Monte Carlo model of nonlinear chromatography.

A stochastic approach to the nonlinear chromatography theory, based on the Monte Carlo simulation method, is presented. A computer program, acting as a "virtual chromatograph" and performing a discrete event simulation, is described. Such a program allows one to choose the column type, operating conditions, sample composition, injection method, mobile-phase dispersion model, and stationary-phase sorption-desorption kinetics. Nonlinearity is accounted for by continuously monitoring and updating both the column and the solute status and by moving individual molecules step by step along the column according to specific random modes. The program has been validated through a series of statistical tests and comparing the results with the well-known achievements of the classical stochastic theory. A first application is presented, referred to a real case benzene elution on a gas solid capillary column, where the Langmuir adsorption isotherm is assumed. The effect of both the sorption modes and the site capacity are investigated. Possible applications to investigate open problems in several fields of separation science are emphasized. In addition, several specific points such as the down-scaling of a real case and the correspondence of specific adsorption dynamics with the equilibrium Langmuir isotherm are described.