%P 1395-1402
%I Elsevier Ltd
%A Z. Kassim
%A M. Saad Khan
%A B. Lal
%V 19
%T Thermodynamic modelling on methane hydrate equilibrium condition in the presence of electrolyte inhibitor
%R 10.1016/j.matpr.2019.11.158
%D 2019
%L scholars11893
%J Materials Today: Proceedings
%O cited By 25; Conference of 2018 International Conference on Chemical Sciences and Engineering: Advance and New Materials, ICCSE 2018 ; Conference Date: 7 November 2018 Through 8 November 2018; Conference Code:157391
%K Electrolytes; Gas hydrates; Hydration; Hydrogen bonds; Methane; Temperature, Equilibrium conditions; Equilibrium temperatures; Hydrate cages; Hydrate equilibria; Hydrate equilibrium prediction; Hydrate inhibition; Methane hydrates; Thermodynamic modelling; Thermodynamics theory; Water activity, Forecasting
%X In hydrate equilibrium conditions at given pressure, only one temperature is presence which is the equilibrium temperature. Therefore, in this work, thermodynamic modelling was employed to predict the effect of TEACl on methane hydrate equilibrium temperature. The hydrate equilibrium temperature are modelled using the thermodynamic model proposed by Dickens and Quinby-Hunt adapter from earlier work of Pieroen. The model was established from the conventional thermodynamic theory of salts are capable to interrupt the water activity. Based on the theory, cation and anion of TEACl is able to form a hydrogen bond with water hence hindrance the hydrate cage formation and further disrupts the encapsulation of methane gas molecules. Acceptable agreement between the experimental data and the model results is observed with less than 1.0 K deviation. In comparison, the thermodynamic model is used to predict the literature experimental data and deviation is found to be at 0.6 K. Furthermore, the average absolute deviation (AAD) is found to be over predicted of 0.15 K, 0.18 K and 0.32 K for 1 wt, 5 wt and 10 wt of TEACl concentrations, respectively. The accuracy of the model indicates of all the studied system in the presence of TEACl serves an excellent groundwork to extend the application of the model. © 2019 Elsevier Ltd.