The phase equilibria relationship of the system RbCl-PEG6000-H2O were investigated at temperatures of 288.2,298.2,and 308.2 K,the compositions of solid-liquid equilibria(SLE)and liquid-liquid equilibria(LLE)were deter...The phase equilibria relationship of the system RbCl-PEG6000-H2O were investigated at temperatures of 288.2,298.2,and 308.2 K,the compositions of solid-liquid equilibria(SLE)and liquid-liquid equilibria(LLE)were determined.The complete phase diagrams,binodal curve diagrams,and tie-line diagrams were all plotted.Results show that both solid-liquid equilibria and liquid-liquid equilibria relationships at each studied temperature.The complete phase diagrams at 288.2 K,298.2 K and 308.2 K consist of six phase regions:unsaturated liquid region(L),two saturated solutions with one solid phase of RbCl(L_S),one saturated liquid phase with two solid phases of PEG6000 and RbCl(2S+L),an aqueous two-phase region(2L),and a region with two liquids and one solid phase of RbCl(2L_S).With the increase in temperature,the layering ability of the aqueous two-phase system increases,and both regions(2L)and(2L_S)increase.The binodal curves were fitted using the nonlinear equations proposed by Mistry,Hu,and Jayapal.Additionally,the tie-line data were correlated with the Othmer-Tobias,Bancroft,Hand,and Bachman equations.The liquid-liquid equilibria at 288.2 K,298.2 K and 308.2 K were calculated using the NRTL model.The findings confirm that the experimental and calculated values are in close agreement,demonstrating the model’s effectiveness in representing the system’s behavior.展开更多
Accurate estimation of the solubility of a chemical compound is an important issue for many industrial proce sses.To overcome the defects of some thermodynamic models and simple correlations,a parallel neural network(...Accurate estimation of the solubility of a chemical compound is an important issue for many industrial proce sses.To overcome the defects of some thermodynamic models and simple correlations,a parallel neural network(PNN) model was conceived and optimized to predict the solubility of diosgenin in seven n-alkanols(C_(1)-C_(7)).The linear regression analysis of the parity plots indicates that the PNN model can give more accurate descriptions of the solubility of diosgenin than the ordinary neural network(ONN) model.The comparison of the average root mean square deviation(RMSD) shows that the suggested model has a slight advantage over the thermodynamic NRTL model in terms of the calculating precision.Moreover,the PNN model can reflect the effects of the temperature and the chain length of the alcohol solvent on the solution behavior of diosgenin correctly and can estimate its solubility in the n-alkanols with more carbon atoms.展开更多
基金supported by the National Natural Science Foundation of China(U1507111).
文摘The phase equilibria relationship of the system RbCl-PEG6000-H2O were investigated at temperatures of 288.2,298.2,and 308.2 K,the compositions of solid-liquid equilibria(SLE)and liquid-liquid equilibria(LLE)were determined.The complete phase diagrams,binodal curve diagrams,and tie-line diagrams were all plotted.Results show that both solid-liquid equilibria and liquid-liquid equilibria relationships at each studied temperature.The complete phase diagrams at 288.2 K,298.2 K and 308.2 K consist of six phase regions:unsaturated liquid region(L),two saturated solutions with one solid phase of RbCl(L_S),one saturated liquid phase with two solid phases of PEG6000 and RbCl(2S+L),an aqueous two-phase region(2L),and a region with two liquids and one solid phase of RbCl(2L_S).With the increase in temperature,the layering ability of the aqueous two-phase system increases,and both regions(2L)and(2L_S)increase.The binodal curves were fitted using the nonlinear equations proposed by Mistry,Hu,and Jayapal.Additionally,the tie-line data were correlated with the Othmer-Tobias,Bancroft,Hand,and Bachman equations.The liquid-liquid equilibria at 288.2 K,298.2 K and 308.2 K were calculated using the NRTL model.The findings confirm that the experimental and calculated values are in close agreement,demonstrating the model’s effectiveness in representing the system’s behavior.
基金supported by the Science and Technology Plan Project of Henan Province (No. 192102310232)。
文摘Accurate estimation of the solubility of a chemical compound is an important issue for many industrial proce sses.To overcome the defects of some thermodynamic models and simple correlations,a parallel neural network(PNN) model was conceived and optimized to predict the solubility of diosgenin in seven n-alkanols(C_(1)-C_(7)).The linear regression analysis of the parity plots indicates that the PNN model can give more accurate descriptions of the solubility of diosgenin than the ordinary neural network(ONN) model.The comparison of the average root mean square deviation(RMSD) shows that the suggested model has a slight advantage over the thermodynamic NRTL model in terms of the calculating precision.Moreover,the PNN model can reflect the effects of the temperature and the chain length of the alcohol solvent on the solution behavior of diosgenin correctly and can estimate its solubility in the n-alkanols with more carbon atoms.
