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Prediction of Critical Temperature and Pressure of Hydrocarbons Using Simple Molecular Properties

Authors: Kamal I. Al-Malah;

Prediction of Critical Temperature and Pressure of Hydrocarbons Using Simple Molecular Properties

Abstract

Four hundred and seventy (470) hydrocarbons (CnHm) were utilized to fit their critical temperature (Tc) and critical pressure (Pc) as functions of molecular weight and carbon atomic fraction. The proposed model is of the form: Tc=a*(Cfrac)b*(MW)c and Pc= a*(Cfrac)1/3+b*(MW)1/3+c where a, b, and c are the non-linear regressed parameters for the given model; Cfrac is the carbon atomic fraction in a molecule, which is equal to n/(n+m) for a hydrocarbon compound; and MW is the molecular weight, which is calculated as (12n + m). The model was found to predict both Tc and Pc with an adequate accuracy, manifested via the associated percent relative error (PRE) of the curve-fitted Tc and Pc. Out of the examined 470 hydrocarbons, low MW compounds were found to have PRE values higher than 10% for the predicted Tc values. On the other hand, for Pc prediction, higher PRE values were found for higher molecular weight compounds, with C26 and above. Although the proposed model does not strictly differentiate among isomers having the same molecular weight and chemical formula, nevertheless, the difference in Tc and Pc among isomers is not significant to be picked up by a simple, straight forward model. A more rigorous model will work hard to offset such small differences in Tc and Pc among isomers, nevertheless, at the expense of model simplicity.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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