On the evaluation of the carbon dioxide solubility in polymers using gene expression programming

Evaluation, prediction, and measurement of carbon dioxide (CO 2 ) solubility in different polymers are crucial for engineers in various chemical applications, such as extraction and generation of novel materials. In this paper, correlations based on gene expression programming (GEP) were generated t...

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Bibliographic Details
Published in:Scientific reports 2023-08, Vol.13 (1), p.12505-12505, Article 12505
Main Authors: Amiri-Ramsheh, Behnam, Nait Amar, Menad, Shateri, Mohammadhadi, Hemmati-Sarapardeh, Abdolhossein
Format: Article
Language:English
Subjects:
639/166
639/4077
Carbon dioxide
Gene expression
Humanities and Social Sciences
multidisciplinary
Polymers
Polystyrene
Science
Science (multidisciplinary)
Solubility
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Summary:Evaluation, prediction, and measurement of carbon dioxide (CO 2 ) solubility in different polymers are crucial for engineers in various chemical applications, such as extraction and generation of novel materials. In this paper, correlations based on gene expression programming (GEP) were generated to predict the value of carbon dioxide solubility in three polymers. Results showed that the generated correlations could represent an outstanding efficiency and provide predictions for carbon dioxide solubility with satisfactory average absolute relative errors of 9.71%, 5.87%, and 1.63% for polystyrene (PS), polybutylene succinate-co-adipate (PBSA), and polybutylene succinate (PBS), respectively. Trend analysis based on Henry’s law illustrated that increasing pressure and decreasing temperature lead to an increase in carbon dioxide solubility. Finally, outlier discovery was applied using the leverage approach to detect the suspected data points. The outlier detection demonstrated the statistical validity of the developed correlations. William’s plot of three generated correlations showed that all of the data points are located in the valid zone except one point for PBS polymer and three points for PS polymer.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-023-39343-8