研究论文
Deep learning based combining rule for the estimation of vapor–liquid equilibrium
Sezin Bekri, Dilek Özmen, Atilla Özmen
Istanbul University-Cerrahpaşa Yalova University Kadir Has University
来源Brazilian Journal of Chemical Engineering
年份2023
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学科主题
工程Phase Equilibria and Thermodynamics
Refrigeration and Air Conditioning Technologies · Process Optimization and Integration
参考文献 61
Flow of information through an artificial neural network
被引 24P.R.B. Guimarãaes, C. McGreavy · Computers & Chemical Engineering · 1995
Vapor–Liquid Equilibrium Measurements for Binary Mixtures Containing 1,1,1,2,3,3,3-Heptafluoropropane (HFC-227ea)1
被引 13Seungbum Koo, Jiyoung Chang, Hong Bin Kim · International Journal of Thermophysics · 2000
Vapor+Liquid Equilibrium Measurements and Correlation of the Binary Refrigerant Mixtures Difluoromethane (HFC-32)+1,1,1,2,3,3-Hexafluoropropane (HFC-236ea) and Pentafluoroethane (HFC-125)+1,1,1,2,3,3-Hexafluoropropane (HFC-236ea) at 288.6, 303.2, and 318.2 K
被引 16Sergio Bobbo, Laura Fedele, Mauro Scattolini · International Journal of Thermophysics · 2000
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引用本文 3
Machine learning models for vapor-liquid equilibrium of binary mixtures: State of the art and future opportunities
被引 6Gabriel Y. Ottaiano, Tiago Dias Martins · Process Safety and Environmental Protection · 2024
Machine Learning for Fluid Thermodynamics: State of the Art and Open Challenges
被引 4Federico Succetti, Massimo Panella, Paolo Giannitrapani · IEEE Access · 2025
Solubility Prediction in N2O + Ionic Liquid Systems Using Artificial Neural Networks Including Thermodynamically Consistent Data
被引 1Elías N. Fierro, Ariana Muñoz, Patricio I. Cerda · Processes · 2025
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