Reactive Crystallization Process of Lithium Carbonate

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Reactive Crystallization Process of Lithium Carbonate ( reactive-crystallization-process-lithium-carbonate )

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Processes 2019, 7, 248 11 of 16 Table 6. Cont. Feeding Rate Concentration Stirring Speed rpm 300.00 500.00 300.00 400.00 400.00 300.00 500.00 400.00 500.00 400.00 300.00 500.00 500.00 400.00 400.00 400.00 500.00 300.00 400.00 600.00 Yield % 71.43 90.91 78.35 83.05 88.03 80.36 79.15 87.73 80.71 90.42 72.91 87.83 72.07 87.54 86.87 88.46 78.70 85.50 89.71 87.36 D [4,3] μm 140.00 90.70 135.00 90.60 108.00 134.00 110.00 101.00 104.00 93.10 131.00 92.50 109.00 92.60 98.70 96.80 113.00 122.00 96.20 91.50 Run 11 40.00 12 60.00 13 60.00 14 50.00 15 50.00 16 60.00 17 60.00 18 50.00 19 60.00 20 50.00 21 40.00 22 40.00 23 40.00 24 50.00 25 50.00 26 50.00 27 60.00 28 40.00 29 50.00 30 50.00 2.00 1.75 4.00 2.25 4.00 1.75 3.00 2.50 3.00 2.00 2.00 2.25 2.00 1.75 3.00 2.00 2.00 2.25 3.00 2.00 4.00 1.75 4.00 2.25 2.00 1.75 5.00 2.00 1.00 2.00 3.00 2.00 4.00 1.75 2.00 2.25 3.00 2.00 3.00 2.00 Temperature ◦C mL/min mol/L 3.2.2. Model Fitting and ANOVA Analysis The experimental data was used to develop a second-order polynomial model which can be written as: kkkk Y = β0 +􏲥βi ×Ai +􏲥􏲥βij ×Ai ×Aj +􏲥βii ×Ai2 +ε (20) i=1 i=1 j=1 i=1 in which β0 is the intercept, βi, βij, βii are first-order, interactive, and second-order effects, respectively, i and j represent the number of k factors, and ε is the residual error [27]. This method is able to evaluate interaction effects and pure quadratic effects, and is considered to be the most efficient evaluation method that can improve the quality of data. ANOVA was used to determine the significance of each term in the equation and estimate the goodness of fitting quality. In the results of this ANOVA analysis the p-values could be used to check the significance of each term. Specifically, values of “probability (p) > F” less than 0.05, 0.01, and 0.001 indicate that the model terms are significant, highly significant, and remarkably significant, respectively, while values greater than 0.05 indicate that the model terms are not significant [28]. The results of ANOVA for the quadratic model of the yield are shown in Table 7. ANOVA revealed that the model was highly significant (p < 0.01) for the yield of Li2CO3 product, indicating that the developed model was reliable. As can be seen from Table 7, significant linear A, highly significant quadratic A2 and C2, and remarkably significant linear C effects on yield were shown by the ANOVA results, while for the other factors, the p-values were greater than 0.05, indicating that these factors were not significant. Based on the regression coefficient (β) values, solution concentration was revealed to be a major effect, followed by temperature, feeding rate, and stirring speed. The yield of the Li2CO3 product can be expressed by the following second order polynomial equation: R(Yield) = 88.82 + 2.19a + 1.21B + 3.85C + 0.092D + 0.76AB − 1.84AC + 0.38AD + 1.60BC − 0.064BD − 0.11CD − 2.54A2 − 0.99B2 − 2.47C2 − 1.08D2 (21)

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