■ Venue :  W1-1, #2430 (주흘회의실)     

■ Abstract : 

To achieve a society based on renewable energy, the development of catalysts that are both efficient and economical is essential. Traditionally, catalysts have been developed through a trial-and-error approach guided by chemical intuition. Recently, the use of computational simulation techniques, such as Density Functional Theory (DFT) calculations, has greatly accelerated the discovery of new catalysts. However, these computational approaches come with limitations, including substantial computational costs and dependence on existing chemical databases. The advancement of Artificial Intelligence (AI) could offer a new methodology that overcomes these limitations and accelerates catalyst developments. This presentation will introduce a novel approach for catalyst discovery that combines computational simulations and AI, and will demonstrate specific examples of catalysts developed through this integrated approach. It will also discuss the future direction of AI research for the development of new catalysts.