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Simulation of ^(13)C NMR chemical shifts of carbinol carbon atoms using quantitative structure-spectrum relationships 被引量:2

Simulation of ^(13)C NMR chemical shifts of carbinol carbon atoms using quantitative structure-spectrum relationships
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摘要 A quantitative structure-spectrum relationship (QSSR) model was developed to simulate 13C nuclear magnetic resonance (NMR) spectra of carbinol carbon atoms for 55 alcohols. The proposed model,using multiple linear regression,contained four descriptors solely extracted from the molecular structure of compounds. The statistical results of the final model show that R2= 0.982 4 and S=0.869 8 (where R is the correlation coefficient and S is the standard deviation). To test its predictive ability,the model was further used to predict the 13C NMR spectra of the carbinol carbon atoms of other nine compounds which were not included in the developed model. The average relative errors are 0.94% and 1.70%,respectively,for the training set and the predictive set. The model is statistically significant and shows good stability for data variation as tested by the leave-one-out (LOO) cross-validation. The comparison with other approaches also reveals good performance of this method. A quantitative structure-spectrum relationship (QSSR) model was developed to simulate ^13C nuclear magnetic resonance (NMR) spectra of carbinol carbon atoms for 55 alcohols. The proposed model, using multiple linear regression, contained four descriptors solely extracted from the molecular structure of compounds. The statistical results of the final model show that R2= 0.982 4 and S=0.869 8 (where R is the correlation coefficient and S is the standard deviation). To test its predictive ability, the model was further used to predict the ^13C NMR spectra of the carbinol carbon atoms of other nine compounds which were not included in the developed model. The average relative errors are 0.94% and 1.70%, respectively, for the training set and the predictive set. The model is statistically significant and shows good stability for data variation as tested by the leave-one-out (LOO) cross-validation. The comparison with other approaches also reveals good performance of this method.
出处 《Journal of Central South University》 SCIE EI CAS 2011年第2期323-330,共8页 中南大学学报(英文版)
基金 Projects(20775010, 21075011) supported by the National Natural Science Foundation of China Project(2008AA05Z405) supported by the National High-tech Research and Development Program of China Project(09JJ3016) supported by the Natural Science Foundation of Hunan Province, China Project(09C066) supported by the Scientific Research Fund of Hunan Provincial Education Department, China Project(2010CL01) supported by the Foundation of Hunan Provincial Key Laboratory of Materials Protection for Electric Power and Transportation, China
关键词 核磁共振光谱 原子光谱 碳原子 甲醇 模拟 模型预测 化学 定量构谱关系 carbinol carbon atom ^13C nuclear magnetic resonance chemical shift topological indices quantitative structure-spectroscopy relationship
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