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Application of design of experiments, response surface methodology and partial least squares regression on nanocomposites synthesis

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Abstract

We present an integral chemometric treatment for characterization and synthesis of low-density poly(ethylene)/organically modified montmorillonite nanocomposites using direct melt processing method, complementing design of experiment (DOE), response surface methodology (RSM) and partial least squares (PLS) regression. A central composite circumscribed DOE was used to study the influence of four processing parameters—concentration of clay (Clay%), concentration of compatibilizer (Comp%), mixing temperature (T mix) and mixing time (t mix)—on six nanocomposites properties: interlayer distance, decomposition temperature, melting temperature, Young’s modulus, loss modulus and storage modulus. PLS-regression was used to simultaneously correlate parameters and responses. RSM was used to explore interactions among parameters and predict nanocomposite properties on the experimental region. The six responses were simultaneously PLS-modeled with R 2 = 0.768 (p ≤ 0.05) being Clay% and Comp% the most important parameters and t mix the least influential. Moreover, significant (p ≤ 0.05) and complex interactions among Clay%, Comp% and t mix were found. A complementary interpretation of score and loading plots, coefficient plots, variable importance plots and response surface plots are explained to show how to find the optimal combination of processing parameters according the desired nanocomposite properties.

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References

  1. Pavlidou S, Papaspyrides CD (2008) A review on polymer-layered silicate nanocomposites. Prog Polym Sci 33:1119–1198

    Article  CAS  Google Scholar 

  2. Golebiewski J, Rozanski A, Dzwonkowski J, Galeski A (2008) Low density polyethylene-montmorillonite nanocomposites for film blowing. Eur Polym J 44:270–286

    Article  CAS  Google Scholar 

  3. Osman MA, Rupp JEP, Suter U (2005) Tensile properties of polyethylene-layered silicate nanocomposites. Polymer 46:1653–1660

    Article  CAS  Google Scholar 

  4. Morawiec J, Pawlak A, Slouf M, Galeski A, Piorkowska E, Krasnikowa N (2005) Preparation and properties of compatibilized LDPE/organo-modified montmorillonite nanocomposites. Eur Polym J 41:1115–1122

    Article  CAS  Google Scholar 

  5. Zhai H, Xu W, Guo H, Zhou Z, Shen S, Song Q (2004) Preparation and characterization of PE and PE-g-MAH/montmorillonite nanocomposites. Eur Polym J 40:2539–2545

    Article  CAS  Google Scholar 

  6. Zhao C, Qin H, Gong F, Feng M, Zhang S, Yang M (2005) Mechanical, thermal and flammability properties of polyethylene/clay nanocomposites. Polym Degrad Stabil 87:183–189

    Article  CAS  Google Scholar 

  7. Zhong Y, Janes D, Zheng Y, Hetzer M, De Kee D (2007) Mechanical and oxygen barrier properties of organoclay-polyethylene nanocomposite films. Polym Eng Sci 47(7):1101–1107

    Article  CAS  Google Scholar 

  8. Pérez MA, Rivas BL, Rodríguez SM, Maldonado A, Venegas C (2010) Polypropylene/clay nanocomposites. Synthesis and characterization. J Chil Chem Soc 55(4):440–444

    Article  Google Scholar 

  9. Paul DR, Robeson LM (2008) Polymer nanotechnology: nanocomposites. Polymer 49:3187–3204

    Article  CAS  Google Scholar 

  10. Sinha-Ray S, Okamoto M (2003) Polymer/layered silicate nanocomposites: a review from preparation to processing. Prog Polym Sci 28:1539–1641

    Article  Google Scholar 

  11. Tjong SC (2006) Structural and mechanical properties of polymer nanocomposites. Mater Sci Eng R 53:73–197

    Article  Google Scholar 

  12. Contreras D, Moreno Y, Salgado Y, Cárdenas G, Baggio R, Peña O, Pivan JY (2007) Synthesis and optimization of experimental variables of a hybrid organic-inorganic compound. New J Chem 31:1751–1754

    Article  CAS  Google Scholar 

  13. Yong V, Hahn HT (2005) Dispersant optimization using design of experiments for SiC/vinyl ester nanocomposites. Nanotechnology 16:354–360

    Article  CAS  Google Scholar 

  14. Box G, Hunter JS, Hunter WG (2005) Statistics for experimenters—design, innovation, and discovery, 2nd edn. Wiley-Interscience, New Jersey

    Google Scholar 

  15. Bruns RE, Scarminio IS, de Barros-Neto B (2006) Statistical design—chemometrics, 1st edn. Elsevier, Amsterdam

    Google Scholar 

  16. Campos-Requena VH, Rivas BL, Pérez MA, Contreras D, Muñoz E (2013) Optimization of processing parameters for the synthesis of low-density polyethylene/organically modified montmorillonite nanocomposites using X-ray diffraction with experimental design. Polym Int 62(4):548–553

    Article  CAS  Google Scholar 

  17. Eriksson L, Johansson E, Kettaneh-World N, Wikström C, World S (2000) Design of experiments: principles and applications, 3rd edn. Umetrics, Stockholm

    Google Scholar 

  18. Barbas JM, Machado AV, Covas JA (2012) In-line near-infrared spectroscopy for the characterization of dispersion in polymer-clay nanocomposites. Polym Test 31(4):527–536

    Article  CAS  Google Scholar 

  19. Brun N, Bourson P, Margueron S (2013) Quantification of rubber in high impact polystyrene by Raman spectroscopy. Comparison of a band fitting method and chemometrics. Vib Spectrosc 67:55–60

    Article  CAS  Google Scholar 

  20. Real BD, Ortiz MC, Sarabia LA (2007) Analysis of interferents by means a D-optimal screening design and calibration using partial least squares regression in the spectrophotometric determination of Cr(VI). Talanta 71:1599–1609

    Article  CAS  Google Scholar 

  21. Dejaegher B, Vander Heyden Y (2011) Experimental designs and their recent advances in set-up, data interpretation, and analytical applications. J Pharm Biomed 56:141–158

    Article  CAS  Google Scholar 

  22. Almeida-Bezerra M, Erthal-Santelli R, Padua-Oliveira E, Silveira-Villar L, Escaleira LA (2008) Response surface methodology (RSM) as a tool for optimization in analytical chemistry. Talanta 76:965–977

    Article  Google Scholar 

  23. Faria R, Duncan JC, Brereton RG (2007) Dynamic mechanical analysis and chemometrics for polymer identification. Polym Test 26(3):402–412

    Article  CAS  Google Scholar 

  24. Sulub Y, DeRudder J (2013) Determination of polymer blends composed of polycarbonate and rubber entities using near-infrared (NIR) spectroscopy and multivariate calibration. Polym Test 32(4):802–809

    Article  CAS  Google Scholar 

  25. Næs T, Isaksson T, Fearn T, Davies T (2002) Multivariate calibration and classification, 1st edn. NIR Publications, Chichester

    Google Scholar 

  26. Wold S, Sjöström M, Eriksson L (2001) PLS-regression: a basic tool of chemometrics. Chemom Intell Lab Syst 58:109–130

    Article  CAS  Google Scholar 

  27. Geladi P, Manley M, Lestander T (2003) Scatter plotting in multivariate data analysis. J Chemom 17:503–511

    Article  CAS  Google Scholar 

  28. Höskuldsson A (1988) PLS regression methods. J Chemom 2:211–228

    Article  Google Scholar 

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Acknowledgments

The authors thank FONDEF (Grant No. DI0i1234), REDOC (MINEDUC Project UCO1202 at U. de Concepción) and CONICYT REGIONAL CIPA (Centro de Investigación de Polímeros Avanzados) R08C1002. Víctor H. Campos-Requena gratefully thanks CONICYT-Chile for its financial support through Doctoral Thesis Support Grant 24110010 and Doctoral Studies in Chile Support Grant 21090205; to Grant MECE2-Chile UCH0601 for Abroad Doctoral Stay financial support; to Heinrich-Hertz-Gesellschaft, D-76131 Karlsruhe and Karlsruher Universitätsgesellschaft e.V., D-76049 Karlsruhe for their financial support; and also thanks to Mónica Uribe from GEA-UdeC.

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Authors and Affiliations

  1. Facultad de Farmacia, Universidad de Concepción, Casilla 160-C, Concepción, Chile

    Víctor H. Campos-Requena

  2. Facultad de Ciencias Químicas, Universidad de Concepción, Casilla 160-C, Concepción, Chile

    Víctor H. Campos-Requena, Bernabé L. Rivas & Mónica A. Pérez

  3. Institute for Chemical Technology and Polymer Chemistry, Karlsruhe Institute of Technology (KIT), Engesserstraβe 18, 76128, Karlsruhe, Germany

    Manfred Wilhelm

Authors
  1. Víctor H. Campos-Requena
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  2. Bernabé L. Rivas
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  3. Mónica A. Pérez
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  4. Manfred Wilhelm
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Correspondence to Bernabé L. Rivas.

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Campos-Requena, V.H., Rivas, B.L., Pérez, M.A. et al. Application of design of experiments, response surface methodology and partial least squares regression on nanocomposites synthesis. Polym. Bull. 71, 1961–1982 (2014). https://doi.org/10.1007/s00289-014-1166-6

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  • DOI: https://doi.org/10.1007/s00289-014-1166-6

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