文摘
A new method for estimating the thermodynamic parameters of 螖H(T0), 螖S(T0), and 螖CP for use in thermodynamic modeling of GC脳GC separations has been developed. The method is an alternative to the traditional isothermal separations required to fit a three-parameter thermodynamic model to retention data. Herein, a non-linear optimization technique is used to estimate the parameters from a series of temperature-programmed separations using the Nelder-Mead simplex algorithm. With this method, the time required to obtain estimates of thermodynamic parameters a series of analytes is significantly reduced. This new method allows for precise predictions of retention time with the average error being only 0.2 s for 1D separations. Predictions for GC 脳 GC separations were also in agreement with experimental measurements; having an average relative error of 0.37% for 1tr and 2.1% for 2tr.