scholarly journals Measurement and Calculation of the Liquid–Liquid Phase Boundaries and Phase Equilibria for the Hexane+Polyethylene System at High Temperatures

2016 ◽  
Vol 49 (6) ◽  
pp. 493-502 ◽  
Author(s):  
Masashi Haruki ◽  
Shohei Fujikawa ◽  
Kotaro Adachi ◽  
Yuki Hadano ◽  
Shin-ichi Kihara ◽  
...  
Keyword(s):  
Liquid Phase ◽  
Phase Equilibria ◽  
High Temperatures ◽  
Phase Boundaries

VAN LAAR EQUATION AND UNIFAC TO CORRELATE THE DATA LIQUID PHASE EQUILIBRIA FOR THE EXTRACTION OF PHENOLIC COMPOUNDS FROM MODEL COAL TAR

2016 ◽  
Vol 72 (9) ◽  
Author(s):  
Dewi Selvia Fardhyanti ◽  
Wahyudi B. Sediawan ◽  
Panut Mulyono ◽  
Muslikhin Hidayat
Keyword(s):  
Phenolic Compounds ◽  
Liquid Phase ◽  
Phase Equilibria ◽  
Coal Tar ◽  
Van Laar Equation

Effect of pressure on the solid-liquid phase equilibria in (water + sodium sulfate) system

1992 ◽  
Vol 76 ◽  
pp. 163-173 ◽  
Author(s):  
Y. Tanaka ◽  
S. Hada ◽  
T. Makita ◽  
M. Moritoki
Keyword(s):  
Liquid Phase ◽  
Phase Equilibria ◽  
Sodium Sulfate ◽  
Effect Of Pressure ◽  
Solid Liquid

Phase equilibria in the AlNbTi system at high temperatures

1998 ◽  
Vol 6 (2) ◽  
pp. 79-94 ◽  
Author(s):  
A. Hellwig ◽  
M. Palm ◽  
G. Inden
Keyword(s):  
Phase Equilibria ◽  
High Temperatures

Solid-liquid Phase Equilibria of U(VI) in NaCl Solutions

1998 ◽  
Vol 62 (2) ◽  
pp. 245-263 ◽  
Author(s):  
P. Dı́az Arocas ◽  
B. Grambow
Keyword(s):  
Liquid Phase ◽  
Phase Equilibria ◽  
Solid Liquid

scholarly journals Thermodynamics and Machine Learning Based Approaches for Vapor–Liquid–Liquid Phase Equilibria in n-Octane/Water, as a Naphtha–Water Surrogate in Water Blends

Processes ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 413
Author(s):  
Sandra Lopez-Zamora ◽  
Jeonghoon Kong ◽  
Salvador Escobedo ◽  
Hugo de Lasa
Keyword(s):  
Machine Learning ◽  
Liquid Phase ◽  
Phase Equilibria ◽  
Aspen Plus ◽  
Phase Region ◽  
Two Phase ◽  
Technical Literature ◽  
Phase Liquid ◽  
Liquid Vapor ◽  
Vapor Liquid

The prediction of phase equilibria for hydrocarbon/water blends in separators, is a subject of considerable importance for chemical processes. Despite its relevance, there are still pending questions. Among them, is the prediction of the correct number of phases. While a stability analysis using the Gibbs Free Energy of mixing and the NRTL model, provide a good understanding with calculation issues, when using HYSYS V9 and Aspen Plus V9 software, this shows that significant phase equilibrium uncertainties still exist. To clarify these matters, n-octane and water blends, are good surrogates of naphtha/water mixtures. Runs were developed in a CREC vapor–liquid (VL_ Cell operated with octane–water mixtures under dynamic conditions and used to establish the two-phase (liquid–vapor) and three phase (liquid–liquid–vapor) domains. Results obtained demonstrate that the two phase region (full solubility in the liquid phase) of n-octane in water at 100 °C is in the 10-4 mol fraction range, and it is larger than the 10-5 mol fraction predicted by Aspen Plus and the 10-7 mol fraction reported in the technical literature. Furthermore, and to provide an effective and accurate method for predicting the number of phases, a machine learning (ML) technique was implemented and successfully demonstrated, in the present study.

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