Evaluation of Machine Learning Assisted Phase Behavior Modelling of Surfactant–Oil–Water Systems

Evaluation of Machine Learning Assisted Phase Behavior Modelling of Surfactant–Oil–Water Systems

This paper evaluates the ability of machine learning (ML) algorithms to capture and reproduce complex multiphase behavior in surfactant–oil–water systems. The main objective of the paper is to evaluate the ability of machine learning algorithms to capture complex phase behavior of a surfactant–oil–w...

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Bibliographic Details
Main Authors: Daulet Magzymov, Meruyert Makhatova, Zhassulan Dairov, Murat Syzdykov
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Applied Sciences
Subjects:
surfactant
phase behavior
hybrid model
machine learning
graphical equation of state
Online Access:https://www.mdpi.com/2076-3417/15/1/100
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