(69a) Superstructure Design of Solvent-Assisted Plastics Recycling Processes
AIChE Annual Meeting
2022
2022 Annual Meeting
Liaison Functions
Undergraduate Research Presentations - Chemicals, Biotechology, and Environment
Monday, November 14, 2022 - 8:00am to 8:15am
Despite the extensive history of plastic manufacturing and widespread use, much of this industry's waste goes unrecycled. The current waste management infrastructure lacks an effective sorting method for plastic waste and as a result a portion of the plastics sent to material recovery facilities are rejected. Conventional mechanical recycling downgrades the recycled plastics properties whereas chemical recycling presents a promising alternative this problem. However, plastic recycling is not economically viable, solvent recovery is a necessary step because of the large volume of solvent required. To that end, difficult problems posed by plastics entering their end-of-life stage need to be addressed through the investigation of feasible chemical recycling methods.
To address this issue, we present a superstructure optimization approach for the recovery and recycling of plastic. With this framework, we categorize and compare different separation technologies based on driving forces, efficiencies, feed properties, and group them into stages. Not only do we consider the technologies used but also the physicochemical properties of the chosen solvent. Within the superstructure, technologies are divided into four stages, namely, impurity removal, recovery, purification, and refinement. Technologies are mathematically modeled in the General Algebraic Modeling Systems (GAMS) software as a mixed-integer nonlinear programming (MINLP) problem. Through the implementation of binary variables, which are used for making a âyesâ or ânoâ decision, we can select an optimal path that simultaneously quantifies the environmental impact, cost, and recovery of the recycling process and meet quality specifications.
To validate the proposed framework, a case study of poly (ethylene terephthalate) (PET) recycling was developed and analyzed. In this case study, ethyl benzoate was used as a solvent for PET dissolution. The proposed process consists of two steps: (1) a dye removal and (2) polymer recovery. PET waste is first subjected to a dye removal step by dissolution through a solvent ethyl benzoate at 120ºC. We can simultaneously quantify the potential environmental advantages of the process along with the cost to obtain PET recovery of up to 80% in addition to solvent recyclability benefits.
To address this issue, we present a superstructure optimization approach for the recovery and recycling of plastic. With this framework, we categorize and compare different separation technologies based on driving forces, efficiencies, feed properties, and group them into stages. Not only do we consider the technologies used but also the physicochemical properties of the chosen solvent. Within the superstructure, technologies are divided into four stages, namely, impurity removal, recovery, purification, and refinement. Technologies are mathematically modeled in the General Algebraic Modeling Systems (GAMS) software as a mixed-integer nonlinear programming (MINLP) problem. Through the implementation of binary variables, which are used for making a âyesâ or ânoâ decision, we can select an optimal path that simultaneously quantifies the environmental impact, cost, and recovery of the recycling process and meet quality specifications.
To validate the proposed framework, a case study of poly (ethylene terephthalate) (PET) recycling was developed and analyzed. In this case study, ethyl benzoate was used as a solvent for PET dissolution. The proposed process consists of two steps: (1) a dye removal and (2) polymer recovery. PET waste is first subjected to a dye removal step by dissolution through a solvent ethyl benzoate at 120ºC. We can simultaneously quantify the potential environmental advantages of the process along with the cost to obtain PET recovery of up to 80% in addition to solvent recyclability benefits.