Application of the monte carlo method to prediction of dispersibility of graphene invarious solvents

A. P. Toropova, A. A. Toropov, J. B. Veselinovic, A. M. Vesélinovic, E. Benfenati, D. Leszczynska, J. Leszczynski

Research output: Contribution to journalArticlepeer-review

Abstract

The dispersibility of graphene ismodeled as amathematical function of themolecular structure of solvent represented by simplified molecular input-line entry systems (SMILES) together with the graph of atomic orbitals (GAO). TheGAOismolecular graph where atomic orbitals e.g. 1s1, 2p4, 3d7 etc., are vertexes of the graph instead of the chemical elements used as the graph vertexes in the traditionally used molecular graph (hydrogen suppressed molecular graph or hydrogen filled molecular graph). The optimal descriptors calculated with theMonte Carlomethodwere used to build up one variable correlations “descriptor- dispersibility”. The CORAL software is used as a tool to build up themodel. Based on the results of calculations the structural features which are promoters of increase or those which are promoters of decrease of the dispersibility are detected and discussed. The predictive potential of the used approach is checked up with three random and non identical splits of available data into the training, calibration, and validation (invisible during building up the model) sets. The statistics for external validation sets are the following: n=11, r2=0.6379, s=0.392 (split 1); n=8, r2=0.7308, s=0.378 (split 2); and n=5, r2=0.7797, s=0.504 (split 3).

Original languageEnglish
Pages (from-to)1211-1216
Number of pages6
JournalInternational Journal of Environmental Research
Volume9
Issue number4
Publication statusPublished - 2015

Keywords

  • CORAL software
  • Dispersibility
  • Graphene
  • Monte carlo method
  • QSPR

ASJC Scopus subject areas

  • Environmental Science(all)

Fingerprint Dive into the research topics of 'Application of the monte carlo method to prediction of dispersibility of graphene invarious solvents'. Together they form a unique fingerprint.

Cite this