledgements

Financial support by the National Key Basic Research Program of China (“973”) (2013CB733503) and the Natural Science Foundation of China (no. 21136001 and 21276008) are greatly appreciated. D. L. also thanks the support of Beijing Higher Education Young Elite Teacher Project (no. YETP0486).

Notes and references

  1. H. Faghihian, H. Nourmoradi and M. Shokouhi, Desalin. Water Treat., 2014, 52, 305–313 CrossRef CAS PubMed.
  2. C. Duran, S. O. Tumay, D. Ozdes, H. Serencam and H. Bektas, Int. J. Food Sci. Technol., 2014, 49, 1586–1592 CrossRef CAS PubMed.
  3. S. Velazquez-Peña, C. Barrera-Díaz, I. Linares-Hernández, B. Bilyeu and S. A. Martínez-Delgadillo, Ind. Eng. Chem. Res., 2012, 51, 5905–5910 CrossRef.
  4. R. Li, T. A. Mulder, U. Beckmann, P. D. W. Boyd and S. Brooker, Inorg. Chim. Acta, 2004, 357, 3360–3368 CrossRef CAS PubMed.
  5. A. Kudelski, M. Janik-Czachor, J. Bukowska, M. Dolata and A. Szummer, J. Mol. Struct., 1999, 482–483, 245–248 CrossRef CAS.
  6. D. T. Read, Y. W. Cheng and R. Geiss, Microelectron. Eng., 2004, 75, 63–70 CrossRef CAS PubMed.
  7. A. Ghaee, M. Shariaty-Niassar, J. Barzin and A. Zarghan, Appl. Surf. Sci., 2012, 258, 7732–7743 CrossRef CAS PubMed.
  8. I. Villaescusa, N. Fiol, M. Martínez, N. Miralles, J. Poch and J. Serarols, Water Res., 2004, 38, 992–1002 CrossRef CAS PubMed.
  9. A. K. Bhattacharya, S. N. Mandal and S. K. Das, Chem. Eng. J., 2006, 123, 43–51 CrossRef CAS PubMed.
  10. S.-H. Lin and R.-S. Juang, J. Hazard. Mater., 2002, B92, 315–326 CrossRef.
  11. Ö. Yavuz, Y. Altunkaynak and F. Güzel, Water Res., 2003, 37, 948–952 CrossRef.
  12. S. R. Shukla and R. S. Pai, Sep. Purif. Technol., 2005, 43, 1–8 CrossRef CAS PubMed.
  13. S. R. Shukla and R. S. Pai, Bioresour. Technol., 2005, 96, 1430–1438 CrossRef CAS PubMed.
  14. P.-Z. Li, X.-J. Wang, K. Zhang, A. Nalaparaju, R. Zou, R. Zou, J. Jiang and Y. Zhao, Chem. Commun., 2014, 50, 4683–4685 RSC.
  15. W. M. Bloch, R. Babarao, M. R. Hill, C. J. Doonan and C. J. Sumby, J. Am. Chem. Soc., 2013, 135, 10441–10448 CrossRef CAS PubMed.
  16. R. Sathre and E. Masanet, RSC Adv., 2013, 3, 4964–4975 RSC.
  17. X.-P. Zhou, Z. Xu, M. Zeller and A. D. Hunter, Chem. Commun., 2009, 5439–5441 RSC.
  18. Y.-X. Tan, Y.-P. He, M. Wang and J. Zhang, RSC Adv., 2014, 4, 1480–1483 RSC.
  19. S. H. Jhung, N. A. Khan and Z. Hasan, CrystEngComm, 2012, 14, 7099–7109 RSC.
  20. M. R. Sohrabi, Z. Matbouie, A. A. Asgharinezhad and A. Dehghani, Microchim. Acta, 2013, 180, 589–597 CrossRef CAS.
  21. Y. Wang, J. Xie, Y. Wu, H. Ge and X. Hu, J. Mater. Chem. A, 2013, 1, 8782–8789 CAS.
  22. F. Ke, L.-G. Qiu, Y.-P. Yuan, F.-M. Peng, X. Jiang, A.-J. Xie, Y.-H. Shen and J.-F. Zhu, J. Hazard. Mater., 2011, 196, 36–43 CrossRef CAS PubMed.
  23. K. Jayaramulu, R. P. Narayanan, S. J. George and T. K. Maji, Inorg. Chem., 2012, 51, 10089–10091 CrossRef CAS PubMed.
  24. Y. Zhou, H.-H. Chen and B. Yan, J. Mater. Chem. A, 2014, 2, 13691–13697 CAS.
  25. X. Meng, R.-L. Zhong, X.-Z. Song, S.-Y. Song, Z.-M. Hao, M. Zhu, S.-N. Zhao and H.-J. Zhang, Chem. Commun., 2014, 50, 6406–6408 RSC.
  26. L. Li, X. Chen, X. Liu and Z. Zhao, Hydrometallurgy, 2014, 146, 149–153 CrossRef CAS PubMed.
  27. J. H. Cavka, S. Jakobsen, U. Olsbye, N. Guillou, C. Lamberti, S. Bordiga and K. P. Lillerud, J. Am. Chem. Soc., 2008, 130, 13850–13851 CrossRef PubMed.
  28. W. Zhang, H. Huang, C. Zhong and D. Liu, Phys. Chem. Chem. Phys., 2012, 14, 2317–2325 RSC.
  29. Y. Luan, N. Zheng, Y. Qi, J. Yu and G. Wang, Eur. J. Inorg. Chem., 2014, 4268–4272 CrossRef CAS PubMed.
  30. Q. Yang, S. Vaesen, F. Ragon, A. D. Wiersum, D. Wu, A. Lago, T. Devic, C. Martineau, F. Taulelle, P. L. Llewellyn, H. Jobic, C. Zhong, C. Serre, G. D. Weireld and G. Maurin, Angew. Chem., Int. Ed., 2013, 52, 10316–10320 CrossRef CAS PubMed.
  31. S. Biswas, J. Zhang, Z. Li, Y.-Y. Liu, M. Grzywa, L. Sun, D. Volkmer and P. V. D. Voort, Dalton Trans., 2013, 42, 4730–4737 RSC.
  32. L. Alaerts, M. Maes, L. Giebeler, P. A. Jacobs, J. A. Martens, J. F. M. Denayer, C. E. A. Kirschhock and D. E. D. Vos, J. Am. Chem. Soc., 2008, 130, 14170–14178 CrossRef CAS PubMed.
  33. J. Song, H. Kong and J. Jang, J. Colloid Interface Sci., 2011, 359, 505–511 CrossRef CAS PubMed.
  34. S. J. Garibay and S. M. Cohen, Chem. Commun., 2010, 46, 7700–7702 RSC.
  35. Z. Chen, Z. Geng, Z. Zhang, L. Ren, T. Tao, R. Yang and Z. Guo, Eur. J. Inorg. Chem., 2014, 3172–3177 CrossRef CAS PubMed.
  36. K. Prout, A. Edwards, V. Mtetwa, J. Murray, J. F. Saunders and F. J. C. Rossotti, Inorg. Chem., 1997, 36, 2820–2825 CrossRef CAS PubMed.
  37. R. J. Deeth and M. A. Hitchman, Inorg. Chem., 1986, 25, 1225–1233 CrossRef CAS.
  38. C. M. Futalan, C.-C. Kan, M. L. Dalida, K.-J. Hsien, C. Pascua and M.-W. Wan, Carbohydr. Polym., 2011, 83, 528–536 CrossRef CAS PubMed.
  39. R. Kumar, M. Kumar, R. Ahmad and M. A. Barakat, Chem. Eng. J., 2013, 218, 32–38 CrossRef CAS PubMed.
  40. K. G. Bhattacharyya and S. S. Gupta, Chem. Eng. J., 2008, 136, 1–13 CrossRef CAS PubMed.
  41. B. S. Gupta, M. Curran, S. Hasan and T. K. Ghosh, J. Environ. Manage., 2009, 90, 954–960 CrossRef PubMed.
  42. L. Zhou, Y. Wang, Z. Liu and Q. Huang, J. Hazard. Mater., 2009, 161, 995–1002 CrossRef CAS PubMed.
  43. M. Sprynskyy, B. Buszewski, A. P. Terzyk and J. Namieśnik, J. Colloid Interface Sci., 2006, 304, 21–28 CrossRef CAS PubMed.
  44. A. Barati, M. Asgari, T. Miri and Z. Eskandari, Environ. Sci. Pollut. Res., 2013, 20, 6242–6255 CrossRef CAS PubMed.
  45. C. O. Ijagbemi, M.-H. Baek and D.-S. Kim, J. Hazard. Mater., 2009, 166, 538–546 CrossRef CAS PubMed.
  46. M. Panayotova and B. Velikov, J. Environ. Sci. Health, Part A: Toxic/Hazard. Subst. Environ. Eng., 2002, 37, 139–147 CrossRef PubMed.
  47. S.-H. Huang and D.-H. Chen, J. Hazard. Mater., 2009, 163, 174–179 CrossRef CAS PubMed.
  48. X. Zhao, D. Liu, H. Huang, W. Zhang, Q. Yang and C. Zhong, Microporous Mesoporous Mater., 2014, 185, 72–78 CrossRef CAS PubMed.
  49. K. Cheng, Y.-M. Zhou, Z.-Y. Sun, H.-B. Hu, H. Zhong, X.-K. Kong and Q.-W. Chen, Dalton Trans., 2012, 41, 5854–5861 RSC.
  50. P. Yin, Q. Xu, R. Qu, G. Zhao and Y. Sun, J. Hazard. Mater., 2010, 173, 710–716 CrossRef CAS PubMed.

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