Empirical Modeling and Optimization by Active Central Composite Rotatable Design: Brilliant Red HE-3B Dye Biosorption onto Residual Yeast Biomass-Based Biosorbents - Carmen Zaharia; Daniela Suteu (Applied Sciences, 2022)
(1) Introduction: Natural polymers can be successfully used as a matrix to immobilize residual yeast-based biomass in a form that is easy to handle and can be used as biosorbent capable of removing persistent polluting species from different aqueous systems such as reactive azo dyes. (2) Experimental: Two types of new biosorbents were prepared based on residual Saccharomyces pastorianus yeast biomass immobilized in sodium alginate (using two different practice techniques) and studied in the biosorption process of reactive Brilliant Red HE-3B dye using certain experimental planning matrices according to the active central composite rotatable design of 23 order. The experimental data obtained under certain selected working conditions were processed considering the influence of three independent variables (biosorbent concentration—X1, initial dye concentration—X2 and biosorption time—X3) onto the dependent variable (Y = f(X1,X2,X3)) expressing the performance of reactive dye biosorption onto the new prepared biosorbents (i.e., dye removal degree, %). (3) Results: Two mathematical models were proposed for each prepared biosorbent. The maximum dye removal was 52.878% (Y1) when 18 g/L biosorbent 1 (micro-encapsulated form) was applied in 70 mg/L dye-containing solution for at least 8 h, and 75.338% (Y2) for 22.109 g/L biosorbent 2 (immobilized form) in 48.49 mg/L dye-containing solution for at least 8.799 h. (4) Discussion: The optimal values achieved for the two tested biosorbents were compared, and we investigated the possibility of using this residual biomass as a biosorbent for the reactive dye removal, supported by the experimental results with the recommended variation domains of each influencing variable. The results are sufficient to permit performing dye removal higher than 50% (biosorbent 1) or 70% (biosorbent 2), working with more than 18–22 g/L biosorbent after at least 8 h (as an exchange at work). (5) Conclusions: The proposed models are in good agreement with the experimental data and permit the prediction of dye biosorption behavior onto the experimental variation domain of each independent variable.