Experimental petroleum resin production and optimization using response surface modeling
Mohamad-Taghi Rostami1, Hamidreza Shahverdi2, Vahid Javanbakht3
1Department of Chemical Engineering, Isfahan University of Technology, Isfahan, 84156-83111, Iran.
Scientific Reports
|January 28, 2026
Summary
This study optimized petroleum resin production using a combined experimental and modeling approach. The best conditions yielded high-quality resin with maximum output and minimal color, validated by accurate predictions.
Area of Science:
- Polymer Chemistry
- Chemical Engineering
- Materials Science
Background:
- Petroleum resins are vital industrial materials.
- Optimizing their production is key for efficiency and quality.
- Cationic polymerization offers a route to tailored resin properties.
Purpose of the Study:
- To develop an integrated framework for optimizing petroleum resin production.
- To systematically investigate the impact of key parameters on resin characteristics.
- To establish predictive models for resin yield, molecular weight, softening point, and color.
Main Methods:
- Response Surface Methodology (RSM) with a Central Composite Design (CCD).
- Investigation of reaction temperature, catalyst dosage (AlCl3), and reaction time.
- Empirical modeling and experimental validation for multi-objective optimization.
Main Results:
- Developed highly predictive models (R² > 0.94) for resin properties.
- Identified optimal conditions: 20°C, 1.13 wt% catalyst, 86 min for maximum yield (22.5%) and softening point (152°C) with low color (Gardner 3.7).
- Experimental validation showed prediction errors below 3%.
Conclusions:
- The study provides a robust, validated framework for optimizing petroleum resin synthesis.
- Mechanistic insights into polymerization behavior were gained.
- The findings have direct implications for industrial-scale petroleum resin production.
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