Murat BEKEN

A new tool for prediction of phase transitions in liquid crystals

In this article, fundamental analysis of C37H59NO2, C37H59NO3, and C41H67NO2 from among liquid crystals is conducted via Differential Thermal Analysis (DTA) device in high pressure environment. Phase transition temperature, entalphy, and entrophy of these liquid crystals are observed. In addition, an Artificial Neural Network (ANN), which is a method of Artificial Intelligence, is modeled. Then, output values of ANN model and DTA device are compared, and correlation between them is demonstrated. For the values which are not measured with DTA device, outputs are produced by ANN model. In this article, three layered feed-forward back propagation ANN model is used. With this approach, it is proved that, ANN is a resourceful method for prediction in studies conducted about phase transition.

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