膦类化合物核磁共振谱化学位移预测
定量结构波谱关系,膦类化合物,核磁共振谱化学位移,离子性指数,立体效应参数,,定量结构波谱关系，膦类化合物，核磁共振谱化学位移，离子性指数，立体效应参数,摘要
摘 要 采用离子性指数(INI)、立体效应参数(εi)对291个膦化合物中磷原子进行结构表征,并与其核磁共振磷谱(31P NMR)建立定量结构波谱关系(QSSR)模型。分别利用多元线性回归(MLR)、偏最小二乘回归(PLSR)、人工神经网络(ANN)建模，同时采用内部及外部双重验证的办法对所得模型稳定性能进行深入分析和检验，建模计算值、留一法(LOO)交互校验(CV)预测值和外部样本预测值的复相关系数Rcum、QLOO和Qext分别为0.9449, 0.9408和0.9338(MLR)；0.9421、0.9411和0.9338(PLSR)；0.9741、0.9736和0.9471 (ANN)。结果表明：INI、εi与31P NMR谱化学位移显著相关。关键词 定量结构波谱关系，膦类化合物，核磁共振谱化学位移，离子性指数，立体效应参数
Prediction of the 31P Chemical Shifts in Nuclear Magnetic
Resonance Spectroscopy for 291 Phosphines
Tong Jianbo, Zeng Hui, Zhang Shengwan, Zhou Peng, Yang Shengxi,Feng Yanlin, Zhang Qiaoxia, Li Zhiliang
(College of Chemistry and Chemical Engineering, Shanxi University, Taiyuan 030006)
(College of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400044)
(Key Laboratory of Biomedical Engineering of Chongqing Municipality, Chongqing 400044)
Abstract Systematic investigations were made on relationship between 31P nuclear magnetic resonance (NMR) of chemical shifts of 291 phosphines and their molecular structure parameters of phosphorus atoms, such as ionicity index (INI) and stereoscopic effect parameters (εi). Here three quantitative structurespectrum relationship (QSSR) models were built by multiple linear regression (MLR), partial least square regression (PLS) and artificial neural network (ANN), the estimation stability and generalization ability of these models were strictly analyzed by both internal and external validations. The correlation coefficients (R2) of established MLR, PLS and ANN models, LeaveOneOut (LOO) CrossValidation(CV), predicted values versus experimental ones of external samples were 0.9449, 0.9408 and 0.9338(MLR); 0.9421, 0.9411 and 0.9338(PLS); 0.9741, 0.9736 and 0.9471(ANN), respectively. Satisfactory results showed that INI and εi were obviously related with 31P NMR chemical shifts of phosphines. ......
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