Theoretical studies on heats of formation for cubylnitrates using density functional theory B3LYP method and semiempirical MO methods

被引:31
|
作者
Zhang, J [1 ]
Xiao, JJ [1 ]
Xiao, HM [1 ]
机构
[1] Nanjing Univ Sci & Technol, Dept Chem, Nanjing 210094, Peoples R China
关键词
cubylnitrates; heat of formation; density functional theory; semiempirical MO methods; isodesmic reactions;
D O I
10.1002/qua.1092
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
The heats of formation (HOF) have, been calculated for all the 21 cubylnitrate compounds using the semiemprical molecular orbital (MO) methods (MINDO/3, MNDO, AM1, and PM3) and for 8 of 21 cubylnitrates containing 1-4-ONO2 groups using the density functional theory (DFT) method at the B3LYP/6-31G* level by means of designed isodesmic reactions-The cubane cage skeletons in cubylnitrate molecules have been kept in setting up isodesmic reactions to produce more accurate and reliable results. It is found that there are good linear relationships between the HOFs of the 8 cubylnitrates calculated using B3LYP/6-31G* and two semiempirical MO (PM3 and AM1) methods, and the linear correlation coefficients of PM3 and AM methods are 0.9901 and 0.9826, respectively. Subsequently, the accurate HOFs at B3LYP/6-31G* level of other 13 cubylnitrates containing 4-8-ONO2 groups are obtained by systematically correcting their PM3-calculated HOFs. Compared with noncaged nitrates, all the 21 cubylnitrates have high heats of formation implying that they may be very powerful energetic materials and have highly exploitable value. The relationship between the HOFs and the molecular structures of cubylnitrates has been discussed. (C) 2002 John Wiley & Sons, Inc.
引用
收藏
页码:305 / 312
页数:8
相关论文
共 50 条
  • [1] Theoretical studies on heats of formation for polynitrocubanes using the density functional theory B3LYP method and semiempirical MO methods
    Zhang, J
    Xiao, HM
    Gong, XD
    JOURNAL OF PHYSICAL ORGANIC CHEMISTRY, 2001, 14 (08) : 583 - 588
  • [2] Studies on heats of formation for polycyanocubanes with density functional theory B3LYP method and semiempirical MO methods
    Zhang, J
    Xiao, HM
    Xiao, JJ
    Gong, XD
    ACTA CHIMICA SINICA, 2001, 59 (08) : 1230 - 1235
  • [3] Studies on heats of formation for tetrazole derivatives with density functional theory B3LYP method
    Chen, ZX
    Xiao, JM
    Xiao, HM
    Chiu, YN
    JOURNAL OF PHYSICAL CHEMISTRY A, 1999, 103 (40): : 8062 - 8066
  • [4] A B3LYP hybrid density functional theory study of structural properties, energies, and heats of formation for silicon-hydrogen compounds
    Jursic, BS
    JOURNAL OF MOLECULAR STRUCTURE-THEOCHEM, 2000, 497 : 65 - 73
  • [5] Studies on the trapping and detrapping transition states of atomic hydrogen in octasilsesquioxane using the density functional theory B3LYP method
    Mattori, M
    Mogi, K
    Sakai, Y
    Isobe, T
    JOURNAL OF PHYSICAL CHEMISTRY A, 2000, 104 (46): : 10868 - 10872
  • [6] A comparison of PM3 semiempirical and B3LYP density functional methods for calculating carbon nanotube -: Hydrocarbon bond strengths
    Bolton, K
    Gustavsson, S
    Rosén, A
    2003 THIRD IEEE CONFERENCE ON NANOTECHNOLOGY, VOLS ONE AND TWO, PROCEEDINGS, 2003, : 615 - 618
  • [7] Accurate Prediction of Heats of Formation by a Combined Method of B3LYP and Neural Network Correction
    Wu, Jianming
    Xu, Xin
    JOURNAL OF COMPUTATIONAL CHEMISTRY, 2009, 30 (09) : 1424 - 1444
  • [8] The B3LYP hybrid density functional study on solids
    Chen Z.-Y.
    Yang J.-L.
    Frontiers of Physics in China, 2006, 1 (3): : 339 - 343
  • [9] Performance of B3LYP density functional methods for a large set of organic molecules
    Tirado-Rives, Julian
    Jorgensen, William L.
    JOURNAL OF CHEMICAL THEORY AND COMPUTATION, 2008, 4 (02) : 297 - 306
  • [10] Machine Learning Methods to Predict Density Functional Theory B3LYP Energies of HOMO and LUMO Orbitals
    Pereira, Florbela
    Xiao, Kaixia
    Latino, Diogo A. R. S.
    Wu, Chengcheng
    Zhang, Qingyou
    Aires-de-Sousa, Joao
    JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2017, 57 (01) : 11 - 21