Improved model for fullerene C60 solubility in organic solvents based on quantum-chemical and topological descriptors

Tetyana Petrova, Bakhtiyor F. Rasulev, Andrey A. Toropov, Danuta Leszczynska, Jerzy Leszczynski

Research output: Contribution to journalArticle

42 Citations (Scopus)

Abstract

Fullerenes are sparingly soluble in many solvents. The dependence of fullerene's solubility on molecular structure of the solvent must be understood in order to manage efficiently this class of compounds. To find such dependency ab initio quantum-chemical calculations in combination with quantitative structure-property relationship (QSPR) tool were used to model the solubility of fullerene C60 in 122 organic solvents. A genetic algorithm and multiple regression analysis (GA-MLRA) were applied to generate correlation models. The best performance is accomplished by the four-variable MLRA model with prediction coefficient r test 2 ≥ 0.903. This study reveals a correlation of highest occupied molecular orbital energy (HOMO), certain heteroatom fragments, and geometrical parameters with solubility. Several other important parameters of solvents that affect the C60 solubility have been also evaluated by the QSPR analysis. The employed GA-MLRA approach enhanced by application of quantum-chemical calculations yields reliable results, allowing one to build simple, interpretable models that can be used for predictions of C60 solubility in various organic solvents.

Original languageEnglish
Pages (from-to)3235-3247
Number of pages13
JournalJournal of Nanoparticle Research
Volume13
Issue number8
DOIs
Publication statusPublished - Aug 2011

Fingerprint

Fullerenes
Solubility
Organic solvents
Descriptors
fullerenes
solubility
Multiple Regression
Regression Analysis
Regression analysis
genetic algorithms
regression analysis
Genetic algorithms
Genetic Algorithm
Model
Prediction
Molecular orbitals
predictions
Molecular structure
molecular orbitals
Fragment

Keywords

  • C60
  • DFT
  • Fullerene
  • Modeling and simulation
  • Predictive method
  • QSPR
  • Quantum-chemical descriptors
  • Solubility

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Condensed Matter Physics
  • Modelling and Simulation
  • Chemistry(all)
  • Materials Science(all)
  • Bioengineering

Cite this

Improved model for fullerene C60 solubility in organic solvents based on quantum-chemical and topological descriptors. / Petrova, Tetyana; Rasulev, Bakhtiyor F.; Toropov, Andrey A.; Leszczynska, Danuta; Leszczynski, Jerzy.

In: Journal of Nanoparticle Research, Vol. 13, No. 8, 08.2011, p. 3235-3247.

Research output: Contribution to journalArticle

Petrova, Tetyana ; Rasulev, Bakhtiyor F. ; Toropov, Andrey A. ; Leszczynska, Danuta ; Leszczynski, Jerzy. / Improved model for fullerene C60 solubility in organic solvents based on quantum-chemical and topological descriptors. In: Journal of Nanoparticle Research. 2011 ; Vol. 13, No. 8. pp. 3235-3247.
@article{3669688805c046b18a808f3ea201b0f5,
title = "Improved model for fullerene C60 solubility in organic solvents based on quantum-chemical and topological descriptors",
abstract = "Fullerenes are sparingly soluble in many solvents. The dependence of fullerene's solubility on molecular structure of the solvent must be understood in order to manage efficiently this class of compounds. To find such dependency ab initio quantum-chemical calculations in combination with quantitative structure-property relationship (QSPR) tool were used to model the solubility of fullerene C60 in 122 organic solvents. A genetic algorithm and multiple regression analysis (GA-MLRA) were applied to generate correlation models. The best performance is accomplished by the four-variable MLRA model with prediction coefficient r test 2 ≥ 0.903. This study reveals a correlation of highest occupied molecular orbital energy (HOMO), certain heteroatom fragments, and geometrical parameters with solubility. Several other important parameters of solvents that affect the C60 solubility have been also evaluated by the QSPR analysis. The employed GA-MLRA approach enhanced by application of quantum-chemical calculations yields reliable results, allowing one to build simple, interpretable models that can be used for predictions of C60 solubility in various organic solvents.",
keywords = "C60, DFT, Fullerene, Modeling and simulation, Predictive method, QSPR, Quantum-chemical descriptors, Solubility",
author = "Tetyana Petrova and Rasulev, {Bakhtiyor F.} and Toropov, {Andrey A.} and Danuta Leszczynska and Jerzy Leszczynski",
year = "2011",
month = "8",
doi = "10.1007/s11051-011-0238-x",
language = "English",
volume = "13",
pages = "3235--3247",
journal = "Journal of Nanoparticle Research",
issn = "1388-0764",
publisher = "Springer Netherlands",
number = "8",

}

TY - JOUR

T1 - Improved model for fullerene C60 solubility in organic solvents based on quantum-chemical and topological descriptors

AU - Petrova, Tetyana

AU - Rasulev, Bakhtiyor F.

AU - Toropov, Andrey A.

AU - Leszczynska, Danuta

AU - Leszczynski, Jerzy

PY - 2011/8

Y1 - 2011/8

N2 - Fullerenes are sparingly soluble in many solvents. The dependence of fullerene's solubility on molecular structure of the solvent must be understood in order to manage efficiently this class of compounds. To find such dependency ab initio quantum-chemical calculations in combination with quantitative structure-property relationship (QSPR) tool were used to model the solubility of fullerene C60 in 122 organic solvents. A genetic algorithm and multiple regression analysis (GA-MLRA) were applied to generate correlation models. The best performance is accomplished by the four-variable MLRA model with prediction coefficient r test 2 ≥ 0.903. This study reveals a correlation of highest occupied molecular orbital energy (HOMO), certain heteroatom fragments, and geometrical parameters with solubility. Several other important parameters of solvents that affect the C60 solubility have been also evaluated by the QSPR analysis. The employed GA-MLRA approach enhanced by application of quantum-chemical calculations yields reliable results, allowing one to build simple, interpretable models that can be used for predictions of C60 solubility in various organic solvents.

AB - Fullerenes are sparingly soluble in many solvents. The dependence of fullerene's solubility on molecular structure of the solvent must be understood in order to manage efficiently this class of compounds. To find such dependency ab initio quantum-chemical calculations in combination with quantitative structure-property relationship (QSPR) tool were used to model the solubility of fullerene C60 in 122 organic solvents. A genetic algorithm and multiple regression analysis (GA-MLRA) were applied to generate correlation models. The best performance is accomplished by the four-variable MLRA model with prediction coefficient r test 2 ≥ 0.903. This study reveals a correlation of highest occupied molecular orbital energy (HOMO), certain heteroatom fragments, and geometrical parameters with solubility. Several other important parameters of solvents that affect the C60 solubility have been also evaluated by the QSPR analysis. The employed GA-MLRA approach enhanced by application of quantum-chemical calculations yields reliable results, allowing one to build simple, interpretable models that can be used for predictions of C60 solubility in various organic solvents.

KW - C60

KW - DFT

KW - Fullerene

KW - Modeling and simulation

KW - Predictive method

KW - QSPR

KW - Quantum-chemical descriptors

KW - Solubility

UR - http://www.scopus.com/inward/record.url?scp=80051588636&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=80051588636&partnerID=8YFLogxK

U2 - 10.1007/s11051-011-0238-x

DO - 10.1007/s11051-011-0238-x

M3 - Article

AN - SCOPUS:80051588636

VL - 13

SP - 3235

EP - 3247

JO - Journal of Nanoparticle Research

JF - Journal of Nanoparticle Research

SN - 1388-0764

IS - 8

ER -