Quasi-SMILES and nano-QFPR: The predictive model for zeta potentials of metal oxide nanoparticles

Building up of the predictive quantitative structure–property/activity relationships (QSPRs/QSARs) for nanomaterials usually are impossible owing to the complexity of the molecular architecture of the nanomaterials. Simplified molecular input-line entry system (SMILES) is a tool to represent the molecular architecture of “traditional” molecules for “traditional” QSPR/QSAR. The quasi-SMILES is a tool to represent features (conditions and circumstances), which accompany the behavior of nanomaterials. Having, the training set and validation set, so-called quantitative feature–property relationships (QFPRs), based on the quasi-SMILES, one can build up model for zeta potentials of metal oxide nanoparticles for situations characterized by different features.