Predicting Flash Point of Organosilicon Compounds Using Quantitative Structure Activity Relationship Approach
The flash point (FP) of a compound is the primary property used in the assessment of fire hazards for flammable liquids and is amongst the crucial information that people handling flammable liquids must possess as far as industrial safety is concerned. In this work, the FPs of 236 organosilicon comp...
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| Language: | English |
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Wiley
2014-01-01
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| Series: | Journal of Chemistry |
| Online Access: | http://dx.doi.org/10.1155/2014/482341 |
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| author | Chen-Peng Chen Chan-Cheng Chen Hsu-Fang Chen |
| author_facet | Chen-Peng Chen Chan-Cheng Chen Hsu-Fang Chen |
| author_sort | Chen-Peng Chen |
| collection | DOAJ |
| description | The flash point (FP) of a compound is the primary property used in the assessment of fire hazards for flammable liquids and is amongst the crucial information that people handling flammable liquids must possess as far as industrial safety is concerned. In this work, the FPs of 236 organosilicon compounds were collected and used to construct a quantitative structure activity relationship (QSAR) model for predicting their FPs. The CODESSA PRO software was adopted to calculate the required molecular descriptors, and 350 molecular descriptors were developed for each compound. A modified stepwise regression algorithm was applied to choose descriptors that were highly correlated with the FP of organosilicon compounds. The proposed model was a linear regression model consisting of six descriptors. This 6-descriptor model gave an R2 value of 0.9174, QLOO2 value of 0.9106, and Q2 value of 0.8989. The average fitting error and the average predictive error were found to be of 10.34 K and 11.22 K, respectively, and the average fitting error in percentage and the average predictive error in percentage were found to be of 3.30 and 3.60%, respectively. Compared with the known reproducibility of FP measurement using standard test method, these predicted results were of a satisfactory precision. |
| format | Article |
| id | doaj-art-3616d5d3e40f43d1b08cc7d4c37c788e |
| institution | Kabale University |
| issn | 2090-9063 2090-9071 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Chemistry |
| spelling | doaj-art-3616d5d3e40f43d1b08cc7d4c37c788e2025-02-03T06:44:20ZengWileyJournal of Chemistry2090-90632090-90712014-01-01201410.1155/2014/482341482341Predicting Flash Point of Organosilicon Compounds Using Quantitative Structure Activity Relationship ApproachChen-Peng Chen0Chan-Cheng Chen1Hsu-Fang Chen2Department of Occupational Safety and Health, China Medical University, 91 Hsueh-Shih Road, Taichung 40402, TaiwanDepartment of Safety, Health and Environmental Engineering, National Kaohsiung First University of Science and Technology, No. 1 University Road, Yanchao District, Kaohsiung 824, TaiwanDepartment of Safety, Health and Environmental Engineering, National Kaohsiung First University of Science and Technology, No. 1 University Road, Yanchao District, Kaohsiung 824, TaiwanThe flash point (FP) of a compound is the primary property used in the assessment of fire hazards for flammable liquids and is amongst the crucial information that people handling flammable liquids must possess as far as industrial safety is concerned. In this work, the FPs of 236 organosilicon compounds were collected and used to construct a quantitative structure activity relationship (QSAR) model for predicting their FPs. The CODESSA PRO software was adopted to calculate the required molecular descriptors, and 350 molecular descriptors were developed for each compound. A modified stepwise regression algorithm was applied to choose descriptors that were highly correlated with the FP of organosilicon compounds. The proposed model was a linear regression model consisting of six descriptors. This 6-descriptor model gave an R2 value of 0.9174, QLOO2 value of 0.9106, and Q2 value of 0.8989. The average fitting error and the average predictive error were found to be of 10.34 K and 11.22 K, respectively, and the average fitting error in percentage and the average predictive error in percentage were found to be of 3.30 and 3.60%, respectively. Compared with the known reproducibility of FP measurement using standard test method, these predicted results were of a satisfactory precision.http://dx.doi.org/10.1155/2014/482341 |
| spellingShingle | Chen-Peng Chen Chan-Cheng Chen Hsu-Fang Chen Predicting Flash Point of Organosilicon Compounds Using Quantitative Structure Activity Relationship Approach Journal of Chemistry |
| title | Predicting Flash Point of Organosilicon Compounds Using Quantitative Structure Activity Relationship Approach |
| title_full | Predicting Flash Point of Organosilicon Compounds Using Quantitative Structure Activity Relationship Approach |
| title_fullStr | Predicting Flash Point of Organosilicon Compounds Using Quantitative Structure Activity Relationship Approach |
| title_full_unstemmed | Predicting Flash Point of Organosilicon Compounds Using Quantitative Structure Activity Relationship Approach |
| title_short | Predicting Flash Point of Organosilicon Compounds Using Quantitative Structure Activity Relationship Approach |
| title_sort | predicting flash point of organosilicon compounds using quantitative structure activity relationship approach |
| url | http://dx.doi.org/10.1155/2014/482341 |
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