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

Andrey A. Toropov, P. Ganga Raju Achary, Alla P. Toropova

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)107-110
Number of pages4
JournalChemical Physics Letters
Volume660
DOIs
Publication statusPublished - Sep 1 2016

Keywords

  • CORAL software
  • Monte Carlo method
  • QFPR
  • QSPR/QSAR
  • quasi-SMILES

ASJC Scopus subject areas

  • Physics and Astronomy(all)
  • Physical and Theoretical Chemistry

Fingerprint

Dive into the research topics of 'Quasi-SMILES and nano-QFPR: The predictive model for zeta potentials of metal oxide nanoparticles'. Together they form a unique fingerprint.

Cite this