Predicting boiling points of aliphatic alcohols through multivariate image analysis applied to quantitative structure-property relationships

Mohammad Goodarzi, Matheus P. Freitas

Research output: Contribution to journalArticle

32 Citations (Scopus)

Abstract

The boiling points of a set of 58 aliphatic alcohols have been modeled through an image-based approach, in which descriptors are pixels (binaries) of 2D chemical structures. While some simple descriptors, such as molecular weight, do not account for some structural influences (e.g., in chain and position isomerism) on the studied property, the MIA-QSPR (multivariate image analysis applied to quantitative structure-property relationship) method, coupled to multilinear partial least-squares regression, correlated the chemical structures with the corresponding boiling points satisfactorily well.

Original languageEnglish (US)
Pages (from-to)11263-11265
Number of pages3
JournalJournal of Physical Chemistry A
Volume112
Issue number44
DOIs
StatePublished - Nov 6 2008

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Boiling point
image analysis
boiling
Image analysis
alcohols
Alcohols
regression analysis
molecular weight
Pixels
Molecular weight
pixels

ASJC Scopus subject areas

  • Physical and Theoretical Chemistry

Cite this

Predicting boiling points of aliphatic alcohols through multivariate image analysis applied to quantitative structure-property relationships. / Goodarzi, Mohammad; Freitas, Matheus P.

In: Journal of Physical Chemistry A, Vol. 112, No. 44, 06.11.2008, p. 11263-11265.

Research output: Contribution to journalArticle

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