芳香醚类化合物13C NMR化学位移模拟

摘要

构建了基于分子三维结构计算的原子电负性距离矢量（atomic electronegative space distance vector,AESDV），用以描述各芳香醚类化合物分子中不同等价碳原子的化学微环境，并结合原子自身杂化状态指数（AHSI），建立了13C核磁共振定量结构波谱关系的多元线性回归模型，复相关系数（R）为0.964，标准误差（SD）为8.673．经留一法交互检验的复相关系数（RCV）为0.948，标准误差（SDCV）为10.362．随机抽出样本进行外部检验，得到测试集的复相关系数（Rtest1及 Rtest2）分别为0.979和0.939，标准误差（SDtest1及 SDtest2）分别为6.400和10.162．研究结果表明，使用该方法所建模型具有良好的预测能力和稳定性．%Atomic electronegative space distance vector (AESDV) which characterizing the microenvironment of equivalent carbon atoms was constructed based on the three-dimensional structures of aromatic ethers. TheAESDVwas then employed in combination with atomic hybridation state index (AHSI) to calculate13C NMR chemical shifts of 46 carbon atoms in 9 aromatic ethers, and to explore quantitative structure spectroscopy relationship. With multiple linear regression (MLR), a model with a correlation coefficient (R) of 0.964 and a standard deviation (SD) of 8.763 was obtained. Cross-validation of the model was performed by leave-one-out procedure (LOO), resulting in a correlation coefficient (RCV) of 0.948 and a standard deviation (SDCV) of 10.362. Furthermore, the 9 aromatic ethers were randomly assigned into a training set and a test set, respectively, to validate this model, and the correlation coefficientsRtest1 andRtest2 were found to be 0.979 and 0.939, and the standard deviationsSDtest1 andSDtest2to be 6.400 and 10.162, respectively. The results showed that the model established can be used to predict13C NMR chemical shifts in aromatic ethers.