Share This Article:

Mauro: A Novel Strategy for Optimizing Mixture Properties

Abstract Full-Text HTML Download Download as PDF (Size:255KB) PP. 1260-1264
DOI: 10.4236/am.2012.330182    3,518 Downloads   5,356 Views   Citations

ABSTRACT

The paper illustrates an innovative procedure for experimental design in mixture analysis. It relies on D-optimal designs performed on the combinatorial explosion of five levels of components composition, keeping in mind the requirements of Central Composite Designs. The final response surface model is obtained by the formerly developed CARSO method.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

S. Clementi, M. Fernandi, M. Baroni, D. Decastri, G. Randazzo and F. Scialpi, "Mauro: A Novel Strategy for Optimizing Mixture Properties," Applied Mathematics, Vol. 3 No. 10A, 2012, pp. 1260-1264. doi: 10.4236/am.2012.330182.

References

[1] G. E. Box, W. G. Hunter and J. S. Hunter, “Statistics for Experimenters,” Wiley, New York, 1978.
[2] MODDE: www.umetrics.com
[3] S. Clementi, G. Cruciani, G. Curti and B. Skagerberg, “PLS Response Surface Optimization: The CARSO Procedure,” Journal of Chemometrics, Vol. 3, No. 3, 1989, pp. 499-509. doi:10.1002/cem.1180030307
[4] M. Baroni, S. Clementi, G. Cruciani, N. Kettaneh-Wold and S. Wold, “D Optimal Designs in QSAR,” Quantitative Structure-Activity Relationships, Vol. 12, No. 3, 1993, pp. 225-231. doi:10.1002/qsar.19930120302
[5] G. Cruciani, S. Clementi, D. Pitea, M. Lasagni and R. Todeschini, “A Chemometric Approach for Evaluating the Efficiency of a Pilot Plant for MSW Combustion,” Chemosphere, Vol. 23, No. 8-10, 1991, pp. 1407-1416. doi:10.1016/0045-6535(91)90165-A
[6] M. Baroni, G. Costantino, G. Cruciani, D. Riganelli, R. Valigi and S. Clementi. “Generating Optimal Linear PLS Estimations (GOLPE): An Advanced Chemometric Tool for Handling 3D QSAR Problems,” Quantitative Structure-Activity Relationships, Vol. 12, No. 1, 1993, pp. 9-20. doi:10.1002/qsar.19930120103
[7] M. Bertuccioli, S. Clementi, G. Cruciani, G. Giulietti and I. Rosi, “Food Quality Optimization,” Food quality and preference, Vol. 2, No. 1, 1990, pp.1-12. doi:10.1016/0950-3293(90)90025-P
[8] S. Clementi, G. Cruciani, M. Pastor and T. Lundstedt, “Series Design in Synthetic Chemistry,” In: F. Gualtieri, Ed., New Trends in Synthetic Medicinal Chemistry, Vol. 7, Wiley-VCH, Weinheim, 2000, pp. 17-37. doi:10.1002/9783527613403.ch2
[9] M. Baroni, P. Benedetti, S. Fraternale, F. Scialpi, P. Vix and S. Clementi, “The CARSO Procedure in Process Optimization,” Journal of Chemometrics, Vol. 17, No. 1, 2003, pp. 9-15. doi:10.1002/cem.772
[10] H. Wold, “Nonlinear estimation by Iterative Least Squares Procedures,” In: F. N. David and J. Neyman, Eds., Research Papers in Statistics, Festschrift for J. Neyman, Wiley, London, New York, 1966.
[11] S. Wold, C. Albano, W. J. Dunn, U. Edlund, K. Esbensen, P. Geladi, S. Hellberg, E. Johansson, W. Lindberg and M. Sj?str?m, “Multivariate Data Analysis in Chemistry,” In: B. R. Kowalski, Ed., Chemometrics, Reidel, Dordrecht, 1984, pp. 17-95
[12] www.miasrl.com.

  
comments powered by Disqus

Copyright © 2018 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.