Research on the Catalytic Coupling of Ethanol to $C4$ Olefins: A Multi-Modal Study with BP-NN-Assisted Bayesian Optimization and PSO-Driven Variational Strategies

This study focuses on the process conditions for the preparation of $C4$ olefins via ethanol-catalyzed coupling technology for the wide range of applications of $C4$ olefins in the production of chemicals and pharmaceuticals, a process of remarkable significance and value for the optimization of chemical products. In order to maximize the yield of $C4$ olefin under the given experimental conditions, this paper combines the BP neural network model of Bayesian optimization with the black-box optimization model, and further solves for the optimal catalyst combinations and reaction temperatures by the particle swarm algorithm with the introduction of a variational strategy. Through this comprehensive method, the key conditions for achieving the maximum yield of $C4$ olefins were determined, demonstrating the good application of this method in the optimization process of the chemical industry.