Predicting the Net Heat of Combustion of Organosilicon Compounds from Molecular Structures

2012 ◽  
Vol 51 (40) ◽  
pp. 13274-13281 ◽  
Author(s):  
Yong Pan ◽  
Juncheng Jiang ◽  
Yinyan Zhang
2014 ◽  
Vol 716-717 ◽  
pp. 180-183
Author(s):  
Hong Yin Cao ◽  
Rui Wang

A quantitative structure–property relationship (QSPR) model for predicting the standard net heat of combustion () was developed based on the ant colony optimization (ACO) method coupled with the partial least square (PLS) for variable selection. Five molecular descriptors were screened out as the parameters of the model, which were finally constructed using multi-linear regression (MLR) method. A reliable model of five parameters for predicting the of esters was established, which can provide some help for engineering to predict the based on only their molecular structures.


2000 ◽  
Vol 78 (11) ◽  
pp. 1388-1395 ◽  
Author(s):  
G Fritz ◽  
M Keuthen ◽  
F Kirschner ◽  
E Matern ◽  
H Goesmann ◽  
...  

The photobromination of 1,1,3,3,5,5-hexamethyl-1,3,5-trisilacyclohexane (1) almost exclusively attacks CH2 groups and results in 2,2-dibromo-trisilacyclohexane (2) as well as 2,2,4,4-tetrabromo-trisilacyclohexane (3) in high yields. Starting from a mixture of C-brominated trisilacyclohexanes the isomeric 2,2,9-tribromo-1,3,3,5,5,8,8,10,10,13,13-undecamethyl-1,3,5,8,10,13-hexasilabicyclo[7.2.2]tridec-6-yne (6) had been obtained in very low yield in an attempt to establish a preparative route to adamantanes with a C4Si6 skeleton, i.e., with C bridgeheads and SiR2 bridges. By ICl-cleavage of a Si—methyl bond in 2 and subsequent substitution with Br3CLi, the trisilacyclohexane 4 with functional groups in opposite positions of the ring can be obtained. Linking the step-by-step synthesized Cl-Me2Si-C=C-SiMe2-CH2-SiMe2-Ph to the CBr3 group of 4 results after HBr-cleavage of the Si—Ph bond in (ω-bromo-octynyl)-trisilacyclohexane (12). A ring closure of 12 would result in an isomeric hexasila bicyclo[7.2.2]tridec-6-yne. The compounds were characterized by 1H, 13C, and 29Si NMR spectra. Additionally, the molecular structures of 4 and 6 were confirmed by X-ray single crystal investigations.Key words: 1,1,3,3,5,5-hexamethyl-1,3,5-trisilacyclohexane, bromination, 2,2,9-tribromo-1,3,3,5,5,8,8,10,10,13,13-undecamethyl-1,3,5,8,10,13-hexasilabicyclo[7.2.2]tridec-6-yne, carbosilane synthesis, NMR data, crystal structure investigation.


2012 ◽  
Vol 37 (2) ◽  
pp. 130-139 ◽  
Author(s):  
Yong Pan ◽  
Juncheng Jiang ◽  
Rui Wang ◽  
Xiao Zhu ◽  
Yinyan Zhang

2013 ◽  
Vol 750-752 ◽  
pp. 2248-2251
Author(s):  
Rui Wang ◽  
Hong Yin Cao ◽  
Quan Sheng Kang ◽  
Zhen Ming Li

A novel QSPR model was proposed as to predict the gross heat of combustion of 32 nitro aromatic compounds. Genetic algorithm (GA) was applied to select the optimal subset of the molecular structures descriptors most related to gross heat of combustion. The multiple linear regression (MLR) was taken to build a prediction model of gross heat of combustion for the 32 compounds. The correlation coefficients (R2) together with correlation coefficient of the leave-one-out cross validation (Q2CV) of the model is 0.997 and 0.995, respectively. The new model is highly statistically significant, and the robustness as well as internal prediction capability of which is satisfactory. This study can provide a new way for predicting the gross heat of combustion of nitro aromatic compounds for engineering.


2013 ◽  
Vol 651 ◽  
pp. 210-215 ◽  
Author(s):  
Hong Yin Cao ◽  
Rui Wang

A quantitative structure–property relationship (QSPR) model for prediction of standard net heat of combustion (ΔH0c) was developed based on the ant colony optimization (ACO) method coupled with the partial least square (PLS) for variable selection. For developing this model, a diverse set of 1650 organic compounds were used, and 1481 molecular descriptors were calculated for every compound. Four molecular descriptors were screened out as the parameters of the model, which was finally constructed using multi-linear regression (MLR) method. The squared correlation coefficient R2of the model was 0.995 for the training set of 1322 compounds. For the test set of 328 compounds, the corresponding R2was 0.996. The results of this study showed that an accurate prediction model for ΔH0ccould be obtained by using the ant colony optimization method. Moreover, this study can provide a new way for predicting the ΔH0cof organic compounds for engineering based on only their molecular structures.


Sign in / Sign up

Export Citation Format

Share Document