EXPERIMENTAL STUDY ON THE APPLICATION OF MACHINE LEARNING METHOD IN CATALYTIC MATERIALS

Aihua Zhang

ABSTRACT:Machine learning has emerged as a powerful tool for analyzing complex data sets and making predictions in a wide range of applications, including catalysis. Bycombining statistical methods, algorithms, and computational power, machine learning can help identify patterns and relationships in catalytic systems that are difficult or impossible to discern using traditional approaches. This can lead to more efficient and effective catalyst design, optimization, and prediction of catalytic activity. Machine learning has already been successfully applied to various aspects of catalysis, including catalyst discovery, reaction mechanism identification, and kinetic modeling. The continued integration of machine learning with catalysis research holds great promise for advancing our understanding of catalytic systems and developing new and improved catalysts for important industrial processes.

Keywords:Machine Learning, catalytic materials, chemistry, efficiency, catalytic.