Efficient Numerical Approaches for Solving Nonlinear Models in Gradient Elution Chromatography.

Chromatography is a highly efficient method for separating and quantifying compounds, especially in complex scenarios where purity is critical. Focuses on gradient elution chromatography, aiming to develop a precise numerical method applicable to various chromatographic models. Gradient elution involves gradually increasing the eluent strength during chromatography by altering the mobile phase composition, enabling the separation of challenging mixtures. This tackles a nonlinear equilibrium dispersive model, a complex system of equations. Achieving numerical accuracy and computational efficiency is crucial for obtaining realistic solutions. The research employs a discontinuous Galerkin finite element scheme, well-suited for capturing sharp discontinuities in chromatographic fronts with low computational cost. The results offer valuable insights into the impact of gradient parameters on concentration profiles, benefiting the understanding and optimization of gradient elution chromatography.