Experimental Solubility Data for Binary Mixtures of Ethane and 2,2,4-Trimethylpentane at Pressures up to 6 MPa Using a New Variable-Volume Sapphire Cell

2017 ◽  
Vol 62 (11) ◽  
pp. 3915-3920 ◽  
Author(s):  
Wayne Michael Nelson ◽  
Deresh Ramjugernath
Keyword(s):  
Binary Mixtures ◽  
Solubility Data ◽  
Variable Volume ◽  
Experimental Solubility Data ◽  
Experimental Solubility

Determination of Abraham model solute descriptors for 4-tert-butylbenzoic acid from experimental solubility data in organic mono-solvents

2018 ◽  
Vol 57 (4) ◽  
pp. 445-452 ◽  
Author(s):  
Erin Hart ◽  
Grace Lee ◽  
Ellen Qian ◽  
Megan Jodray ◽  
Maribel Barrera ◽  
...  
Keyword(s):  
Solubility Data ◽  
Abraham Model ◽  
Experimental Solubility Data ◽  
Experimental Solubility ◽  
Solute Descriptors

scholarly journals Solubility of Acetophenone in Supercritical Carbon Dioxide

2016 ◽  
Vol 10 (1) ◽  
pp. 18-28 ◽  
Author(s):  
Maria Y. Dwi ◽  
Jessica Julian ◽  
Jindrayani N. Putro ◽  
Adi T. Nugraha ◽  
Yi-Hsu Ju ◽  
...  
Keyword(s):  
Experimental Data ◽  
Carbon Dioxide ◽  
Equation Of State ◽  
Supercritical Carbon Dioxide ◽  
Static Method ◽  
Solubility Data ◽  
Experimental Solubility Data ◽  
Experimental Solubility ◽  
Robinson Equation ◽  
Supercritical Carbon

The solubility data of acetophenone in supercritical carbon dioxide (scCO2) were measured using a static method at several temperatures (313.15, 323.15, 333.15, and 343.15K) and pressures ranging from10 MPa to 28 MPa. The density based models (Chrastil and Del valle– Aguilera models) and the Peng-Robinson equation of state (PR-EOS) with quadratic and Stryjek-Vera combining rules were employed to correlate the experimental data. Good correlations between the calculated and experimental solubility data were obtained. The sum of squared errors (SSE) are 0.38 % and 0.37 % for Chrastil and Del Valle – Aguilera models, respectively; and 9.07 % for Peng-Robinson equation of state with quadratic combining rule and 4.00 % for Peng-Robinson equation of state with Stryjek-Vera combining rule.

scholarly journals The importance of the accuracy of the experimental data for the prediction of solubility

2010 ◽  
Vol 75 (4) ◽  
pp. 483-495 ◽  
Author(s):  
Slavica Eric ◽  
Marko Kalinic ◽  
Aleksandar Popovic ◽  
Halid Makic ◽  
Elvisa Civic ◽  
...  
Keyword(s):  
Experimental Data ◽  
Computational Models ◽  
Linear Regression Analysis ◽  
Heuristic Method ◽  
Parameter Analysis ◽  
Solubility Data ◽  
Data Sets ◽  
Data Set ◽  
Experimental Solubility Data ◽  
Experimental Solubility

Aqueous solubility is an important factor influencing several aspects of the pharmacokinetic profile of a drug. Numerous publications present different methodologies for the development of reliable computational models for the prediction of solubility from structure. The quality of such models can be significantly affected by the accuracy of the employed experimental solubility data. In this work, the importance of the accuracy of the experimental solubility data used for model training was investigated. Three data sets were used as training sets - Data Set 1 containing solubility data collected from various literature sources using a few criteria (n = 319), Data Set 2 created by substituting 28 values from Data set 1 with uniformly determined experimental data from one laboratory (n = 319) and Data Set 3 created by including 56 additional components, for which the solubility was also determined under uniform conditions in the same laboratory, in the Data Set 2 (n = 375). The selection of the most significant descriptors was performed by the heuristic method, using one-parameter and multi-parameter analysis. The correlations between the most significant descriptors and solubility were established using multi-linear regression analysis (MLR) for all three investigated data sets. Notable differences were observed between the equations corresponding to different data sets, suggesting that models updated with new experimental data need to be additionally optimized. It was successfully shown that the inclusion of uniform experimental data consistently leads to an improvement in the correlation coefficients. These findings contribute to an emerging consensus that improving the reliability of solubility prediction requires the inclusion of many diverse compounds for which solubility was measured under standardized conditions in the data set.

Glycol Loss in a Gaseous System: Thermodynamic Assessment Test of Experimental Solubility Data

2011 ◽  
Vol 56 (11) ◽  
pp. 4012-4016 ◽  
Author(s):  
Amir H. Mohammadi ◽  
Ali Eslamimanesh ◽  
Mohammad Yazdizadeh ◽  
Dominique Richon
Keyword(s):  
Thermodynamic Assessment ◽  
Solubility Data ◽  
Experimental Solubility Data ◽  
Experimental Solubility

Solubility of methane in octane + ethanol at temperatures from 303.15 K to 333.15 K and pressures up to 12.01 MPa

2012 ◽  
Vol 66 (4) ◽  
Author(s):  
Jun-Qing Cai ◽  
Jin-Zhi Qiao
Keyword(s):  
Experimental Data ◽  
Equation Of State ◽  
Solubility Data ◽  
Mixing Rules ◽  
Average Deviation ◽  
Experimental Solubility Data ◽  
Experimental Solubility

AbstractSolubility of methane in octane + ethanol was measured at temperatures ranging from 303.15 K to 333.15 K and pressures ranging from 2.60 MPa to 12.01 MPa. Experimental data were analyzed using the Soave-Redlich-Kwong equation of state with three types of mixing rules, and the estimated average deviation from the experimental solubility data was less than 3.5 %.

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