Global Optimization of Initial Conditions of RAFT Polymerization Process

This works presents a survey on global optimization methods applied to the operation of a polymerization batch reactor. Usually operational variables as temperature and pressure are used to optimize reaction time and conversion using fixed initial concentrations and parameters usually inherited from the lab work. In this effort, the initial conditions are optimized as a first step toward the optimization of the process. To achieve this goal the method starts with a comprehensive solution for the RAFT (Reversible Addition-Fragmentation chain Transfer) polymerization in a batch reactor using the moment method model. The complex model provides concentrations Initiator Monomer, dead and slept polymer and polydispersity and average molecular weight and lenght among others. The model is then used to perform optimization of the initial operating conditions using Differential Evolution (DE), Simulated Annealing (SA) algorithm, Particle Swarm (PS) and the Barter Algorithm (BA). With this information it is intended to implement a methodology for process optimization to enhance its use in industry. The RAFT process is known to provide a chemical control of the most important parameters, however if it is intended to use in the industry it is necessary to propose control systems and optimal initial conditions and operation to ensure product quality and therefore its sustainability and profitability.