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14.6: Additional Resources

  • Page ID
    220787
  • The following set of experiments provide practical examples of the optimization of experimental conditions. Examples include simplex optimization, factorial designs for developing empirical models of response surfaces, and fitting experimental data to theoretical models of the response surface.

    • Amenta, D. S.; Lamb, C. E.; Leary, J. J. “Simplex Optimization of Yield of sec-Butylbenzene in a Friedel-Crafts Alkylation,” J. Chem. Educ. 1979, 56, 557–558.

    • Gozálvez, J. M.; García-Diaz, J. C. “Mixture Design Experiments Applied to the Formulation of Colo- rant Solutions,” J. Chem. Educ. 2006, 83, 647–650.

    • Harvey, D. T.; Byerly, S.; Bowman, A.; Tomlin, J. “Optimization of HPLC and GC Separations Using Response Surfaces,” J. Chem. Educ. 1991, 68, 162–168.

    • Krawcyzk, T.; Shupska, R.; Baj, S. “Applications of Chemiluminescence in the Teaching of Experimental Design,” J. Chem. Educ. 2015, 92, 317–321.

    • Leggett, D. L. “Instrumental Simplex Optimization,” J. Chem. Educ. 1983, 60, 707–710.

    • Oles, P. J. “Fractional Factorial Experimental Design as a Teaching Tool for Quantitative Analysis,” J. Chem. Educ. 1998, 75, 357–359.

    • Palasota, J. A.; Deming, S.N. “Central Composite Experimental Design,” J. Chem. Educ. 1992, 69, 560–561.

    • Sangsila, S.; Labinaz, G.; Poland, J. S.; vanLoon, G. W. “An Experiment on Sequential Simplex Optimization of an Atomic Absorption Analysis Procedure,” J. Chem. Educ. 1989, 66, 351–353.

    • Santos-Delgado, M. J.; Larrea-Tarruella, L. “A Didactic Experience of Statistical Analysis for the De- termination of Glycine in a Nonaqueous Medium using ANOVA and a Computer Program,” J. Chem. Educ. 2004, 81, 97–99.

    • Shavers, C. L.; Parsons, M. L.; Deming, S. N. “Simplex Optimization of Chemical Systems,” J. Chem Educ. 1979, 56, 307–309.

    • Stieg, S. “A Low-Noise Simplex Optimization Experiment,” J. Chem. Educ. 1986, 63, 547–548.

    • Stolzberg, R. J. “Screening and Sequential Experimentation: Simulations and Flame Atomic Absorption Spectrometry Experiments,” J. Chem. Educ. 1997, 74, 216–220.

    • Van Ryswyk, H.; Van Hecke, G. R. “Attaining Optimal Conditions,” J. Chem. Educ. 1991, 66, 878– 882.

    The following texts and articles provide an excellent discussion of optimization methods based on searching algorithms and mathematical modeling use factorial designs, including a discussion of the relevant calculations. A few of these sources discuss other types of experimental designs.

    • Analytical Methods Committee “Experimental design and optimization (1): an introduction to some basic concepts,” AMCTB 24, 2006.

    • Analytical Methods Committee “Experimental design and optimization (2): handling uncontrolled factors,” AMCTB 26, 2006.

    • Analytical Methods Committee “Experimental design and optimization (3): some fractional factorial designs,” AMCTB 36, 2009.

    • Analytical Methods Committee “Experimental design and optimisation (4): Plackett–Burman de- signs,” AMCTB 55, 2013.

    • Bayne, C. K.; Rubin, I. B. Practical Experimental Designs and Optimization Methods for Chemists, VCH Publishers: Deerfield Beach, FL; 1986.

    • Bezerra, M. A.; Santelli, R. E.; Oliveira, E. P.; Villar, L. S.; Escaleira, L. A. “Response surface methodology (RSM) as a tool for optimization in analytical chemistry,” Talanta 2008, 76, 965–977.

    • Box, G. E. P. “Statistical Design in the Study of Analytical Methods,” Analyst 1952, 77, 879–891.

    • Deming, S. N.; Morgan, S. L. Experimental Design: A Chemometric Approach, Elsevier: Amsterdam, 1987.

    • Ferreira, S. L. C.; dos Santos, W. N. L.; Quintella, C. M.; Neto, B. B.; Bosque-Sendra, J. M. “Doehlert Matrix: A Chemometric Tool for Analytical Chemistry—Review,” Talanta 2004, 63, 1061–1067.

    • Ferreira, S. L. C.; Bruns, R. E.; Ferreira, H. S.; Matos, G. D.; David, J. M.; Brandão, G. C.; da Silva, E. G. P.; Portugal, L. A.; dos Reis, P. S.; Souza, A. S.; dos Santos, W. N. L. “Box-Behnken Design: An Alternative for the Optimization of Analytical Methods,” Anal. Chim. Acta 2007, 597, 179–186.

    • Gonzalez, A. G. “Two Level Factorial Experimental Designs Based on Multiple Linear Regression Models: A Tutorial Digest Illustrated by Case Studies,” Anal. Chim. Acta 1998, 360, 227–241.

    • Goupy, J. “What Kind of Experimental Design for Finding and Checking Robustness of Analytical Methods?” Anal. Chim. Acta 2005, 544, 184–190.

    • Hendrix, C. D. “What Every Technologist Should Know About Experimental Design,” Chemtech 1979, 9, 167–174.

    • Hendrix, C. D. “Through the Response Surface with Test Tube and Pipe Wrench,” Chemtech 1980, 10, 488–497.

    • Leardi, R. “Experimental Design: A Tutorial,” Anal. Chim. Acta 2009, 652, 161–172.

    • Liang, Y. “Comparison of Optimization Methods,” Chromatography Review 1985, 12(2), 6–9.

    • Morgan, E. Chemometrics: Experimental Design, John Wiley and Sons: Chichester, 1991.

    • Walters, F. H.; Morgan, S. L.; Parker, L. P., Jr.; Deming, S. N. Sequential Simplex Optimization, CRC Press: Boca Raton, FL, 1991.

    The following texts provide additional information about ANOVA calculations, including discussions of two-way analysis of variance.

    • Graham, R. C. Data Analysis for the Chemical Sciences, VCH Publishers: New York, 1993.

    • Miller, J. C.; Miller, J. N. Statistics for Analytical Chemistry, Ellis Horwood Limited: Chichester, 1988.

    The following resources provide additional information on the validation of analytical methods.

    • Gonzalez, A. G.; Herrador, M. A. “A Practical Guide to Analytical Method Validation, Including Measurement Uncertainty and Accuracy Profiles,” Trends Anal. Chem. 2007, 26, 227–238.

    • Thompson, M.; Ellison, S. L. R.; Wood, R. “Harmonized Guidelines for Single-Laboratory Validation of Analytical Methods,” Pure Appl. Chem. 2002, 74, 835–855.

     

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