烷烃衍生物第一电离能的自相关拓扑研究

Autocorrelation topological study on the first ionization potentials for aliphatic amines, alcohols, ethers and haloalkanes

文中定义烷烃衍生物分子中非氢原子的染色序数(fi),它对于非氢原子具有优异的选择性。由fi建构1阶染色序数自相关拓扑指数(1F)的定义式为:1F=[Σ(1+k)-0.25·(fi·fj)-1]0.5,它对烷烃衍生物分子具有良好的结构选择性。32种脂肪族胺、醇、醚、硫醇、硫醚类化合物的第一电离能(Ip,eV)与1F及O,N,S原子的电负性(XPL)的关系式为:Ip=13.0264-3.82081F+0.1773XPL,R=0.9929。令人满意的27种卤代烷(F,Cl,Br,I)的关系式为:Ip=8.2727-2.64061F+1.5168XPL,R=0.9979。这两个模型较好地揭示了烷烃衍生物第一电离能的递变规律。经Jackknife法检验,具有模型稳健性,并对23种烷烃衍生物Ip估算,显示良好的预测能力。因此,文中为烷烃衍生物第一电离能的预测提供一种有效方法。上述59种烷烃衍生物的Ip与1F的相关系数为0.9791,明显优于著名的Kier指数(1Xv)(其R仅为0.4190)。结果表明,所建定量结构性质相关(QSPR)模型的相关性高、稳健性好、预测能力强。

An atomic colouring number (f_i) was defined in this paper. It has an excellent selectivity for non-hydrogen atoms in alkane and alkyl derivative molecules. The first order autocorrelation topological index ( 1F) of the colouring number was defined as: 1F=[Σ(1+k) -0.25·(f_ ii·f_ jj) -1] 0.5, which showed a good structural selectivity for alkyl derivatives. The first ionization potentials (I_p, eV) of 32 compounds of aliphatic amines, alcohols, ethers, thio-alcohols and thio-ethers could be expressed as a function of 1F and the electronegativity (X_ PL) of O, N and S atoms: I_p=13.026?4-3.820?8 1F+0.177?3 X_ PL, R=0.992?9. A satisfactory equation for 27 compounds of haloankanes was developed as follows: I_p=8.272?7-2.640?6 1F+1.516?8X_ PL, R= 0.997?9. These two models elucidate the rule for variation of I_p for different alkyl derivatives. Furthermore, a modified Jackknife test was performed to validate the model robustness, and the values of I_p of 23 compounds of alkyl derivatives are estimated with a good predictability. Therefore, this paper provides an effective method to predicate the first ionization potentials of alkyl derivatives. A correlation coefficient between I_p and 1F for above 59 alkyl derivatives is equal to 0.979?1, which is much better than that of the famous Kier's index 1X v (R =0.419?0). These results demonstrate that the quantitative structure-property relationship(QSPR) models have a high correlativity, fine stability and precise predictability.