Accelerated stochastic simulation of free radical polymerization through a hybrid algorithm

Stochastic Simulation Algorithms (SSA) are a cornerstone in simulating Free Radical Polymerization (FRP) due to their accuracy and reliability. However, computational inefficiency remains a challenge for large-scale and complex polymerization systems. This work introduces a novel stochastic simulation algorithm designed to significantly enhance computational efficiency while maintaining high accuracy. By streamlining simulation processes, the proposed algorithm reduces computational time and extends the scalability of stochastic methods. Beyond FRP, the algorithm is also applied to Degenerative Transfer (DT) systems as a demonstration of its versatility. These results showcase the algorithm's potential as a universal tool for accelerating stochastic simulations in polymer science, enabling deeper insights and broader applications across various polymerization processes.