The study of rangescaling transformation of nanoparticle compounds on thin films of goldcentered monolayer protected nanoparticles by molecular modeling

A quantitative structure–retention relation (QSRR) study was conducted on the rangescaling transformation (Xa) of the nanoparticle compounds which obtained by comprehensive twodimensional gas chromatography (GC×GC) stationary phases consisting of thin films of the goldcentered monolayer protected nanoparticles (MPNs) system. The genetic algorithm was used as descriptor selection and model development method. Modeling of the relationship between the selected molecular descriptors and the retention time was achieved by linear (partial least square; PLS) and nonlinear (LevenbergMarquardt artificial neural network; LM ANN) methods. Linear and nonlinear methods resulted in an accurate prediction whereas more accurate results were obtained by LM ANN model.