Citation: Yuan Hua, Li Mengyang, Chen Chunni, Peng Xiaoxiao. Study on Quantitative Structure-Property Relationship of the Flash Points of Oxygen-Containing Organic Compounds based on Topological Descriptors[J]. Chemistry, ;2017, 80(4): 385-391. shu

Study on Quantitative Structure-Property Relationship of the Flash Points of Oxygen-Containing Organic Compounds based on Topological Descriptors

Key Laboratory of Theoretical Organic Chemistry and Function Molecule, Ministry of Education, Key Laboratory of QSAR/QSPR of Hunan Provincial University, School of Chemistry and Chemical Engineering, Hunan University of Science and Technology, Xiangtan 411201

Received Date: 27 June 2016
Accepted Date: 19 November 2016

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The flash point is a physical quantity indicating the flammable degree of a compound, and also an important safety index of combustible liquid. This paper analyzed the relationship between flash points and molecular structures of oxygen-containing organic compounds, including alcohols, phenols, ethers, aldehydes, ketones, carboxylic acids and esters. A set of molecular structural descriptors, i. e., the vertex degree-distance index (VDI), odd-even index (OEI), edge degree-distance index (EDI), molecular volume index (MVI), and hydrogen bond indicator (HB) were extracted and calculated. Based on these descriptors and the two-thirds power of the number of vertexes (N^2/3), quantitative structure-property relationship analysis was carried out for the flash points of 81 oxygen-containing organic compounds in the training set. The multiple linear regression model based on N^2/3, VDI, EDI, OEI, MVI and HB was established with the correlation coefficient R=0.9909, the standard deviation s=6.39K, and the average relative deviation ARD=1.60%. The flash points of 20 oxygen-containing organic compounds in the test set were predicted by this model, and the ARD was 1.84%.
- Oxygen-containing compounds,
- Flash point,
- Quantitative structure-property relationship,
- Molecular structural descriptors,
- Multiple linear regression
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