| 肖方竹.基于DFT与量子拓扑学的氯代二苯并呋喃QSPR研究[J].南华大学学报(自然科学版),2012,26(1):73~78.[XIAO Fang-zhu.QSPR Study of PCDFs Based on DFT-Quantum Topological Method[J].Journal of University of South China(Science and Technology),2012,26(1):73~78.] |
| 基于DFT与量子拓扑学的氯代二苯并呋喃QSPR研究 |
| QSPR Study of PCDFs Based on DFT-Quantum Topological Method |
| 投稿时间：2011-12-06 |
| DOI： |
| 中文关键词: 氯代二苯并呋喃 光解半衰期 平衡电负性 量子拓扑指数 定量结构-性质相关 |
| 英文关键词:polychlorinated dibenzofurans(PCDFs) photolysis half-lives equilibrium electro-negativity quantum topological indices quantitative structure-property relationship(QSPR) |
| 基金项目:湖南省卫生厅科研基金资助项目(B2011-039);衡阳市科研基金资助项目(2011KS2) |
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| 中文摘要: |
| 为了研究多氯代二苯并呋喃(PCDFs)在云杉针叶和飞灰表面的光解半衰期(t1/2)与其结构的定量关系,本文应用密度泛函理论(DFT),在B3LYP/6-31+G(d) 基组上优化和振动分析计算了48种PCDFs的分子空间几何结构,得到其各原子之间空间拓扑距离,并建立拓扑空间距离矩阵.结合分子中各原子的支化度,应用原子平衡电负性对分子图进行着色修饰,得到量子拓扑指数XP1、XP2.采用偏最小二乘回归法(PLS)对48种PCDFs在云杉针叶和飞灰表面的t1/2进行模拟分析,分别得到2定量结构-性质相关(QSPR)模型,并用这种模型对t1/2进行预测,结果表明预测结果和实验值吻合较好.同时对QSPR拓扑模型采用留一检验法(LOO)进行测试,测试结果显示模型具有良好稳定性和较强的预测能力. |
| 英文摘要: |
| In order to study the quantitative relationship between photolysis half-lives (t1/2) of PCDFs on spruce (Picea abies) needles and fly ash surfaces and its structure.In this paper,using density functional theory (DFT),the molecular space structure patterns of 48 polychlorinated dibenzofurans (PCDFs) were optimized,calculated and analysed at the B3LYP/6-31+G(d) level and the topological distance matrix was built with the space topological distance among atoms.We introduced two quantum topological indices XP1,XP2based on the topological distance matrix,branch vertex of atoms in a molecule,which was put forward by colouring atoms in the molecular graph with equilibrium electro-negativity.And two quantitative structure-property relationship(QSPR) models on t1/2of PCDFs on spruce(Picea abies) needles and fly ash surfaces were developed by partial least regression (PLS).The calculated results by the model indicate the average relative deviations between calculated values and experimental data of t1/2.To validate the estimation stability for internal samples and the predictive capability for external samples of resulting models,Leave-One-Out (LOO) were performed.And the results shows that the models have good stability and predictability. |
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