"Multiple response function" » "Multiple response selection", "Multiple response factor"
Publication Date: 2016.
This paper presents a comparison between a multiple response function (MR) proposed for optimization of analyticalstrategies involving multi-element determinations with the desirability function D, which was proposed by Derringerand Suich in 1980. The MR function is established by the average of the sum of the normalized responses for eachanalyte considering the highest value of these. This comparison was performed during the optimization of an spectrometerfor quantification of six elements using inductively coupled plasma optical emission spectrometry (ICP OES). Four instrumentalfactors were studied (auxiliary gas flow rate, plasma gas flow rate, nebulizer gas flow rate and radio frequencypower). A (24) two-level full factorial design and a Box Behnken matrix were developed to evaluate the performance ofthe two multiple response functions. The results found demonstrated great similarity in the interpretations obtained consideringthe effect values of the factors calculated using the two-level full factorial design employing the two multiple responses.Also a Box Behnken design was performed to compare the applicability of the two multiple response functions inquadratic models. The results achieved demonstrated high correlation (0.9998) between the regression coefficients of thetwo models. Also the response surfaces obtained showed great similarity in terms of formats and experimental conditionsfound for the studied factors. Thus, the multiple response (MR) is presented as a simple tool, easy to manipulate, efficientand very helpful for application in analytical procedures involving multi-response. An overview of applications of thisfunction in several multivariate optimization tools as well as in various analytical techniques is presented.
Author affiliation: Novaes, Cleber G.. Universidade Estadual do Sudoeste da Bahia; Brasil. Universidade Federal da Bahia; Brasil
Author affiliation: Ferreira, Sergio L.C.. Universidade Federal da Bahia; Brasil
Author affiliation: Neto, João H. S.. Universidade Estadual do Sudoeste da Bahia; Brasil
Author affiliation: de Santana, Fernanda A.. Universidade Federal da Bahia; Brasil
Author affiliation: Portugal, Lindomar A.. Universidad de las Islas Baleares; España
Author affiliation: Goicoechea, Hector Casimiro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina
Repository: CONICET Digital (CONICET). Consejo Nacional de Investigaciones Científicas y Técnicas