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[摘要]：Previous studies demonstrated that quantitative structure retention relationships (QSRR) combined with the linear solvent strength (LSS) model allow for prediction of gradient reversed phase high performance liquid chromatography (HPLC) retention time for any analyte of a known molecular structure under defined HPLC conditions. The QSRR model derived at the selected gradient time was tested at the same gradient time. Presently, in the first step, experimental retention data for model sets of just 5 analytes were used to derive appropriate QSRR models at two gradient times. Additionally, a new molecular modeling approach based on a more accurate ab initio method was here proposed. Those QSRR models were used to further predict gradient retention times for sets of 16 test analytes belonging to polynuclear aromatic hydrocarbons (PAHs), at two selected gradient times. Then, applying linear solvent strength (LSS) theory, only predicted retention times for PAHs were used to find the optimal gradient conditions to separate them. Satisfactory predictions of gradient retention times for PAHs were obtained. Contrary to the previous achievements, the proposed QSRR provides the chance to predict retention of PAHs with the appropriate selectivity achieving the same sequence of analytes eluted in the experiment and during the simulation performed on the computer screen. |
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