Theses and Dissertations
Date of Award
12-1-2024
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Chemistry
First Advisor
Javier Macossay-Torres
Second Advisor
Narayan Bhat
Third Advisor
Debasish Bandyopadhyay
Abstract
Over 90% of the approximately 1 million PET bottles sold every minute end up in landfills or oceans, where they can persist for centuries. Plastic pollution urgently needs sustainable management and recycling solutions to mitigate the environmental impact of PET waste. From all techniques to recycle plastic waste, catalytic glycolysis stands out for its rapid reaction time, high monomer yields, lower costs, and enhanced durability.
In this work glycolysis of PET was evaluated under microwave conditions using 1,5,7-Triazabicyclo [4.4.0] dec5-ene (TBD) and 1,8-Diazabicyclo [5.4.0] undec-7-ene (DBU) as catalysts, being DBU as the best catalyst for further analysis. The effect of reaction parameters such as temperature ranges, catalyst concentrations, time, and PET depolymerization rate (% PET conversion) were evaluated and optimized via using a Machine Learning model. The reactions were conducted using an Anton Paar Monowave 400 microwave reactor at catalyst concentrations (1.5 - 10 wt. /wt. %), PET to Ethylene Glycol ratio of 1:10, temperature range 180 - 220°C. and time (1 min – 60 mins). PET was completely depolymerized in 14 mins at 220°C using a catalyst concentration of 5.8 wt./wt.%, and the product was characterized using NMR, FTIR and Mass Spectrometry.
Recommended Citation
Aamir, M. (2024). Machine Learning Optimized Depolymerization of PET (Polyethylene Terephthalate) via Glycolysis [Master's thesis, The University of Texas Rio Grande Valley]. ScholarWorks @ UTRGV. https://scholarworks.utrgv.edu/etd/1853

Comments
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