Low-temperature lithium extraction from α-spodumene with NH4HF2: Modeling and optimization by least squares and artificial neural networks

[Display omitted] •Modeling and optimization of Li extraction by LS and ANN•Li extraction of 96% from α-spodumene at low-temperature (157°C) using NH4HF2•Minimization of the reaction time and fluorinating agent amount•Separation of silicon by-products such as ammonium fluorosilicates•Virtually residue-free process with full use of ore components In this research, an efficient method of lithium extraction from α-spodumene by thermal treatment with NH4HF2 was optimized. Temperature (T), α-spodumene:NH4HF2 molar ratio (m), and reaction time (t) were studied using a two-level univariate strategy. The results were modeled using least squares (LS) and artificial neural networks (ANN) and then compared to obtain a predictive model of the system. Both models showed good concordance with the experimental data (R² of 0.9881 and 0.9957, respectively) and with each other. The ANOVA of the cubic model indicated that T, m, t, and the interactions Tt, T², and T³ were significant. Finally, the system was optimized using response surface methodology to maximize Li extraction and minimize operational parameters. The desirability function predicted an extraction value of 95.48±2.50% for T=156.7°C, m=1:17.5, and t=100.6min. Experimental lithium extractions of 96.45±3.68% were obtained at 157°C using a molar ratio of 1:17.5 for 100min. The products of the thermal treatment were LiF, (NH4)3SiF6·F, (NH4)3AlF6, NH3, and H2O. After a water leaching step, the silicon in the sample was separated, obtaining (NH4)3SiF6·F as a by-product. Finally, the solid products were leached with H2SO4 10% (v/v) to solubilize all lithium.