Prediction of Solubility in Supercritical Carbon Dioxide and Organic Polymeric Materials

• Main Authors: Li-Hsin Wang, 王立行
• Other Authors: 林祥泰
• Format: Others
• Language: en_US
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/3fq9a8

博士 === 國立臺灣大學 === 化學工程學研究所 === 105 === Developing predictive models to provide useful information for the phase behaviors, especially for the properties of solubility in complex systems, is the main goal of this research. The drug solubility in the supercritical carbon dioxide and the gas solubility in the organic polymer membrane are considered in this study since the application of these novel technologies reduces the energy use and the pollution generated. In the past, to our best knowledge, fewer studies focus on developing “predictive models” that require no experimental inputs for making the predictions. As a result, COSMO-based methods which only require the quantum properties of molecules are chosen, and modifications are introduced in order to provide better prediction accuracy. In the first part of this research, the drug solubility in supercritical carbon dioxide is predicted from Peng-Robison plus COSMOSAC equation of state (PR+COSMOSAC EOS). The melting temperature, Tm and enthalpy of melting, Hm, of the solid drug and the critical properties (Tc,Pc) and acentric factor for fluid are the only properties required. The average logrithmetic deviations (ALD-x) in predicted solubility of 46 drugs in subcritical and supercritical carbon dioxide (T= 293.15 K~473K, P= 8.5MPa~50MPa, and 1150 solubility data ranging from 10-7~10-2) is found to be 1.14(8145.04%). The prediction inaccuracy can be significantly reduced to 0.81(3689.35%) when introducing an additional correction to the dispersion energy for aromatic and ring structures. Solid-vapor-liquid equilibrium for the drug-solvent pair is also determined in order to examine the stability of the predicted solubility. From the first part of this research, we found the deficiency of the PR+COSMOSAC EOS for the prediction of saturated pressure at low temperatures. In order to improve the prediction quality systematically, we introduce two modifications in PR+COSMOSAC EOS. In particular, the accuracy for the vapor pressure near triple point shows major improvement, with the ALD-P reduced from 0.391(4747.67%) to 0.321(3029.12%). The sublimation pressure can also be estimated providing that the melting temperature and enthalpy of fusion are available. The ALD-P in sublimation pressure from the modified PR+COSMOSAC EOS for 1140 substances is 0.71(412.9%), which is only 1/3 of that from the original model (1.13(1249%)). This model is capable of providing both the vapor pressure and sublimation pressure over a wide range of conditions (from the critical point to below the triple point). It is particularly useful when no experimental data is available. In the last part of this research, A predictive approach based on the combination of PR+COSMOSAC equation of state (EOS) and COSMO-SAC liquid model through self-consistent mixing rule (SCMR) is proposed for the prediction of gas solubility in polymers. We have validated this approach using 84 binary systems consisting of 9 gas molecules and 21 polymers with temperature ranging from 283.15 K to 498 K. The root mean square error (RMSE) in the predicted log_10 k_H is 0.33(86.71%), which is significantly more accurate than those from other predictive approaches. We believe this new method may provide useful assistants to the development of polymer membrane-based gas separation processes especially when experimental information is not available.