Citation: Du Xihua, Tian Lin, Li Jing. Theoretical Research on Retention and Separation Factors of Diarylmethane Derivatives by Neural Network Method[J]. Chemistry, ;2016, 79(11): 1073-1078. shu

Theoretical Research on Retention and Separation Factors of Diarylmethane Derivatives by Neural Network Method

1.
School of Chemistry and Chemical Engineering, Xuzhou Institute of Technology, Xuzhou 221111

Received Date: 11 March 2016
Available Online: 31 July 2016
Fund Project:

In order to study retention factors and separation factors of the chiral diarylmethane derivatives, the molecular connectivity index and electrotopological state index of 63 chiral diarylmethane derivatives were calculated based on the location of molecular structure and conjugation matrix. The relationship model between the retention factors, separation factors and optimized molecular structure parameters of these compounds were developed. Using the structural parameters as the input variables of the neural network, we constructed three satisfying QSRR models with back-propagation algorithm, whose network structure were different. The total correlation coefficient R was 0.981, 0.972 and 0.992 respectively. The mean deviation between the experimental and the predicted values of lgk₂, lgk₁ and lgα was 0.041, 0.042 and 0.010 respectively. The results showed that there was good nonlinear relationship between the lgk₂, lgk₁, lgα and the structural parameters.
- Diarylmethane derivatives,
- Retention factors,
- Separation factors,
- Molecular connectivity index,
- Electrotopological state indices,
- Neural networks
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沈阳化工大学材料科学与工程学院沈阳 110142