The solubility of CI Disperse Red 4 and CI Disperse Red 15 in supercritical carbon dioxide was measured using a dynamic method. The data was analyzed using a back propagation neural network. The results showed that the neural network accurately estimated the solubility data in supercritical carbon dioxide with a good fitting level of 0.99.
The solubility of 1-amino-2-hydroxy-4-methoxy-anthraquinone (CI Disperse Red 4) and 1-amino-2-hydroxy-anthraquinone (CI Disperse Red 15) in supercritical carbon dioxide was measured using a dynamic method over a temperature range from 343.15 to 373.15 K and a pressure range from 14 to 22 MPa. The experimental data are analysed by using the back propagation neural network constructed by MATLAB. In the back propagation neural network, the input layer consisted of two inputs, which are temperature and pressure, the output layer consisted of the solubility of dyes, and the hidden layer function was composed of a non-linear function. The results of the analysis showed that a good fitting level of 0.99 was obtained, which means that the back propagation neural network can accurately estimate the solubility data in supercritical carbon dioxide.
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