Optimizing the Selection of Solvents for the Dissolution and Precipitation of Polyethylene

Plastic recycling is prevalently mechanical, which is inefficient at removing contaminants and produces low-grade materials. Solvent-based polymer dissolution and precipitation is emerging as a low-energy alternative to mechanical recycling when tackling highly contaminated plastic waste streams. We present a computer-aided molecular and process design (CAMPD) formulation for the selection of optimal solvents and process temperatures for polymer recycling via a dissolution and precipitation process. A mixed-integer nonlinear programming (MINLP) model is proposed to minimize the energy requirement for the dissolution of commercial low-density polyethylene, a ubiquitous polymer in industrial and municipal plastic waste, while minimizing the solvent viscosity and toxicity through multiobjective optimization. We integrate the SAFT-??Mie group-contribution equation of state in the optimization framework to predict key thermodynamic properties and to ensure that the desired phase behaviour is achieved. A ranked list of solvents and the corresponding process temperatures is obtained using integer cuts. Two polyethylene molecular weights are considered. In each case, we construct a Pareto front to quantify the trade-offs between the energy requirements of the process and the selected solvent properties. Furthermore, we investigate the simultaneous design of the dissolution and cooling precipitation to analyse the effect of varying the precipitation temperature on the energy of dissolution. The current study provides valuable insights into selecting optimal solvents for polyethylene dissolution, advancing the design of more efficient plastic recycling processes.