半透膜仪采集空气中多氯联苯采样速度与其结构和性质定量构效关系研究(英文)  

Quantitative relationship for air sampling rates of polychlorinated biphenyls by semipermeable membrane devices with their structures and properties

作　　者：朱秀华[1] 丁光辉[2] Walkiria Levy Karl-Werner Schramm 王炜[1] 穆军[1] 

机构地区：[1]中国大连交通大学环境与化学工程学院,辽宁大连116028 [2]中国大连海事大学环境科学与工程学院,辽宁大连116026 [3]Helmholtz Zentrum Munchen-German Research Center for Environmental Health,Institute of EcologicalChemistry,Ingolstadter Landstr.1,D-85764 Neuherberg,Munich,Germany [4]TUM,Wissenschaftszentrum Weihenstephan fuer Emaehnmg und Landnutzung,Department fuer Biowissenschaftliche Grundlagen,Weihenstephaner Steig 23,85350 Freising,Germany

出　　处：《计算机与应用化学》2011年第1期6-10,共5页Computers and Applied Chemistry

基　　金：supported bv the National Natural Science Foundation of China(20877011);State Key Laboratory of Environmental Chemistry and Ecotoxicology,Research Center for Eco-Environmental Sciences,Chinese Academy of Science(KF2009-17);the Key Laboratory of Industrial Ecology and Environmental Engineering,China Ministry of Education(0802);Scientific Research Foundation for Returned Overseas Chinese Scholars~~

摘　　要：根据MOPAC2009软件包中PM6算法得到的分子描述符研究半透膜仪(SPMDs)采集大气中多氯联苯(PCBs)采样速度(R_(air))的定量构效关系(QSPR)模型,并分析影响R_(air)的关键因素。以半经验PM6算法得到的分子量子化学描述符作为预测变量,采用偏最小二乘算法(PLS)构建了R_(air)的QSPR模型。根据交叉验证,所得到的最佳模型中PLS成分解释的因变量的累积变异(Q^2_(cum))为0.683,这表明该模型具有良好的预测能力和稳健性。通过外部验证和将实验测得的R_(air)与预测得到的R_(air)进行比较,对所构建模型的稳定性和可靠性进行了验证,结果表明无论是训练组还是预测组,其预测值与实测值间均具有较好的线性关系,线性相关系数均大于0.8376。对PCBs采样速度R_(air)的主要影响因素为PCBs与SPMDs中甘油三油酸酯分子间的相互作用大小和为将PCBs溶解在甘油三油酸酯中形成洞穴所需能量要求。The purpose of this paper is to develop Quantitative structure-property relationship （QSPR） models for air sampling rates （Rair） of polychlorinated biphenyls （PCBs） with semipermeable membrane devices （SPMDs） based on molecular descriptors derived from the PM6 method in MOPAC2009 software package, and analyze the key factors influencing the Rair. Partial least square （PLS） regression was used to develope QSPR model for Rair. Quantum chemical descriptors computed by semi-empirical PM6 method were used as predictor variables. The cumulative variance of the dependent variable explained by the PLS components and determined by cross-validation （Q^2cum）, for the optimal model is 0.683, indicating that the model has good predictive ability and robustness, and could be used to estimate Rair values. The stability and validity of the model was also tested by external validation testing and by comparing calculated Rair with experimental data. The linear correlation coefficients between predicted and experimental values were all larger than 0.8376 for both training set and prediction set. The main factors governing Rair values of PCBs are intermolecular interactions between PCBs and triolein in SPMDs and the energy required for cave-forming in dissolution of PCBs into triolein of SPMDs.

关 键 词：空气采样速度 SPMD PCB PLS QSPR 

分 类 号：X132[环境科学与工程—环境科学] O6-39[理学—化学]