A chemometrics approach to predict the dispersibility of graphene in various liquid phases using theoretical descriptors and solvent empirical parameters

Colloids and Surfaces A: Physicochemical and Engineering Aspects

Volumn 441, Issue , 2014, Pages 766-775

  Yousefinejad, Saeed ^a   Hemmateenejad, Bahram ^a  

^a SHIRAZ UNIVERSITY   (Iran)

Author keywords

Dispersibility; Graphene; Nano science; QSPR; Solvent empirical parameters

Indexed keywords

LIQUIDS; REGRESSION ANALYSIS; SOLVENTS; VAN DER WAALS FORCES;

DESCRIPTION ABILITIES; DISPERSIBILITIES; DISPERSIVE INTERACTIONS; EMPIRICAL PARAMETERS; MOLECULAR DESCRIPTORS; MULTILINEAR REGRESSION MODEL; QSPR; VAN DER WAALS INTERACTIONS;

GRAPHENE;

COPPER; GRAPHENE; SOLVENT;

ABSORPTION; ARTICLE; CALIBRATION; CHEMICAL INTERACTION; CHEMOMETRICS; COMPARATIVE STUDY; DENSITY; DIPOLE; DISPERSION; ELECTRON; FLUORINE NUCLEAR MAGNETIC RESONANCE; HYDROGEN BOND; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE PROPERTY RELATION; SOLUBILITY; SOLVATION;

EID: 84890249967     PISSN: 09277757     EISSN: 18734359     Source Type: Journal    
DOI: 10.1016/j.colsurfa.2013.03.020     Document Type: Article

References (66)

1. Novoselov K.S., Geim A.K., Morozov S.V., Jiang D., Zhang Y., Dubonos S.V., Grigorieva I.V., Firsov A.A. Electric field effect in atomically thin carbon films. Science 2004, 306:666-669.
2. Geim A.K., Novoselov K.S. The rise of graphene. Nat. Mater. 2007, 6:183-191.
3. Tkachev S.V., Buslaeva E.Y., Gubin S.P. Graphene: a novel carbon nanomaterial. Inorg. Mater. 2011, 47:1-10.
4. Blake P., Hill E.W., Neto A.H.C., Novoselov K.S., Jiang D., Yang R., Booth T.J., Geim A.K. Making graphene visible. Appl. Phys. Lett. 2007, 91:063124.
5. Gaskell P.E., Skulason H.S., Rodenchuk C., Szkopek T. Counting graphene layers on glass via optical reflection microscopy. Appl. Phys. Lett. 2009, 94:143101.
6. Wang F., Zhang Y.B., Tian C.S., Girit C., Zettl A., Crommie M., Shen Y.R. Gate-variable optical transitions in graphene. Science 2008, 320:206-209.
7. Affoune A.M., Prasad B.L.V., Sato H., Enoki T., Kaburagi Y., Hishiyama Y. Experimental evidence of a single nano-graphene. Chem. Phys. Lett. 2001, 348:17-20.
8. 2 by graphene. J. Phys. Chem. C 2008, 112:15704-15707.
9. Dutta S., Pati S.K. Novel properties of graphene nanoribbons: a review. J. Mater. Chem. 2010, 20:8207-8223.
10. Lee C., Wei X.D., Kysar J.W., Hone J. Measurement of the elastic properties and intrinsic strength of monolayer graphene. Science 2008, 321:385-388.
11. Blake P., Brimicombe P.D., Nair R.R., Booth T.J., Jiang D., Schedin F., Ponomarenko L.A., Morozov S.V., Gleeson H.F., Hill E.W., Geim A.K., Novoselov K.S. Graphene-based liquid crystal device. Nano Lett. 2008, 8:1704-1708.
12. Wang X., Zhi L.J., Mullen K. Conductive graphene electrodes for dye-sensitized solar cells. Nano Lett. 2008, 8:323-327.
13. Stankovich S., Dikin D.A., Dommett G.H.B., Kohlhaas K.M., Zimney E.J., Stach E.A., Piner R.D., Nguyen S.T., Ruoff R.S. Graphene-based composite materials. Nature 2006, 442:282-286.
14. Hernandez Y., Lotya M., Rickard D., Bergin S.D., Coleman J.N. Measurement of multicomponent solubility parameters for graphene facilitates solvent discovery. Langmuir 2010, 26:3208-3213.
15. Niyogi S., Bekyarova E., Itkis M.E., McWilliams J.L., Hamon M.A., Haddon R.C. Solution properties of graphite and graphene. J. Am. Chem. Soc. 2006, 128:7720-7721.
16. Stankovich S., Dikin D.A., Piner R.D., Kohlhaas K.A., Kleinhammes A., Jia Y., Wu Y., Nguyen S.T., Ruoff R.S. Synthesis of graphene-based nanosheets via chemical reduction of exfoliated graphite oxide. Carbon 2007, 45:1558-1565.
17. Paredes J.I., Villar-Rodil S., Martinez-Alonso A., Tascon J.M.D. Graphene oxide dispersions in organic solvents. Langmuir 2008, 24:10560-10564.
18. Lotya M., Hernandez Y., King P.J., Smith R.J., Nicolosi V., Karlsson L.S., Blighe F.M., De S., Wang Z., McGovern I.T., Duesberg G.S., Coleman J.N. Liquid phase production of graphene by exfoliation of graphite in surfactant/water solutions. J. Am. Chem. Soc. 2009, 131:3611-3620.
19. Hernandez Y., Nicolosi V., Lotya M., Blighe F.M., Sun Z., De S., McGovern I.T., Holland B., Byrne M., Boland J.J., Niraj P., Duesberg G., Krishnamurthy S., Goodhue R., Hutchison J., Scardaci V., Ferrari A.C., Coleman J.N. High-yield production of graphene by liquid-phase exfoliation of graphite. Nat. Nanotechnol. 2008, 3:563-568.
20. Bourlinos A.B., Georgakilas V., Zboril R., Steriotis T.A., Stubos A.K. Liquid-phase exfoliation of graphite towards solubilized graphenes. Small 2009, 5:1841-1845.
21. Shih C.-J., Lin S., Strano M.S., Blankschtein D. Understanding the stabilization of liquid-phase-exfoliated graphene in polar solvents: molecular dynamics simulations and kinetic theory of colloid aggregation. J. Am. Chem. Soc. 2010, 132:14638-14648.
22. Bouton F., Durand M., Nardello-Rataj V., Borosy A.P., Quellet C., Aubry J.-M. A QSPR model for the prediction of the "fish-tail" temperature of CiE4/water/polar hydrocarbon oil systems. Langmuir 2010, 26:7962-7970.
23. Hemmateenejad B., Yousefinejad S., Mehdipour A.R. Novel amino acids indices based on quantum topological molecular similarity and their application to QSAR study of peptides. Amino Acids 2011, 40:1169-1183.
24. Zhou P., Tian F., Wu Y., Li Z., Zhicai S. Quantitative sequence-activity model (QSAM): applying QSAR strategy to model and predict bioactivity and function of peptides, proteins and nucleic acids. Curr. Comput. Aided Drug Des. 2008, 4:311-321.
25. Hemmateenejad B., Javidnia K., Nematollahi M., Elyasi M. QSAR studies on the antiviral compounds of natural origin. J. Iran. Chem. Soc. 2009, 6:420-435.
26. Verma J., Khedkar V.M., Coutinho E.C. 3D-QSAR in drug design - a review. Curr. Top. Med. Chem. 2010, 10:95-115.
27. Frisch M.J., Trucks G.W., Schlegel H.B., Scuseria G.E., Robb M.A., Cheeseman J.R., et al. Gaussian 98. Revision A.7 1998, Gaussian, Inc., Pittsburgh, PA.
28. Katritzky A.R., Tamm T., Wang Y., Sild S., Karelson M. QSPR treatment of solvent scales. J. Chem. Inf. Comput. Sci. 1999, 39:684-691.
29. Katritzky A.R., Fara D.C., Wang H., Tämm K., Karelson M. Quantitative measures of solvent polarity. Chem. Rev. 2004, 104:175-198.
30. Katritzky A.R., Fara D.C., Kuanar M., Hur E., Karelson M. The classification of solvents by combining classical QSPR methodology with principal component analysis. J. Phys. Chem. A 2005, 109:10323-10341.
31. Buncel E., Rajagopal S. Solvatochromism and solvent polarity scales. Acc. Chem. Res. 1990, 23:226-231.
32. Thanikaivelan P., Subramanian V., Rao J.R., Nair B.U. Application of quantum chemical descriptor in quantitative structure activity and structure property relationship. Chem. Phys. Lett. 2000, 323:59-70.
33. Hemmateenejad B., Yazdani M. QSPR models for half-wave reduction potential of steroids: a comparative study between feature selection and feature extraction from subsets of or entire set of descriptors. Anal. Chim. Acta 2009, 634:27-35.
34. Baumann K. Chance correlation in variable subset regression: influence of the objective function, the selection mechanism, and ensemble averaging. QSAR Comb. Sci. 2005, 24:1033-1046.
35. Kamlet M.J., Taft R.W. Linear solvation energy relationships. Part 1. Solvent polarity-polarizability effects on infrared spectra. J. Chem. Soc., Perkin Trans. 1979, 2:337-341.
36. Kamlet M.J., Taft R.W. Linear solvation energy relationships. Part 2. Correlations of electronic spectral data for aniline indicators with solvent π* and β values. J. Chem. Soc., Perkin Trans. 1979, 2:342-348.
37. Kamlet M.J., Abboud J-L.M., Abraham M.H., Taft R.W. Linear solvation energy relationships. 23. A comprehensive collection of the solvatochromic parameters, π*, α, and β, and some methods for simplifying the generalized solvatochromic equation. J. Org. Chem. 1983, 48:2877-2887.
38. Kraim K., Khatmi D., Saihi Y., Ferkous F., Brahimi M. Quantitative structure activity relationship for the computational prediction of α-glucosidase inhibitory. Chemom. Intell. Lab. Syst. 2009, 97:118-126.
39. Kubinyi H., Hamprecht F.A., Mietzner T. Three-dimensional quantitative similarity-activity relationships (3D QSiAR) from SEAL similarity matrices. J. Med. Chem. 1998, 41:2553-2564.
40. Zefirov N.S., Palyulin V.A. QSAR for boiling points of "small" sulfides. Are the "high-quality structure-property-activity regressions" the real high quality QSAR models?. J. Chem. Inf. Comput. Sci. 2001, 41:1022-1027.
41. Golbraikh A., Tropsha A. Predictive QSAR modeling based on diversity sampling of experimental datasets for the training and test set selection. J. Comput. Aided Mol. Des. 2002, 5:231-243.
42. Consonni V., Ballabio D., Todeschini R. Evaluation of model predictive ability by external validation techniques. J. Chemom. 2010, 24:194-201.
43. Roy K., Mitra I., Kar S., Ojha P.K., Das R.N., Kabir H. Comparative studies on some metrics for external validation of QSPR models. J. Chem. Inf. Model. 2012, 52:396-408.
44. Ojha P.K., Mitra I., Das R.N., Roy K. Further exploring rm 2 metrics for validation of QSPR models. Chemom. Intell. Lab. Syst. 2011, 107:194-205.
45. Kamlet M.J., Abboud J.-L.M., Taft R.W. The solvatochromic comparison method. 6. The pi* scale of solvent polarities. J. Am. Chem. Soc. 1977, 99:6027-6038.
46. Laurence C., Nicolet P., Dalati M.T., Abboud J.M., Notari R. The empirical treatment of solvent-solute interactions: 15 years of pi*. J. Phys. Chem. 1994, 98:5807-5816.
47. Soukup R.W., Schmid R. Metal complexes as color indicators for solvent parameters. J. Chem. Educ. 1985, 62:459-462.
48. Persson I. Solvation and complex formation in strongly solvating solvents. Pure Appl. Chem. 1986, 58:1153-1161.
49. Taft R.W., Price E., Fox I.R., Lewis I.C., Andersen K.K., Davis G.T. Fluorine nuclear magnetic resonance shielding in p-substituted fluorobenzenes. The influence of structure and solvent on resonance effects. J. Am. Chem. Soc. 1963, 85:3146-3156.
50. Karplus K., Das T.P. Theory of localized contributions to the chemical shift. Application to fluorobenzenes. J. Chem. Phys. 1961, 34:1683.
51. Prosser F., Goodman I. Theory of NMR chemical shifts in conjugated fluorine compounds. J. Chem. Phys. 1963, 38:374.
52. Lauterbur P.C. Magnetic shieldings and the electronic structures of aromatic molecules. Tetrahedron Lett. 1961, 2:274-279.
53. Taft R.W., Price E., Fox I.R., Lewis I.C., Andersen K.K., Davis G.T. Fluorine nuclear magnetic resonance shielding in meta-substituted fluorobenzenes. The effect of solvent on the inductive order. J. Am. Chem. Soc. 1963, 85:709-724.
54. Israelachvili J. Intermolecular and Surface Forces 2011, 291-337. Academic Press, Burlington.
55. Hansen C.M. Hansen Solubility Parameters - A User's Handbook 2007, 1-24. CRC Press, Boca Raton.
56. Bergin S.D., Sun Z.Y., Rickard D., Streich P.V., Hamilton J.P., Coleman J.N. Multicomponent solubility parameters for single-walled carbon nanotube-solvent mixtures. ACS Nano 2009, 3:2340-2350.
57. Topliss J.G., Costello R.J. Chance correlations in structure-activity studies using multiple regression analysis. J. Med. Chem. 1972, 15:1066-1068.
58. Topliss J.G., Edwards R.P. Chance factors in studies of quantitative structure-activity relationships. J. Med. Chem. 1979, 22:1238-1244.
59. Livingstone D.J., Salt D.W. Judging the significance of multiple linear regression models. J. Med. Chem. 2005, 48:661-663.
60. Salt D.W., Ajmani S., Crichton R., Livingstone D.J. An improved approximation to the estimation of the critical F values in best subset regression. J. Chem. Inf. Model. 2007, 47:143-149.
61. Deeb O. Correlation ranking and stepwise regression procedures in principal components artificial neural networks modeling with application to predict toxic activity and human serum albumin binding affinity. Chemom. Intell. Lab. Syst. 2010, 104:181-194.
62. Todeschini R., Consonni V. Molecular Descriptors for Chemoinformatics 2009, vol. I:27-38. Wiley-Vch, Weinheim, 107-110, 259-261, 552-553.
63. Gemperline P. Practical Guide to Chemometrics 2006, 128-129. Taylor & Francis Group, Boca Raton.
64. Brereton R. Chemometrics Data Analysis for the Laboratory and Chemical Plant 2004, 47-53. John Wiley & Sons Ltd., Chichester.
65. Netzeva T.I., Worth A.P., Aldenberg T., Benigni R., Cronin M.T.D., Gramatica P., et al. Current status of methods for defining the applicability domain of (quantitative) structure-activity relationships. ATLA - Alternatives to Laboratory Animals 2005, 33:1-19.
66. Todeschini R., Consonni V., Gramatica P. Chemometrics in QSAR. Comprehensive Chemometrics 2009, vol. 4:158-159. Elsevier, Oxford.