A new model for predicting boiling points of alkanes

Simon Mukwembi, Farai Nyabadza

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

A general perception among researchers is that boiling points, which is a key property in the optimization of lubricant performance, are difficult to predict successfully using a single-parameter model. In this contribution, we propose a new graph parameter which we call, for lack of better terminology, the conduction of a graph. We exploit the conduction of a graph to develop a single-parameter model for predicting the boiling point of any given alkane. The model was used to predict the boiling points for three sets of test data and predicted with a coefficient of determination, R2=0.7516,0.7898 and 0.6488, respectively. The accuracy of our model compares favourably to the accuracy of experimental data in the literature. Our results have significant implications on the estimation of boiling points of chemical compounds in the absence of experimental data.

Original languageEnglish
Article number24261
JournalScientific Reports
Volume11
Issue number1
DOIs
Publication statusPublished - Dec 2021

ASJC Scopus subject areas

  • Multidisciplinary

Fingerprint

Dive into the research topics of 'A new model for predicting boiling points of alkanes'. Together they form a unique fingerprint.

Cite this