|About this Abstract
||2021 TMS Annual Meeting & Exhibition
||Materials Processing Fundamentals
||Liquid-liquid Extraction Thermodynamic Parameter Estimator (LLEPE) for Multicomponent Separation Systems
||Titus Quah, Chukwunwike Iloeje
|On-Site Speaker (Planned)
Gibbs Energy Minimization is a powerful tool for modeling liquid-liquid extraction (LLE) in multicomponent systems, but requires key thermodynamic parameters that are often unavailable for several applications involving critical and rare earth material separations. Our earlier work demonstrated an approach for estimating these properties via regression to equilibrium isotherm data, but identified limitations regarding applicability to higher concentration systems, sensitivity to experimental data, and ease of implementation. To extend the accessibility and applicability of Gibbs Energy Minimization for modeling LLE, this study presents LLEPE, an open-source Python package for estimating thermodynamic parameters. LLEPE extends parameter estimation to include aqueous-phase Pitzer coefficients that capture the effects of ionic interactions, and offers analysis and visualization tools that assess experimental data quality and prediction model performance. The study discusses LLEPE’s approach, and presents a case study highlighting its applicability to rare earth metal solvent extraction.
||Machine Learning, Modeling and Simulation, Extraction and Processing