Exploring Gel-Point Identification in Epoxy Resin Using Rheology and Unsupervised Learning
Any thermoset resin’s processing properties and end-use performance are heavily influenced by the gel time. The complicated viscosity of resin as a function of temperature is investigated in this work, with a particular emphasis on identifying the gel point and comprehending polymerization. Rheology...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-10-01
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| Series: | Gels |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2310-2861/9/10/828 |
| _version_ | 1797573808140320768 |
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| author | Eddie Gazo Hanna Khaled Younes Semaan Amine Rabih Roufayel |
| author_facet | Eddie Gazo Hanna Khaled Younes Semaan Amine Rabih Roufayel |
| author_sort | Eddie Gazo Hanna |
| collection | DOAJ |
| description | Any thermoset resin’s processing properties and end-use performance are heavily influenced by the gel time. The complicated viscosity of resin as a function of temperature is investigated in this work, with a particular emphasis on identifying the gel point and comprehending polymerization. Rheology studies carried out using a plate-plate controlled stress rheometer under isothermal conditions were used to compare three experimental techniques for figuring out an epoxy resin’s gel point. We also look at the basic modifications that take place during polymerization. We verify the reliability of the three strategies by including Principal Component Analysis (PCA), an unsupervised machine learning methodology. PCA assists in uncovering hidden connections between these methods and various affecting factors. PCA serves a dual role in our study, confirming method validity and identifying patterns. It sheds light on the intricate relationships between experimental techniques and material properties. This concise study expands our understanding of resin behavior and provides insights that are essential for optimizing resin-based processes in a variety of industrial applications. |
| first_indexed | 2024-03-10T21:14:16Z |
| format | Article |
| id | doaj.art-f6e58bd90188482da101608e7ceeff93 |
| institution | Directory Open Access Journal |
| issn | 2310-2861 |
| language | English |
| last_indexed | 2024-03-10T21:14:16Z |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Gels |
| spelling | doaj.art-f6e58bd90188482da101608e7ceeff932023-11-19T16:35:58ZengMDPI AGGels2310-28612023-10-0191082810.3390/gels9100828Exploring Gel-Point Identification in Epoxy Resin Using Rheology and Unsupervised LearningEddie Gazo Hanna0Khaled Younes1Semaan Amine2Rabih Roufayel3College of Engineering and Technology, American University of the Middle East, Egaila 54200, KuwaitCollege of Engineering and Technology, American University of the Middle East, Egaila 54200, KuwaitCollege of Engineering and Technology, American University of the Middle East, Egaila 54200, KuwaitCollege of Engineering and Technology, American University of the Middle East, Egaila 54200, KuwaitAny thermoset resin’s processing properties and end-use performance are heavily influenced by the gel time. The complicated viscosity of resin as a function of temperature is investigated in this work, with a particular emphasis on identifying the gel point and comprehending polymerization. Rheology studies carried out using a plate-plate controlled stress rheometer under isothermal conditions were used to compare three experimental techniques for figuring out an epoxy resin’s gel point. We also look at the basic modifications that take place during polymerization. We verify the reliability of the three strategies by including Principal Component Analysis (PCA), an unsupervised machine learning methodology. PCA assists in uncovering hidden connections between these methods and various affecting factors. PCA serves a dual role in our study, confirming method validity and identifying patterns. It sheds light on the intricate relationships between experimental techniques and material properties. This concise study expands our understanding of resin behavior and provides insights that are essential for optimizing resin-based processes in a variety of industrial applications.https://www.mdpi.com/2310-2861/9/10/828epoxyrheologygel pointthermosetprincipal component analysis (PCA) |
| spellingShingle | Eddie Gazo Hanna Khaled Younes Semaan Amine Rabih Roufayel Exploring Gel-Point Identification in Epoxy Resin Using Rheology and Unsupervised Learning Gels epoxy rheology gel point thermoset principal component analysis (PCA) |
| title | Exploring Gel-Point Identification in Epoxy Resin Using Rheology and Unsupervised Learning |
| title_full | Exploring Gel-Point Identification in Epoxy Resin Using Rheology and Unsupervised Learning |
| title_fullStr | Exploring Gel-Point Identification in Epoxy Resin Using Rheology and Unsupervised Learning |
| title_full_unstemmed | Exploring Gel-Point Identification in Epoxy Resin Using Rheology and Unsupervised Learning |
| title_short | Exploring Gel-Point Identification in Epoxy Resin Using Rheology and Unsupervised Learning |
| title_sort | exploring gel point identification in epoxy resin using rheology and unsupervised learning |
| topic | epoxy rheology gel point thermoset principal component analysis (PCA) |
| url | https://www.mdpi.com/2310-2861/9/10/828 |
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