SIMULATION OF CHEMICAL REACTIONS AND THE ROLE OF ARTIFICIAL INTELLIGENCE

الملخص

Deep understanding of the nature of chemical reactions, determination of their kinetic characteristics, and prediction of interatomic changes at each stage of the process is considered one of the most complex areas of modern chemistry. In traditional laboratory conditions, such studies require significant time and resources and often involve the use of hazardous substances. Therefore, simulating chemical reactions in a virtual environment has become an integral part of contemporary science. Using simulation technologies, intermolecular interactions, energy changes, stability of intermediate complexes, and the properties of products formed in reactions can be rapidly evaluated using mathematical models. In recent years, the development of artificial intelligence (AI) has taken this process to a new level. AI algorithms can independently learn from various chemical databases, classify reactions, propose new reaction pathways, evaluate the stability of molecular structures, and generate optimal synthesis strategies. In particular, deep learning and generative models provide the ability to identify the most favorable conditions for synthesizing complex organic compounds, optimize catalyst activity, and predict the properties of pharmaceutical substances in advance. Additionally, AI-based simulation platforms improve efficiency by processing experimental results in real time, deriving generalized conclusions, and planning new experiments. This work elaborates on the scientific and practical significance of AI tools in chemical simulations. The study analyzes the strengths and weaknesses of AI models, ways to improve computational accuracy, new approaches to visualizing intermolecular changes, and the prospects of applying these tools in chemical industry, ecology, and pharmaceuticals. The results demonstrate that AI in chemical process prediction is emerging not only as an auxiliary tool but also as a generator of new scientific ideas.