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Abstract
AbstractThis review presents applications of response surface methodology (RSM) when mixture experiments are involved for the optimization in the field of analytical methods development. Several critical issues such as sort of designs, modeling with least squares or artificial neural networks, and multiple response optimization are discussed. The results of a literature survey of the works reported up to 2019 are presented. Finally, an illustrative example providing the necessary information to carry out this kind of work is discussed. A list of the most popular software available to apply RSM is also presented.
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