探討 PC-SAFT狀態方程式應用在預測藥物於超臨界二氧化碳流體中的溶解度;Prediction of Drug Solubility in Supercritical Carbon Dioxide by PC-SAFT EOS

NCU Institutional Repository > 工學院 > 化學工程與材料工程研究所 > 博碩士論文 > Item 987654321/89140

jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://ir.lib.ncu.edu.tw/handle/987654321/89140

题名:	探討 PC-SAFT狀態方程式應用在預測藥物於超臨界二氧化碳流體中的溶解度;Prediction of Drug Solubility in Supercritical Carbon Dioxide by PC-SAFT EOS
作者:	吳蓁蓁;Wu, Chen-Chen
贡献者:	化學工程與材料工程學系
关键词:	超臨界二氧化碳;藥物溶解度;PCSAFT狀態方程式;PC-SAFT EOS;supercritical carbon dioxide;drug solubility
日期:	2022-08-10
上传时间:	2022-10-04 10:59:23 (UTC+8)
出版者:	國立中央大學
摘要:	本研究探討PC-SAFT狀態方程式於預測藥物分子在超臨界二氧化碳中的溶解度，並與PR狀態方程式進行比較。在PC-SAFT狀態方程式對於無氫鍵的系統需要三個純物質參數m、σ、ϵ，而有氫鍵的系統則需要五個純物質參數m、σ、ϵ、ϵAB、кAB，這些參數只需從純物質蒸氣壓或是液體密度回歸而得，相較於臨界性質取得較容易。因PR狀態方程式計算過程中需純物質的臨界性質，故在研究中也比較了使用官能基貢獻法NRR以及PR-COSMOSAC(PRCS)來計算之。本研究一共探討了60個固體溶質，並以其分子結構中有無氫鍵為基準，將分子分成22個不含締合貢獻(無氫鍵)的系統與38個含締合貢獻(有氫鍵)的系統。在22個不含氫鍵系統中，有13個有蒸氣壓與9個無蒸氣壓的系統，在蒸氣壓計算中PC-SAFT的誤差(AARD-P)為2.53%，PR-NRR與PR-PRCS的誤差為48.66%與60.83%；在溶解度的計算中，PC-SAFT使用的參數為蒸氣壓回歸而得，在有二元相互作用參數kij的條件下，PC-SAFT的誤差(ALD-x)為0.29，PR-NRR與PR-PRCS為0.52與0.31，若使用溶解度回歸PC-SAFT純物質參數，得到的溶解度誤差(ALD-x)為0.22。在38個含有氫鍵的系統中，亦探討PC-SAFT純物質參數кAB=0.01與кAB=0.02的計算差異，18個有蒸氣壓的系統中，PC-SAFT蒸氣壓的計算誤差(AARD-P)為8.56% ( кAB=0.01)與10.78% ( кAB=0.02)，PR-NRR與PR-PRCS的誤差為88.46%與189.14%；在溶解度的計算中，PC-SAFT在使用蒸氣壓回歸而得的參數並搭配kij的條件下，誤差(ALD-x)為0.49 ( кAB=0.01)與0.58( кAB=0.02)，而PR-NRR與PR-PRCS的誤差(ALD-x)為0.64與0.71，若使用溶解度回歸PC-SAFT純物質參數，得到的溶解度誤差(ALD-x)為0.28。在蒸氣壓的計算中，使用PC-SAFT會有更好的準確度；在溶解度計算中，針對二元系統，若是在有二元相互作用參數的條件下，PC-SAFT能提供優異的計算能力，而三元系統則是PR-NRR有更好的預估能力。 ;This study aims to understand the accuracy of the Perturbed Chain-Statistical Association Fluid Theory (PC-SAFT) EOS in predicting solubility of drug-like molecules in supercritical carbon dioxide (ScCO2) and compares it with the PR EOS. In PC-SAFT EOS, three pure-component parameters m, σ, ϵ are required for non-associating components, while five pure-component parameters m, σ, ϵ, ϵAB, кAB are required for associating components. These parameters can be regressed by fitting pure-component data such as vapor pressure or liquid density, which is easier to obtain than critical properties. The required critical properties and acentric factor od pure solid solute for PR EOS are determined from group contribution method NRR and PR-COSMOSAC (PRCS) EOS. In this study, a total of 60 drug-like solid solutes were investigated, and the molecules were divided into 22 non-associating solutes and 38 associating based on whether there were hydrogen bonding functional groups, such as hydroxyl or amino groups, in their molecular structures. For the 22 non-associating systems, there are 13 solutes with vapor pressure experimental data, the average absolute relative deviation (AARD-P) in vapor pressure is 2.53% from PCSAFT, and 48.66% and 60.83% from PR-NRR and PR-PRCS. The overall average logarithmic deviation (ALD-x) in solubility for these 13 solid solutes is 0.29 from PCSAFT and 0.52 and 0.31 from PR-NRR and PR-PRCS, and if the PC-SAFT pure-component parameters were regressed by solubility, the overall average logarithmic deviation (ALD-x) in solubility for 22 solid solutes is 0.22. For the 38 associating systems, the difference of PC-SAFT pure-component parameters кAB=0.01 and кAB=0.02 was also discussed. For 18 solid solutes with vapor pressure, the average absolute relative deviation (AARD-P) in vapor pressure is 8.56% (кAB= 0.01) and 10.78% ( кAB= 0.02) from PC-SAFT, and 88.46% and 189.14% from PR-NRR and PR-PRCS; The overall average logarithmic deviation (ALD-x) in solubility for these 18 solid solutes is 0.49 ( кAB =0.01) and 0.58 ( кAB =0.02) from PC-SAFT and 0.64 and 0.71 from PR-NRR and PR-PRCS, and if the PC-SAFT pure-component parameters were regressed by solubility, the overall average logarithmic deviation (ALD-x) in solubility for 38 solid solutes further reduces to 0.28. In the calculation of vapor pressure, PC-SAFT will have better accuracy; in solubility calculation, for binary systems, if there are binary interaction parameter, PC-SAFT can provide excellent prediction ability, and the ternary system is that PR-NRR has better prediction ability.
显示于类别:	[化學工程與材料工程研究所] 博碩士論文

文件中的档案:

档案	描述	大小	格式	浏览次数
index.html		0Kb	HTML	28	检视/开启

在NCUIR中所有的数据项都受到原著作权保护.

社群 sharing

数据加载中.....