Position Group Contribution Method for Predicting the Normal Boiling Point of Organic Compounds

王强; 马沛生; 王昶; 夏淑倩

doi:10.1016/S1004-9541(08)60202-5

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Position Group Contribution Method for Predicting the Normal Boiling Point of Organic Compounds

Updated：2026-01-06

- Position Group Contribution Method for Predicting the Normal Boiling Point of Organic Compounds
- Chinese Journal of Chemical Engineering Vol. 17, Issue 2, Pages: 254-258(2009)
- Affiliations：
  
  1. School of Material Science and Chemical Engineering, Tianjin University of Science and Technology,Tianjin,China,300457
  2. School of Chemical Engineering, Tianjin University,Tianjin,China,300072
- Author bio：
- Funds：
- DOI：10.1016/S1004-9541(08)60202-5
  CLC：
- Published：2009
- Accepted：
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WANG Qiang, MA Peisheng, WANG Chang, XIA Shuqian. Position Group Contribution Method for Predicting the Normal Boiling Point of Organic Compounds[J]. , 2009, 17(2): 254-258.
DOI：

WANG Qiang, MA Peisheng, WANG Chang, XIA Shuqian. Position Group Contribution Method for Predicting the Normal Boiling Point of Organic Compounds[J]. , 2009, 17(2): 254-258. DOI： 10.1016/S1004-9541(08)60202-5.

摘要

Abstract

A new position group contribution model is proposed for the estimation of normal boiling data of organic compounds involving a carbon chain from C

to C

.The characteristic of this method is the use of position distribution function.It could distinguish most of isomers that include cis-or trans-structure from organic compounds.Contributions for hydrocarbons and hydrocarbon derivatives containing oxygen

nitrogen

chlorine

bromine and sulfur

are given.Compared with the predictions

results made use of the most common existing group contribution methods

the overall average absolute difference of boiling point predictions of 417 organic compounds is 4.2 K;and the average absolute percent derivation is 1.0%

which is compared with 12.3 K and 3.2% with the method of Joback

12.1 K and 3.1% with the method of Constantinou-Gani.This new position contribution groups method is not only much more accurate but also has the advantages of simplicity and stability.

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