Prediction of flammability characteristics of pure hydrocarbons from molecular structures

AIChE Journal

Volumn 56, Issue 3, 2010, Pages 690-701

  Pan, Yong ^a   Jiang, Juncheng ^a   Ding, Xiaoye ^a   Wang, Rui ^a   Jiang, Jiajia ^a  

^a NANJING TECH UNIVERSITY   (China)

Author keywords

Flammability characteristics; Hydrocarbons; Molecular descriptors; Prediction; QSPR

Indexed keywords

AUTOIGNITION TEMPERATURE; AVERAGE ABSOLUTE ERROR; DESCRIPTORS; FLAMMABILITY CHARACTERISTICS; FLASH POINTS; MOLECULAR DESCRIPTORS; MULTIPLE LINEAR REGRESSIONS; PURE HYDROCARBONS; QUANTITATIVE STRUCTURE PROPERTY RELATIONSHIPS; TEST SETS; UPPER FLAMMABILITY LIMITS;

HYDROCARBONS; LINEAR REGRESSION; MATHEMATICAL MODELS; MOLECULAR STRUCTURE; SULFUR COMPOUNDS;

FLAMMABILITY;

EID: 76749149590     PISSN: 00011541     EISSN: 15475905     Source Type: Journal    
DOI: 10.1002/aic.12007     Document Type: Article

References (28)

1. Chang YM, Lee JC, Chen JR, Liaw HJ, Shu CM. Flammability characteristics studies on toluene and methanol mixtures with different vapor mixing ratios at 1 atm and 150°C. J Therm Anal Calorim. 2008;93:183-188.
2. Albahri TA. Flammability characteristics of pure hydrocarbons. Chem Eng Sci. 2003;58:3629-3641.
3. Liaw HJ, Chen CT, Gerbaud V. Flash-point prediction for binary partially miscible aqueous-organic mixtures. Chem Eng Sci. 2008; 63:4543-4554.
4. AIChE/CCPS. Guidelines for Engineering Design for Process Safety. New York, NY: American Institute of Chemical Engineers, 1993.
5. ASTM. ASTM Standard Test Method E659-78. West Conshohocken: American Society for Testing and Materials, 2000.
6. Mitchell BE, Jurs PC. Prediction of autoignition temperatures of organic compounds from molecular structure. J Chem Inform Comput Sci. 1997;37:538-547.
7. ASTM Annual Book of Standards. Philadelphia, PA: American Society for Testing and Materials, 2002.
8. Taskinen J, Yliruusi J. Prediction of physicochemical properties based on neural network modeling. Adv Drug Deliv Rev. 2003; 55:1163-1183.
9. Vidal M, Rogers WJ, Holste JC, Mannan MS. A review of estimation methods for flash points and flammability limits. Process Saf Progr. 2004;23:47-55.
10. Pan Y, Jiang JC, Wang R, Cao HY, Cui Y. Predicting the auto-ignition temperatures of organic compounds from molecular structure using support vector machine. J Hazard Mater. 2009;164:1242-1249.
11. Brauner N, Cholakov GSt, Kahrs O, Stateva RP, Shacham M. Linear QSPRs for predicting pure compound properties in homologous series. AIChE J. 2008;54:978-990.
12. Cholakov GSt, Stateva RP, Shacham M, Brauner N. Prediction of properties in homologous series with a shortcut QS2PR method. AIChE J. 2007;53:150-159.
13. Bernazzani L, Duce C, Micheli A, Mollica V, Sperduti A, Starita A, Tiné MR. Predicting physical-chemical properties of compounds from molecular structures by recursive neural networks. J Chem Inform Model. 2006;46:2030-2042.
14. Brauner N, Shacham M, Cholakov GSt, Stateva RP. Property prediction by similarity of molecular structures-practical application and consistency analysis. Chem Eng Sci. 2005;60:5458-5471.
15. Shacham M, Brauner N, Cholakov GST, Stateva RP. Property prediction by correlations based on similarity of molecular structures. AIChE J. 2004;50:2481-2492.
16. Dyekjaer JD, Jonsdottir SO. QSPR models based on molecular mechanics and quantum chemical calculations, Part 2: Thermodynamic properties of alkanes, alcohols, polyols and ethers. Ind Eng Chem Res. 2003;42:4241-4259.
17. Katritzky AR, Maran U, Lobanov V, Karelson M. Structurally diverse quantitative-structure property relationship correlations of technologically relevant physical properties. J Chem Inform Comput Sci. 2000;40:1-18.
18. Katritzky AR, Lobanov VS, Karelson M. QSPR: the correlation and quantitative prediction of chemical and physical properties from structure. Chem Soc Rev. 1995;24:279-287.
19. Rowley RL, Wilding WV, Oscarson JL, Yang Y, Zundel NA. DIPPR Data Compilation of Pure Chemical Properties Design Institute for Physical Properties. Provo, Utah: Brigham Young University, 2006. Available at http//dippr.byu.edu.
20. Todeschini R, Consonni V. Handbook of Molecular Descriptors. Weinheim: Wiley-VCH, 2000.
21. Karelson M, Lobanov VS, Katritzky AR. Quantum-chemical descriptors in QSAR/QSPR studies. Chem Rev. 1996;96:1027-1043.
22. Todeschini R, Consonni V, Mauri A, Pavan M. DRAGON User Manual. Milano, Italy: Talete srl, 2006.
23. Holland JH. Adaptation in Natural and Artificial Systems. Ann Arbor: University of Michigan Press, 1975.
24. Leardi R, Boggia R, Terrile M. Genetic algorithms as a strategy for feature selection. J Chemometr. 1992;6:267-281.
25. Gramatica P. Principles of QSAR models validation: internal and external. QSAR Comb Sci. 2007;26:694-701.
26. Tetteh J, Suzuki T, Metcalfe E, Howells S. Quantitative structureproperty relationships for the estimation of boiling point and flash point using a radial basis function neural network. J Chem Inform Comput Sci. 1999;39:491-507.
27. Suzuki T. Quantitative structure-property relationships for auto-ignition temperatures of organic compounds. Fire Mater. 1994;18:81-88.
28. Tropsha A, Gramatica P, Gombar VK. The importance of being earnest: validation is the absolute essential for successful application and interpretation of QSPR models. QSAR Comb Sci. 2003;22:69-77.