Linear and Nonlinear QSPR Models for Predicting Thermal Stabilities of Nitroaromatic Compounds

高等学校化学研究 ›› 2011, Vol. 27 ›› Issue (5): 891-895.

Linear and Nonlinear QSPR Models for Predicting Thermal Stabilities of Nitroaromatic Compounds

SANG Peng¹, ZOU Jian-wei^1,2*, XU Lin¹ and ZHOU Peng¹

1. Department of Chemistry, Zhejiang University, Hangzhou 310027, P. R. China;
2. Key Laboratory for Molecular Design and Nutrition Engineering, Ningbo Institute of Technology, Zhejiang University, Ningbo 315104, P. R. China

收稿日期:2010-10-21 修回日期:2011-05-07 出版日期:2011-09-25 发布日期:2011-09-06
通讯作者: ZOU Jian-wei E-mail:jwzou@nit.zju.edu.cn
基金资助:
Supported by the National Natural Science Foundation of China(No.20502022).

Linear and Nonlinear QSPR Models for Predicting Thermal Stabilities of Nitroaromatic Compounds

SANG Peng¹, ZOU Jian-wei^1,2*, XU Lin¹ and ZHOU Peng¹

1. Department of Chemistry, Zhejiang University, Hangzhou 310027, P. R. China;
2. Key Laboratory for Molecular Design and Nutrition Engineering, Ningbo Institute of Technology, Zhejiang University, Ningbo 315104, P. R. China

Received:2010-10-21 Revised:2011-05-07 Online:2011-09-25 Published:2011-09-06
Contact: ZOU Jian-wei E-mail:jwzou@nit.zju.edu.cn
Supported by:
Supported by the National Natural Science Foundation of China(No.20502022).

摘要/Abstract

摘要： Quantitative structure-property relationships(QSPRs) have been developed to predict the thermal stability for a set of 22 nitroaromatic compounds by means of the theoretical descriptors derived from electrostatic potentials on molecular surface. Several techniques, including partial least squares regression(PLS), least-squares support vector machine(LSSVM) and Gaussian process(GP) have been utilized to establish the relationships between the structural descriptor and the decomposition enthalpy. The nonlinear LSSVM and GP models have proven to own a better predictive ability than the linear PLS method. Moreover, owing to its ability to handle both linear- and nonlinear-hybrid relationship, GP gives a stronger fitting ability and a better predictive power than LSSVM, and therefore could be well applied to developing QSPR models for the thermal stability of nitroaromatic explosives.

关键词: Quantitative structure-property relationship(QSPR), Nitroaromatic compound, Thermal stability, Gaussian process

Abstract: Quantitative structure-property relationships(QSPRs) have been developed to predict the thermal stability for a set of 22 nitroaromatic compounds by means of the theoretical descriptors derived from electrostatic potentials on molecular surface. Several techniques, including partial least squares regression(PLS), least-squares support vector machine(LSSVM) and Gaussian process(GP) have been utilized to establish the relationships between the structural descriptor and the decomposition enthalpy. The nonlinear LSSVM and GP models have proven to own a better predictive ability than the linear PLS method. Moreover, owing to its ability to handle both linear- and nonlinear-hybrid relationship, GP gives a stronger fitting ability and a better predictive power than LSSVM, and therefore could be well applied to developing QSPR models for the thermal stability of nitroaromatic explosives.

Key words: Quantitative structure-property relationship(QSPR), Nitroaromatic compound, Thermal stability, Gaussian process

中图分类号:

SANG Peng, ZOU Jian-wei*, XU Lin and ZHOU Peng. Linear and Nonlinear QSPR Models for Predicting Thermal Stabilities of Nitroaromatic Compounds[J]. 高等学校化学研究, 2011, 27(5): 891-895.

SANG Peng, ZOU Jian-wei*, XU Lin and ZHOU Peng. Linear and Nonlinear QSPR Models for Predicting Thermal Stabilities of Nitroaromatic Compounds[J]. Chemical Research in Chinese Universities, 2011, 27(5): 891-895.

参考文献

[1] Bretherick L., J. Chem. Educ., 1989, 66, 220 [2] Bretherick L., Handbook of Reactive Chemical Hazards, 4th ed., Butterworths, London, 1990. [3] Frurip D.J., Elwell T., Proc. Safety Prog., 2007, 26, 51 [4] Yu X., Xie Z., Yi B., Wang X., Liu F., Eur. Polym. J., 2007, 43, 818 [5] Keshavarz M.H., Pouretedal H.R., Shokrolahi A., Zali A., Semnani A., J. Hazard. Mater., 2008, 160, 142 [6] Keshavarz M.H., J. Hazard. Mater., 2009, 162, 1557 [7] Saraf S.R., Rogers W.J., Mannan M.S., J. Hazard. Mater., 2003, 98, 15 [8] Fayet G., Joubert L., Rotureau P., Adamo C., Chem. Phys. Lett ., 2009, 467, 407 [9] Fayet G., Rotureau P., Joubert L., Adamo C., J. Hazard. Mater., 2009, 171, 845 [10] Fayet G., Rotureau P., Joubert L., Adamo C., J. Mol. Model., 2010, 16, 805 [11] Katritzky A.R., Petrukhin R., Jain R., Karelson M., J. Chem. Inf. Comput. Sci., 2001, 41, 1521 [12] Gustin J.L., Org. Process Res. Dev., 1998, 2, 27 [13] Pedretti A., Villa L., Vistoli G., J. Mol. Graphics, 2002, 21, 47 [14] Martens H.A., Dardenne P., Chemometr. Intell. Lab. Syst., 1998, 44, 99 [15] Geladi P., Kowalski B.R., Anal. Chim. Acta., 1986, 185, 1 [16] Luco J.M., J. Chem. Inf. Comput. Sci., 1999, 39, 396 [17] Silva M.F., Chipre L.F., Raba J., Luco J.M., Chromatographia, 2001, 53, 392 [18] Luco J.M., Salinas A.P., Torriero A.A.J., Vazquez R.N., Raba J., Marchevsky E.D., J. Chem. Inf. Comput. Sci., 2003, 43, 2129 [19] Luco J. M., Marchevsky E., Curr. Comput.-Aided Drug Design, 2006, 2, 31 [20] Suykens J.A.K., Vandewalle J., Neural Process. Lett., 1999, 9, 293 [21] Zhou P., Tian F.F., Chen X., Shang Z.C., Biopolymers (Pept Sci), 2008, 90, 792 [22] Zhou P., Chen X., Wu Y.Q., Shang Z.C., Amino Acids, 2010, 38, 199 [23] Liu X.H., Liang J., Fan J.C., Shang Z.C., QSAR Comb. Sci., 2009, 28, 1386 [24] Obrezanova O., Csányi G., Gola J.M.R., Segall M.D., J. Chem. Inf. Model., 2007, 47, 1847 [25] Rasmussen C.E., Evaluation of gaussian processes and other methods for non-linear regression. PhD thesis, University of Toronto, Canada, 1996. [26] Wolfe P., SIAM Rev., 1969, 11, 226 [27] Zhou P., Tian F.F., Lv F.L., Shang Z.C., J. Chromatogr. A , 2009, 1216, 3107 [28] ChemoAC calibration toolbox, Virtual institute of chemometrics and industrial metrology, Brussels, Belgium. [29] Suykens J. A. K., van Gestel T., de Brabanter J., de Moor B., Vandewalle J., Least squares support vector machines, World Scientific, Singapore, 2002. [30] Rasmussen C.E., Williams C.K.I., Gaussian processes for machine learning, MIT Press, Massachusetts, 2006. [31] Murray J.S., Brinck T., Lane P., Paulsen K., Politzer P., J. Mol. Struct. (THEOCHEM), 1994, 113, 55

Linear and Nonlinear QSPR Models for Predicting Thermal Stabilities of Nitroaromatic Compounds

Linear and Nonlinear QSPR Models for Predicting Thermal Stabilities of Nitroaromatic Compounds

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	QU Huiqi, PAN Longhai, SUN Yuexin, WANG Lei, LI Yanyan, ZHANG Mingjuan, ZHANG Zhaoxiang, LIN Haifeng. Supramolecular Assemblies of Three New Metronidazole Derivatives Constructed with Various Dihydroxy-benzoic Acids via Hydrogen Bonds[J]. 高等学校化学研究, 2020, 36(6): 1196-1202.
[2]	LIN Qingjin, LIN Chenlu, LIU Jingying, LIU Shuang, XU Haidi, CHEN Yaoqiang, DAN Yi. Optimization of Hybrid Crystal with SAPO-5/34 on Hydrothermal Stability for deNO_x Reaction by NH₃[J]. 高等学校化学研究, 2020, 36(6): 1249-1254.
[3]	LI Kai, HE Kunhuan, LI Quanwen, XIA Bin, WANG Qinglun, ZHANG Yinghui. Crystal Structure and Photoluminescence Properties of Two Barium(Ⅱ) MOFs[J]. 高等学校化学研究, 2018, 34(5): 700-704.
[4]	ZHANG Liangliang, XIN Xuelian, LU Yukun, SUN Daofeng. High-selectivity Detection of 2,4,6-Trinitrophenol Based on Fluorescent Mg-MOF-74 in Ethanol Solution[J]. 高等学校化学研究, 2018, 34(2): 175-179.
[5]	FU Xianwei, LIU Yang, LIU Zhi, DONG Ning, ZHAO Tianyu, ZHAO Dan, LIAN Gang, WANG Qilong, CUI Deliang. Pressure-sensitive Transistor Fabricated from an OrganicSemiconductor 1,1'-Dibutyl-4,4'-bipyridinium Diiodide[J]. 高等学校化学研究, 2018, 34(1): 95-100.
[6]	HU Fang, WANG Yamin, LAI Xiaoyong, WU Yusheng, DU Fei, WANG Chunzhong. Facile Synthesis of Mesoporous Si-containing γ-Al₂O₃Nanofiber with Enhanced Thermal Stability[J]. 高等学校化学研究, 2015, 31(1): 156-159.
[7]	TIAN Xiujuan, WANG Zhongwei, YU Qing, WU Qingyu, GAO Jun. Synthesis and Property of Flame Retardant Epoxy Resins Modified with 2-(Diphenylphosphinyl)-1,4-benzenediol[J]. 高等学校化学研究, 2014, 30(5): 868-873.
[8]	WU Yu-sheng, MA Jiao, LI Ming-chun, HU Fang. Synthesis of γ-Al₂O₃ with High Surface Area and Large Pore Volume by Reverse Precipitation-azeotropic Distillation Method[J]. 高等学校化学研究, 2013, 29(2): 206-209.
[9]	CAO Zi-jian, JIN Lin, WANG Xi-bin, CUI Zhan-chen, ZHANG Da-ming. Properties of DR1/PMMA-co-GMA for High Speed Electro-optical Switch[J]. 高等学校化学研究, 2012, 28(6): 1091-1094.
[10]	LIU Juan-ying, LI Zhi-lin, VOGEL Walter, YANG Hui. In situ XRD Studies on Heat-treated PtRu/C Nanocatalysts[J]. 高等学校化学研究, 2012, 28(3): 511-515.
[11]	WANG Xing-yong, CUI Jing-nan, REN Wei-min, ZHAO Guo-quan, LI Feng, ....... Reductive Metabolism of Nitroaromatic Compounds by Various Liver Microsomes[J]. 高等学校化学研究, 2010, 26(6): 981-985.
[12]	WANG Xue-mei, WU Ya-hong, HAO Zhi-feng*, YU Jian and YU Lin. Preparation, Curing Reactivity and Thermal Properties of Titanium-doped Silicone Resins[J]. 高等学校化学研究, 2010, 26(5): 851-856.
[13]	BAO Ren-lie, KONG Zu-ping, GU Min, YUE Bin, WENG Lin-hong, HE He-yong. Hydrothermal Synthesis and Thermal Stability of Natural Mineral Lindgrenite[J]. 高等学校化学研究, 2006, 22(6): 679-683.
[14]	XU Jing-bo, JING Ti-song, YANG Li, SUN Zhi-wei, SHI Long. Effects of Nitrobenzenes on DNA Damage in Germ Cells of Rats[J]. 高等学校化学研究, 2006, 22(1): 29-32.
[15]	LI Dong-tao, LI Wen, LI Bao-qing. Hydrogen Bonds in Coal——The Influence of Coal Rank and the Recognition of a New Hydrogen Bond in Coal[J]. 高等学校化学研究, 2003, 19(1): 70-75.