2012年5月
Predicting experimental yields as an index to rank synthesis routes II: application to the Curtius rearrangement
JOURNAL OF PHYSICAL ORGANIC CHEMISTRY
- ,
- ,
- ,
- ,
- ,
- 巻
- 25
- 号
- 5
- 開始ページ
- 394
- 終了ページ
- 399
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.1002/poc.1929
- 出版者・発行元
- WILEY
Synthesis yields of organic reactions are one of the most important factors in ranking synthesis routes created by synthesis route design systems such as Transform-Oriented Synthesis Planning and Knowledge base-Oriented Synthesis Planning. If it is possible to predict the yields of synthesis reactions before starting experiments, one can easily determine an order of synthesis routes for experimental works. In the present study, the reaction profiles of the Curtius rearrangement with different substituents were calculated to generate an equation predicting experimental yields of this reaction. Reactions followed by the formation of isocyanates were also analyzed to consider the relationship between reaction times and experimental yields. A partial least squares (PLS) regression was used to correlate the experimental yields with the calculated activation energies, Ea(calc), together with experimental conditions such as dielectric constants of solvents, reaction times, and reaction temperatures as explanatory variables. Although the PLS regression using all the data gave very poor results, we succeeded in making a model equation with R2=0.887 using a modified data set. However, there is a conflict between the predictability and the interpretability on the reaction time. This discrepancy mainly comes from unnecessarily long reaction times in the experiments for azides with calculated Ea values of less than 33kcalmol1. To construct a good model equation for the experimental yields of the Curtius reaction, we have to use data sets obtained from within 90?min of the reaction for the PLS regression. Copyright (c) 2011 John Wiley & Sons, Ltd.
- リンク情報
- ID情報
-
- DOI : 10.1002/poc.1929
- ISSN : 0894-3230
- eISSN : 1099-1395
- Web of Science ID : WOS:000303198500007