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Experimental design for optimization of peroxide formulation stability and cost
Author(s) -
Blanco Marcel,
Coello Jordi,
Sánchez M. Jesús
Publication year - 2006
Publication title -
journal of surfactants and detergents
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.349
H-Index - 48
eISSN - 1558-9293
pISSN - 1097-3958
DOI - 10.1007/s11743-006-5012-1
Subject(s) - stabilizer (aeronautics) , chemistry , hydrogen peroxide , stability (learning theory) , peroxide , solvent , work (physics) , aqueous solution , central composite design , function (biology) , response surface methodology , chromatography , organic chemistry , thermodynamics , computer science , mechanical engineering , physics , machine learning , engineering , evolutionary biology , biology
Cleaning formulations typically contain, in addition to surfactant, a bleaching agent that is usually hydrogen peroxide. This active agent has the disadvantage that it becomes unstable with time, which necessitates the use of various additives in the formulation to ensure its stability. In this work, a study of the different types of surfactants, chelating agents, radical scavengers, stabilizers, and solvents commonly used in the bleaching industry, was made to identify the mixture that better stabilizes an aqueous solution of hydrogen peroxide. The strategy used starts with a screening step based on a hyper‐Greco‐Latin square design. In subsequent steps, a Box‐Wilson design is used to construct a response surface model to identify the composition ensuring the highest possible stability in the formulation. A desirability function is then obtained that allows the stability of the formulation to be maximized and its cost simultaneously minimized. Such a function is optimized using the Nelder‐Mead algorithm. The stability study was made by heating the mixtures at 60°C for variable periods of time. A mixture containing four of these additives was found to provide the best stability, and the solvent did not have any effect on the stabilization. However, this mixture exceeded the expectations in terms of cost, so the composition was adjusted to obtain the best compromise between stability and cost. As the stabilizer is the more expensive additive, in this optimization step its composition was reduced. In the final formulation, the stabilizer concentration can be reduced by up to 23% with respect to that obtained in the previous step without detracting from stability, thereby saving 18.8%.