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摘要
The present paper studies the prediction possibilities of the liquid crystalline behavior for some symmetrically derivatives with two ferrocene units using the artificial intelligence methods - neural networks. The liquid crystalline property is correlated with chemical Structure of the compounds, quantified by a series of molecular descriptors, which are estimated by mechanical molecular simulation. Good predictions are obtained in the validation phase, which proves the generalization capability of the neural model and its availability for liquid crystal property estimation.
- 出版日期2008-4
