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Statistical Analysis and Optimization of the Brilliant Red HE-3B Dye Biosorption onto a Biosorbent Based on Residual Biomass
Using various techniques, natural polymers can be successfully used as a matrix to immobilize a residual microbial biomass in a form that is easy to handle, namely biosorbents, and which is capable of retaining chemical species from polluted aqueous media. The biosorption process of reactive Brillia...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9607323/ https://www.ncbi.nlm.nih.gov/pubmed/36295248 http://dx.doi.org/10.3390/ma15207180 |
Sumario: | Using various techniques, natural polymers can be successfully used as a matrix to immobilize a residual microbial biomass in a form that is easy to handle, namely biosorbents, and which is capable of retaining chemical species from polluted aqueous media. The biosorption process of reactive Brilliant Red HE-3B dye on a new type of biosorbent, based on a residual microbial biomass of Saccharomyces pastorianus immobilized in sodium alginate, was studied using mathematical modeling of experimental data obtained under certain conditions. Different methods, such as computer-assisted statistical analysis, were applied, considering all independent and dependent variables involved in the reactive dye biosorption process. The optimal values achieved were compared, and the experimental data supported the possibility of using the immobilized residual biomass as a biosorbent for the studied reference dye. The results were sufficient to perform dye removals higher than 70–85% in an aqueous solution containing around 45–50 mg/L of reactive dye, and working with more than 20–22 g/L of prepared immobilized microbial biosorbent for more than 9.5–10 h. Furthermore, the proposed models agreed with the experimental data and permitted the prediction of the dye biosorption behavior in the experimental variation field of each independent variable. |
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