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Journal of Molecular Modeling

, 25:267 | Cite as

A DFT-based analysis of adsorption of Cd2+, Cr3+, Cu2+, Hg2+, Pb2+, and Zn2+, on vanillin monomer: a study of the removal of metal ions from effluents

  • Igor Hernandes Santos Ribeiro
  • Davi Texeira Reis
  • Douglas Henrique PereiraEmail author
Original Paper

Abstract

The density functional theory was used to understand the adsorption process of Cd(II), Cr(III), Cu(II), Hg(II), Pb(II), and Zn(II) ions with the methacrylate monomer derived of vanillin (VMA). Different analyses were carried out: Conformational analysis, molecular electrostatic potential (MEP), adsorption energy, frontier orbitals, hardness, and softness, all of which are necessary to predict the formation of complexes. By means of the molecular electrostatic potential and frontier molecular orbital (FMOs), the best region for adsorption was found, so each metallic ion of the study was placed close to the nitrogen and oxygen atoms of the imine and carboxyl groups of vanillin monomer, respectively. The bond of the metal ions with the nitrogen atom was shown to be stronger than with oxygen atoms, because the charge density of the nitrogen is increased in the formation of the Schiff base with the proximity of the aromatic ring. The monomer showed to be more adsorbent for the Cu(II), Cr(III), and Pb(II) ions because of the high energy values involved. The analysis QTAIM was investigated to understand the character of the interaction between vanillin monomer and metal species, which were shown in almost all cases as covalent partial. Thus, the monomer derived from vanillin has good stability in water and is therefore considered a good material for the remediation of effluents and poisonings.

Keywords

Heavy metals Adsorption DFT Vanillin Wastewater treatment 

Notes

Acknowledgments

The authors acknowledges the National Center for High Performance Processing (Centro Nacional de Processamento de Alto Desempenho – CENAPAD) in São Paulo and UNICAMP (Universidade Estadual de Campinas), for computational resources.

References

  1. 1.
    Sun J, Li M, Zhang Z, Guo J (2019) Unravelling the adsorption disparity mechanism of heavy-metal ions on the biomass-derived hierarchically porous carbon. Appl Surf Sci 471:615–620.  https://doi.org/10.1016/j.apsusc.2018.12.050 CrossRefGoogle Scholar
  2. 2.
    Zeng H, Wang L, Zhang D et al (2019) Highly efficient and selective removal of mercury ions using hyperbranched polyethylenimine functionalized carboxymethyl chitosan composite adsorbent. Chem Eng J 358:253–263.  https://doi.org/10.1016/j.cej.2018.10.001 CrossRefGoogle Scholar
  3. 3.
    Cegłowski M, Schroeder G (2015) Removal of heavy metal ions with the use of chelating polymers obtained by grafting pyridine–pyrazole ligands onto polymethylhydrosiloxane. Chem Eng J 259:885–893.  https://doi.org/10.1016/j.cej.2014.08.058 CrossRefGoogle Scholar
  4. 4.
    Sokolsky-Papkov M, Domb AJ, Golenser J (2006) Impact of aldehyde content on amphotericin B−dextran imine conjugate toxicity. Biomacromolecules 7:1529–1535.  https://doi.org/10.1021/bm050747n CrossRefPubMedGoogle Scholar
  5. 5.
    Zhao J, Niu Y, Ren B et al (2018) Synthesis of Schiff base functionalized superparamagnetic Fe3O4 composites for effective removal of Pb(II) and Cd(II) from aqueous solution. Chem Eng J 347:574–584.  https://doi.org/10.1016/j.cej.2018.04.151 CrossRefGoogle Scholar
  6. 6.
    Tang H, Li C, Duan Y et al (2019) Combined experimental and theoretical studies on adsorption mechanisms of gaseous mercury(II) by calcium-based sorbents: the effect of unsaturated oxygen sites. Sci Total Environ 656:937–945.  https://doi.org/10.1016/j.scitotenv.2018.11.460 CrossRefPubMedGoogle Scholar
  7. 7.
    Chu W-L, Dang N-L, Kok Y-Y et al (2018) Heavy metal pollution in Antarctica and its potential impacts on algae. Polar Sci.  https://doi.org/10.1016/j.polar.2018.10.004 CrossRefGoogle Scholar
  8. 8.
    Zewail TM, Yousef NS (2015) Kinetic study of heavy metal ions removal by ion exchange in batch conical air spouted bed. Alex Eng J 54:83–90.  https://doi.org/10.1016/j.aej.2014.11.008 CrossRefGoogle Scholar
  9. 9.
    Cochrane EL, Lu S, Gibb SW, Villaescusa I (2006) A comparison of low-cost biosorbents and commercial sorbents for the removal of copper from aqueous media. J Hazard Mater 137:198–206.  https://doi.org/10.1016/j.jhazmat.2006.01.054 CrossRefPubMedGoogle Scholar
  10. 10.
    Gao Z, Zhan W, Wang Y et al (2015) Aldehyde-functionalized mesostructured cellular foams prepared by copolymerization method for immobilization of penicillin G acylase. Microporous Mesoporous Mater 202:90–96.  https://doi.org/10.1016/j.micromeso.2014.09.053 CrossRefGoogle Scholar
  11. 11.
    Abdullah NH, Shameli K, Abdullah EC, Abdullah LC (2019) Solid matrices for fabrication of magnetic iron oxide nanocomposites: synthesis, properties, and application for the adsorption of heavy metal ions and dyes. Compos Part B 162:538–568.  https://doi.org/10.1016/j.compositesb.2018.12.075 CrossRefGoogle Scholar
  12. 12.
    Llevot A, Grau E, Carlotti S et al (2016) From lignin-derived aromatic compounds to novel biobased polymers. Macromol Rapid Commun 37:9–28.  https://doi.org/10.1002/marc.201500474 CrossRefPubMedGoogle Scholar
  13. 13.
    Bonnet M-L, Costa D, Protopopoff E, Marcus P (2017) Theoretical study of the Pb adsorption on Ni, Cr, Fe surfaces and on Ni based alloys. Appl Surf Sci 426:788–795.  https://doi.org/10.1016/j.apsusc.2017.07.176 CrossRefGoogle Scholar
  14. 14.
    Tan IAW, Hameed BH, Ahmad AL (2007) Equilibrium and kinetic studies on basic dye adsorption by oil palm fibre activated carbon. Chem Eng J 127:111–119.  https://doi.org/10.1016/j.cej.2006.09.010 CrossRefGoogle Scholar
  15. 15.
    Zhang H, Yong X, Zhou J et al (2016) Biomass vanillin-derived polymeric microspheres containing functional aldehyde groups: preparation, characterization, and application as adsorbent. ACS Appl Mater Interfaces 8:2753–2763.  https://doi.org/10.1021/acsami.5b11042 CrossRefPubMedGoogle Scholar
  16. 16.
    Shakeel F, Anwer MK, Shazly GA, Jamil S (2014) Measurement and correlation of solubility of bioactive compound silymarin in five different green solvents at 298.15K to 333.15K. J Mol Liq 195:255–258.  https://doi.org/10.1016/j.molliq.2014.02.039 CrossRefGoogle Scholar
  17. 17.
    Almeida ARRP, Freitas VLS, Campos JIS et al (2019) Volatility and thermodynamic stability of vanillin. J Chem Thermodyn 128:45–54.  https://doi.org/10.1016/j.jct.2018.07.023 CrossRefGoogle Scholar
  18. 18.
    Fache M, Darroman E, Besse V et al (2014) Vanillin, a promising biobased building-block for monomer synthesis. Green Chem 16:1987–1998.  https://doi.org/10.1039/C3GC42613K CrossRefGoogle Scholar
  19. 19.
    Feng P, Wang H, Lin H, Zheng Y (2019) Selective production of guaiacol from black liquor: effect of solvents. Carbon Resour Conversion 2:1–12.  https://doi.org/10.1016/j.crcon.2018.07.005 CrossRefGoogle Scholar
  20. 20.
    Hassan B, Rajan VK, Mujeeb VMA, K. M (2017) A DFT based analysis of adsorption of Hg 2+ ion on chitosan monomer and its citralidene and salicylidene derivatives: prior to the removal of Hg toxicity. Int J Biol Macromol 99:549–554.  https://doi.org/10.1016/j.ijbiomac.2017.03.032 CrossRefPubMedGoogle Scholar
  21. 21.
    Chai J-D, Head-Gordon M (2008) Long-range corrected hybrid density functionals with damped atom–atom dispersion corrections. Phys Chem Chem Phys 10:6615–6620.  https://doi.org/10.1039/B810189B CrossRefGoogle Scholar
  22. 22.
    Raynea S, Forestb K (2016) A comparative examination of density functional performance against the ISOL24/11 isomerization energy benchmark. Comput Theor Chem 1090:147–152.  https://doi.org/10.1016/j.comptc.2016.06.018 CrossRefGoogle Scholar
  23. 23.
    Matczak P (2015) Assessment of various density functionals for intermolecular N → Sn interactions: the test case of poly(trimethyltin cyanide). Comput Theor Chem 1051:110–122.  https://doi.org/10.1016/j.comptc.2014.10.028 CrossRefGoogle Scholar
  24. 24.
    Liu Y, Liu Y, Gallo AA, Knierima KD, Taylor ER, Tzeng N (2015) Performances of DFT methods implemented in G09 for simulations of the dispersion-dominated CH-π in ligand–protein complex: a case study with glycerol-GDH. J Mol Struct 1084:223–228.  https://doi.org/10.1016/j.molstruc.2014.12.028 CrossRefGoogle Scholar
  25. 25.
    Hariharan PC, Pople JA (1973) The influence of polarization functions on molecular orbital hydrogenation energies. Theor Chim Acta 28:213–222.  https://doi.org/10.1007/BF00533485 CrossRefGoogle Scholar
  26. 26.
    Hehre WJ, Ditchfield R, Pople JA (1972) Self—consistent molecular orbital methods. XII. Further extensions of Gaussian—type basis sets for use in molecular orbital studies of organic molecules. J Chem Phys 56:2257–2261.  https://doi.org/10.1063/1.1677527 CrossRefGoogle Scholar
  27. 27.
    Ditchfield R, Hehre WJ, Pople JA (1971) Self-consistent molecular-orbital methods. IX. An extended Gaussian-type basis for molecular-orbital studies of organic molecules. J Chem Phys 54:724–728.  https://doi.org/10.1063/1.1674902 CrossRefGoogle Scholar
  28. 28.
    Chiodo S, Russo N, Sicilia E (2006) LANL2DZ basis sets recontracted in the framework of density functional theory. J Chem Phys 125:104107.  https://doi.org/10.1063/1.2345197 CrossRefPubMedGoogle Scholar
  29. 29.
    Marenich AV, Cramer CJ, Truhlar DG (2009) Universal solvation model based on solute electron density and on a continuum model of the solvent defined by the bulk dielectric constant and atomic surface tensions. J Phys Chem B 113:6378–6396.  https://doi.org/10.1021/jp810292n CrossRefGoogle Scholar
  30. 30.
    Chong DP, Westwood NPC, Langhoff SR (1984) Methyl- and dimethylketene: He I photoelectron spectra and vertical ionization potentials calculated by using perturbation corrections to Koopmans’ theorem. J Phys Chem 88:1479–1481.  https://doi.org/10.1021/j150652a007 CrossRefGoogle Scholar
  31. 31.
    Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA, Cheeseman JR, ScalmaniG BV, Mennucci B, Petersson GA, Nakatsuji H, Caricato M, Li X, Hratchian HP, Izmaylov AF, Bloino J, Zheng G, Sonnenberg JL, Hada M, Ehara M, Toyota K, Fukuda R, Hasegawa J, Ishida M, Nakajima T, Honda Y, Kitao O, Nakai H, Vreven T, Montgomery JA, Peralta Jr JE, Ogliaro F, Bearpark M, Heyd JJ, Brothers E, Kudin KN, Staroverov VN, Kobayashi R, Normand J, Raghavachari K, Rendell A, Burant JC, Iyengar SS, Tomasi J, Cossi M, Rega N, Millam JM, Klene M, Knox JE, Cross JB, Bakken V, Adamo C, Jaramillo J, Gomperts R, Stratmann RE, Yazyev O, Austin AJ, Cammi R, Pomelli C, Ochterski JW, Martin RL, Morokuma K, Zakrzewski VG, Voth GA, Salvador P, Dannenberg JJ, DapprichS DAD, Farkas Ö, Foresman JB, Ortiz JV, Cioslowski J, Fox DJ (2009) Gaussian 09 Revision D01. Gaussian Inc, WallingfordGoogle Scholar
  32. 32.
    Frisch MJ, Adamo C (2016) Gaussview. Gaussian, Inc, WallingfordGoogle Scholar
  33. 33.
    Bader RFW, Matta CF (2004) Atomic charges are measurable quantum expectation values: a rebuttal of criticisms of QTAIM charges. J Phys Chem A 108:8385–8394.  https://doi.org/10.1021/jp0482666 CrossRefGoogle Scholar
  34. 34.
    Pophristic V, Goodman L (2001) Hyperconjugation not steric repulsion leads to the staggered structure of ethane. Nature 411:565–568.  https://doi.org/10.1038/35079036 CrossRefPubMedGoogle Scholar
  35. 35.
    Raghi KR, Sherin DR, Saumya MJ et al (2018) Computational study of molecular electrostatic potential, docking and dynamics simulations of gallic acid derivatives as ABL inhibitors. Comput Biol Chem 74:239–246.  https://doi.org/10.1016/j.compbiolchem.2018.04.001 CrossRefPubMedGoogle Scholar
  36. 36.
    Hakiri R, Ameur I, Abid S, Derbel N (2018) Synthesis, X-ray structural, Hirshfeld surface analysis, FTIR, MEP and NBO analysis using DFT study of a 4-chlorobenzylammonium nitrate (C7ClH9N)+(NO3). J Mol Struct 1164:486–492.  https://doi.org/10.1016/j.molstruc.2018.03.068 CrossRefGoogle Scholar
  37. 37.
    Ravaei I, Haghighat M, Azami SM (2019) A DFT, AIM and NBO study of isoniazid drug delivery by MgO nanocage. Appl Surf Sci 469:103–112.  https://doi.org/10.1016/j.apsusc.2018.11.005 CrossRefGoogle Scholar
  38. 38.
    Kumar PSV, Raghavendra V, Subramanian V (2016) Bader’s theory of atoms in molecules (AIM) and its applications to chemical bonding. J Chem Sci 128:1527–1536.  https://doi.org/10.1007/s12039-016-1172-3 CrossRefGoogle Scholar
  39. 39.
    Soliman SM, Albering J, Abu-Youssef MAM (2017) Structural analyses of two new highly distorted octahedral copper(II) complexes with quinoline-type ligands; Hirshfeld, AIM and NBO studies. Polyhedron 127:36–50.  https://doi.org/10.1016/j.poly.2017.01.051 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Chemistry CollegiateFederal University of Tocantins, Campus GurupiGurupiBrazil

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