Preparation and application of meso-adsorbent NiFe2O4 for the ultrasound-enhanced removal of dye pollutant in water and wastewater: A multivariate study

Document Type : Research Paper

Authors

1 Department of Chemistry, Faculty of Sciences, University of Sistan and Baluchestan, Zahedan 98135-674, Iran

2 Department of Materials Engineering, Faculty of Engineering, University of Sistan and Baluchestan, Zahedan, Iran

10.22104/jpst.2021.4838.1185

Abstract

In this study, we present a new combustion method for the preparation of meso-adsorbent NiFe2O4 powders. SEM, XRD, and BET were used for the characterization of adsorbents. BET measurements confirmed a specific surface area (SSA) of 87.7 m2.g-1, a total pore volume (PV) of 0.2377 cm3.g-1, and a mean pore size (PS) of 10.841 nm. The mean crystallite diameter of the adsorbent using the Scherrer equation was 10 nm. Also, the response surface methodology and artificial neural network models were used for modeling, optimization, and prediction of responses for removing methyl violet from water and wastewater in lab-scale batches. To study absorption, a four-factor central composite design was used to select the best experimental condition for ultrasonic-assisted adsorption of methyl violet dye. The adjusted R2 of 0.9931 and the predicted R2 of 0.9813 are very close, indicating the compatibility of the experimental results with the quadratic model. According to the results, optimum conditions were set at an ultrasonic time of 231 s, 13.5 mg of adsorbent, a dye concentration of 2.0 mg.L-1, and a pH = 7.9. Also, the learning rule of Levenberg–Marquardt was used for ANN Modeling. According to the proposed ANN, the value of the root mean square error (RMSE) was 2.562, and the value of the correlation coefficient (R2) was 0.986. Also, removal efficiencies of 96.8% and 95.57% were obtained for the tap water and wastewater, respectively.

Graphical Abstract

Preparation and application of meso-adsorbent NiFe2O4 for the ultrasound-enhanced removal of dye pollutant in water and wastewater: A multivariate study

Highlights

  • Herein, we present a new combustion method for the preparation of meso-adsorbent NiFe2O4 powders.
  • SEM, XRD, and BET analysis were used to characterize absorbency.
  • To increase the adsorption efficiency, surface methodology (RSM) and artificial neural network (ANN) methods were used to optimize, model and predict the responses.

Keywords


[1] L. Liu, Z.Y. Gao, X.P. Su, X. Chen, L. Jiang, J.M. Yao, Adsorption removal of dyes from single and binary solutions using a cellulose-based bioadsorbent, ACS Sustain. Chem. Eng. 3 (2015) 432-442.‏
[2] T. Robinson, G. McMullan, R. Marchant, P. Nigam, Remediation of dyes in textile effluent: a critical review on current treatment technologies with a proposed alternative, Bioresource Technol. 77 (2001) 247-255.‏
[3] K. Sinha, P.D. Saha, S. Datta, Extraction of natural dye from petals of Flame of forest (Butea monosperma) flower: Process optimization using response surface methodology (RSM), Dyes Pigments, 94 (2012) 212-216.‏
[4] V.K. Gupta, G. Sharma, D. Pathania, N.C. Kothiyal, Nanocomposite pectin Zr (IV) selenotungsto-phosphate for adsorptional/photocatalytic remediation of methylene blue and malachite green dyes from aqueous system, J. Ind. Eng. Chem. 21 (2015) 957-964.‏
[5] A. Rakhshani Aval, M. Rahmani, E. Ghasemi, Development and optimization of chemometric assisted micro-cloud point extraction for preconcentration and separation of Eriochrome black T in water and wastewater samples, Desalin. Water Treat. 120 (2018) 173-179.‏
[6] J.L. Gong, B. Wang, G.M. Zeng, C.P. Yang, C.G. Niu, Q.Y. Niu, Y. Liang, Removal of cationic dyes from aqueous solution using magnetic multi-wall carbon nanotube nanocomposite as adsorbent, J. Hazard. Mater. 164 (2009) 1517-1522.‏
[7] I.N. Savina, C.J. English, R.L. Whitby, Y. Zheng, A. Leistner, S.V. Mikhalovsky, High efficiency removal of dissolved As (III) using iron nanoparticle-embedded macroporous polymer composites, J. Hazard. Mater. 192 (2011) 1002-1008.‏
[8] S. Hasani, F.D. Ardejani, M.E. Olya, Equilibrium and kinetic studies of azo dye (Basic Red 18) adsorption onto montmorillonite: Numerical simulation and laboratory experiments, Korean J. Chem. Eng. 34 (2017) 2265-2274.‏
[9] G. Bayramoglu, M.Y. Arica, Adsorption of Congo Red dye by native amine and carboxyl modified biomass of Funalia trogii: isotherms, kinetics and thermodynamics mechanisms, Korean J. Chem. Eng. 35 (2018) 1303-1311.‏
[10] Z. Jiahua, W. Suying, G. Hongbo, One-pot synthesis of mgnetic graphene nanocomposites decorated with core@double-shell nanoparticles for fast chromium removal, Environ. Sci. Technol. 46 (2012) 977-985.
[11] R. Kaur, A. Hasan, N. Iqbal, S. Alam, M.K. Saini, S.K. Raza, Synthesis and surface engineering of magnetic nanoparticles for environmental cleanup and pesticide residue analysis: A review, J. Sep. Sci. 37 (2014) 1805-1825.‏
[12] N.N. Nassar, N.N. Marei, Vitale G., L.A. Arar, Adsorptive removal of dyes from synthetic and real textile wastewater using magnetic iron oxide nanoparticles: Thermodynamic and mechanistic insights, Can. J. Chem. Eng. 93 (2015) 1965-1974.‏
[13] N.S. Mishra, A. Kuila, A. Nawaz, S. Pichiah, K.H. Leong, M. Jang, Engineered carbon nanotubes: Review on the role of surface chemistry, mechanistic features, and toxicology in the adsorptive removal of aquatic pollutants, ChemistrySelect, 3 (2018) 1040-1055.‏
[14] I.D. Mall, V.C. Srivastava, N.K. Agarwal, Removal of Orange-G and Methyl Violet dyes by adsorption onto bagasse fly ash-kinetic study and equilibrium isotherm analyses, Dyes Pigments, 69 (2006) 210-223.‏
[15] S.M. Musyoka, H. Mittal, S.B. Mishra, J.C. Ngila, Effect of functionalization on the adsorption capacity of cellulose for the removal of methyl violet, Int. J. Biol. Macromol. 65 (2014) 389-397.
[16] F. Keyhanian, S. Shariati, M. Faraji, M. Hesabi, Magnetite nanoparticles with surface modification for removal of methyl violet from aqueous solutions, Arab. J. Chem. 9 (2016) 348-354.
[17] J. Tang, L. Zong, B. Mu, Y. Zhu, A. Wang, Preparation and cyclic utilization assessment of palygorskite/carbon composites for sustainable efficient removal of methyl violet, Appl. Clay Sci. 161 (2018) 317-325.‏
[18] T. Jiang, Y.D. Liang, Y.J. He, Q. Wang, Activated carbon/NiFe2O4 magnetic composite: A magnetic adsorbent for the adsorption of methyl orange, J. Environ. Chem. Eng. 3 (2015) 1740-1751.
[19] M.J. Livani, M. Ghorbani, Fabrication of NiFe2O4 magnetic nanoparticles loaded on activated carbon as novel nanoadsorbent for Direct Red 31 and Direct Blue 78 adsorption, Environ. Technol. 39 (2018) 2977-2993.
[20] A. Homayonfard, M. Miralinaghi, R. Haji Seyed Mohammad Shirazi, E. Moniri, Removal of Cd (II) Ion from aqueous solution using nickel ferrite magnetic nanoparticles cross-linked chitosan, J. Water Wastewater, 31 (2020) 112-127
[21] C. Chatfield, Introduction to Multivariate Analysis, Routledge, 2018.
[22] J. Hernández-Borges, M.A. Rodríguez-Delgado, F.J. Garcia-Montelongo, Optimization of the microwave-assisted saponification and extraction of organic pollutants from marine biota using experimental design and artificial neural networks, Chromatographia, 63 (2006) 155-160.‏
[23] I.H. Cho, K.D. Zoh, Photocatalytic degradation of azo dye (Reactive Red 120) in TiO2/UV system: Optimization and modeling using a response surface methodology (RSM) based on the central composite design, Dyes Pigments, 75 (2007) 533-543.‏
[24] J.P. Coutinho, G.F. Barbero, O.F. Avellán, A. Garcés-Claver, H.T. Godoy, M. Palma, C.G. Barroso, Use of multivariate statistical techniques to optimize the separation of 17 capsinoids by ultra performance liquid chromatography using different columns, Talanta, 134 (2015) 256-263.‏
[25] N. Khan, T.G. Kazi, M. Tuzen, M. Soylak, A multivariate study of solid phase extraction of beryllium (II) using human hair as adsorbent prior to its spectrophotometric detection, Desalin. Water Treat. 55 (2015) 1088-1095.‏
[26] K. Vivek, K.V. Subbarao, B. Srivastava, Optimization of postharvest ultrasonic treatment of kiwifruit using RSM, Ultrason. Sonochem. 32 (2016) 328-335.‏
[27] E. Ahmadloo, S. Azizi, Prediction of thermal conductivity of various nanofluids using artificial neural network, Int. Commun. Heat Mass, 74 (2016) 69-75.‏
[28] S.A. Hosseini, M. Davodian, A.R. Abbasian, Remediation of phenol and phenolic derivatives by catalytic wet peroxide oxidation over Co-Ni layered double nano hydroxides, J. Taiwan Inst. Chem. E. 75 (2017) 97-104.‏
[29] M. Rahmani, E. Ghasemi, M. Sasani, Application of response surface methodology for air assisted-dispersive liquid-liquid microextraction of deoxynivalenol in rice samples prior to HPLC-DAD analysis and comparison with solid phase extraction cleanup, Talanta, 165 (2017) 27-32.
[30] V. Vatanpour, A. Karami, M. Sheydaei, Central composite design optimization of Rhodamine B degradation using TiO2 nanoparticles/UV/PVDF process in continuous submerged membrane photoreactor, Chem. Eng. Process. 116 (2017) 68-75.‏
[31] P. Davoodi, S.M. Ghoreishi, A. Hedayati, Optimization of supercritical extraction of galegine from Galega officinalis L.: Neural network modeling and experimental optimization via response surface methodology, Korean J. Chem. Eng. 34 (2017) 854-865.‏
[32] X. Zheng, W. Zheng, J. Zhou, X. Gao, Z. Liu, N. Han, J. Yin, Study on the discrimination between Corydalis Rhizoma and its adulterants based on HPLC-DAD-Q-TOF-MS associated with chemometric analysis, J. Chromatogr. B, 1090 (2018) 110-121.‏
[33] A.R. Abbasian, M. Shafiee Afarani, One‑step solution combustion synthesis and characterization of ZnFe2O4 and ZnFe1.6O4 nanoparticles, Appl. Phys. A, 125 (2019) 721.
[34] M.A. Bezerra, R.E. Santelli, E.P. Oliveira, L.S. Villar, L.A Escaleira, Response surface methodology (RSM) as a tool for optimization in analytical chemistry, Talanta, 76 (2008) 965-977.‏
[35] F. Diejing, B. Bo, W. Honglun, S. Yourui, Novel fabrication of PAA/PVA/yeast superabsorbent with interpenetrating polymer network for pH-dependent selective adsorption of dyes, J. Polym. Environ. 26 (2018) 567-588.‏
[36] M. Rahmani, M. Kaykhaii, M. Sasani, Application of Taguchi L16 design method for comparative study of ability of 3A zeolite in removal of Rhodamine B and Malachite green from environmental water samples, Spectrochim. Acta A, 188 (2018) 164-169.