Deep learning based combining rule for the estimation of vapor–liquid equilibrium
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Chemical Engineering
Link
https://link.springer.com/content/pdf/10.1007/s43153-023-00377-0.pdf
Reference76 articles.
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3. Bekri S, Özmen D, Türkmenoǧlu A et al (2021) Application of deep neural network (DNN) for experimental liquid–liquid equilibrium data of water + butyric acid + 5-methyl-2-hexanone ternary systems. Fluid Phase Equilib 544–545:113094
4. Bobbo S, Camporese R (1999) Vapor-liquid equilibria for difluoromethane (r32) + and pentafluoroethane (r125) + 1,1,1,3,3,3-hexafluoropropane (r236fa) at 303.2 and 323.3 k. J Chem Eng Data 44(2):349–352
5. Bobbo S, Stryjek R, Elvassore N et al (1998) A recirculation apparatus for vapor–liquid equilibrium measurements of refrigerants. Binary mixtures of r600a, r134a and r236fa. Fluid Phase Equilib 150–151:343–352
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