Application of Box-Behnken Design to Determine the Optimal Conditions of Reductive Leaching of MnO2 from Manganese Mine Tailings

Abstract

Understanding the mechanism that governs the leaching process is of major importance to optimize the various factors involved in the reaction; this article is devoted to this subject. The application of leaching process to extracting Mn from a manganese mine tailings was investigated using a software based design of experiments. The Box-Behnken experimental design was used to provide data for modeling and the variables of model were potassium oxalate concentration, solid-to-liquid ratio and sulphuric acid concentration. The recoveries of Mn are selected as response of design. The optimum condition under which the Mn recoveries are the highest is determined using statistical analysis and analysis of variance. A quadratic model with good adherence to the experimental data in the domain analyzed was developed, which was used to plot the response surface curves and to perform process optimization. The results showed that Mn recovery was 80 % under the optimum conditions: a ratio S/L = 50-70 (g L -1 ) approximately; also, sulfuric acid concentration is 1.1-1.3 M and oxalate concentration in range 0.35-0.45 M, time and temperature of the process were 30 min and 25°C, respectively. The methodology employed allowed to evaluate and identify the effects and interactions of the considered variables with statistical meaning in the process response, i.e., the highest recovery of Mn after 30 min of reaction.

The optimization of fermentation conditions for Pichia pastoris GS115 producing recombinant xylanase

“…According to the previous Plackett — Burman screening test, the optimal conditions of the inoculum size, maize meal, and histidine were determined by the Box–Behnken design. A three‐factor and three‐level second‐order regression of the Box–Behnken design consisting of 17 experimental runs was employed including five replicates at the center point (Table ).…”

“…A lack of fit was found to be nonsignificant ( p = 0.0736), indicating that the model equation was sufficient to predict xylanase activity under any combination of the variables. The p ‐value was a tool used to check the significance of each coefficient, and the smaller the p ‐value, the more significant the corresponding coefficient is . Figure 2A–C shows response surface plots the effect of the selected parameters.…”

“…The Box–Behnken design was used in the Design Expert 7.0 software to evaluate the three factors. Each of these three factors had three coded levels consisting of 17 experimental runs for analyzing the experimental data, including five replicates at the center point (Table ).…”

Influence of Carbon Nanofibers on the Shear Strength and Comparing Cohesion of Direct Shear Test and AFM

“…The main benefits of this design is that it has the potential to minimize the number of runs and can be utilized for more than one factors in one process. −1 (lower), 0 (medial) and +1 (higher) should be set as the three levels of the factors, in order to improve the Box-Behnken design's performance [32]. The characteristic of the Box-Behnken design that sets it apart from other surface designs is such that it has higher efficiency where the design efficiency of one experiment is taken as the number of coefficients in the estimated model divided by the number of experiments [32].…”

Optimization of textile azo dye degradation by electrochemical oxidation using Box-Behnken Design

“…The main selected factors were current density (X1), initial pH (X2) and electrolysis time (X3). Box-Behnken design requires an experiment number according to N = k 2 + k + cp, where (k) is the factor number and (cp) is the replicate number of the central point 25 .…”