Determination of Isosteric Heat and Entropy of Sorption of Air Dried Sheet Rubber Using Artificial Neural Network Approach

Abstract

Equilibrium moisture contents (EMC) of air dried sheet (ADS) rubber were determined by commonly gravimetric-static method with saturated salt solution among surrounding temperatures of 40-70°C correlated to water activity (aw) ranges between 0.10 and 0.9. The experimental results was analyzed by 5 commonly EMC model. The results showed that equilibrium moisture content of ADS rubber decreased with increase of surrounding temperature at constant water activity and the simulated data using Chung-Pfost model has a good relation to experimental data with R2, RMSE and χ2 equal 0.9565, 0.0235 and 0.0006, respectively. However some physical property of ADS rubber sample affects to evaluate EMC modeling. Due to avoid this effect, thus the aim of this research work was to determine EMC value by using Artificial neural network (ANN) method and also evaluate the isosteric heat of sorption by following the Clausius-Clapeyron equation. The results showed that simulated results using ANN approach has relatively high accuracy compared to common EMC model. Finally determination of isosteric heat of sorption and entropy of sorption of ADS rubber were carried on. The results stated that the enthalpy and entropy of heat sorption was power function and polynomial function of moisture content respectively. These two parameters of ADS rubber can be used for prediction suitable storage condition and drying condition for ADS rubber drying in the near future work.