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Revista Producción + Limpia

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Browsing Revista Producción + Limpia by Subject "Absorción"

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    Biosólidos de tratamiento de aguas residuales domésticas, como adiciones en la elaboración de ladrillos cerámicos
    (Corporación Universitaria Lasallista, 2017) Fuentes Molina, Natalia; Isenia León, Samir Alfonso; Ascencio Mendoza, José Gregorio
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    Diseño estadístico para la remoción eficiente del colorante rojo 40 sobre tusa de maíz
    (Corporación Universitaria Lasallista, 2012) Moreno, Anderson; Figueroa, Danilo; Hormaza, Angelina
    Introduction. Industrial colored effluents are an evident indicator of water pollution. Small quantities of dye affect, negatively, the appearance of water bodies and dramatically affect water regeneration, affecting the aquatic life. Several physical-chemical and biological methods have been usted to treat colored effluents, with considerable efficiency degrees, but they are expensive and produce more toxic by-products, so there are problems for their use. Adsorption with alternative adsorbents has proved its efficiency to eliminate colorants in solutions. Objetive. Achieving the maximum removal of the red 40 dye on corn cob by the use of a statistical experimental design and characterize the adsorbent material. Materials and methods. The most important variables of the adsorption process were evaluated under a discontinuous system through a factorial design, with the support of the Statgraphics software for its execution and analysis. The remaining concentration of the colorant was determined with the absorbance, by the use of an UV-vis Perkin Elmer Lamba spectrophotometer. Results. A maximum removal of 99% was achieved with the statistical model used, and a good adjustment (R2 equals 98.97%). The pH was the most significant variable in the adsorption of the red 40 dye. Conclusions. Corn cob proved to be an excellent adsorption material and the high removal degree achieved was due to the statistical experimental design, which is more economic and facilitates the analysis of the most important variables involved in the process.