Резюме:

in recent years, artificial intelligence (AI) and machine learning (ML) technologies have been increasingly integrated into chemical and petrochemical industries. This trend is driven by the need for improved efficiency, automation, and safety in technological processes. The purpose of this study is to review the application of AI methods in analyzing and predicting chemical reactions, as well as in managing technological systems. The research methodology is based on the analysis and synthesis of recent publications and practical case studies of AI implementation in industrial chemistry. Examples of supervised and unsupervised learning, generative models, and predictive systems are considered. It is demonstrated that AI algorithms can accurately forecast material properties, design new compounds, optimize reaction conditions, and detect potential industrial risks. The findings confirm the high efficiency of AI and ML integration into the chemical sector, providing significant cost reduction and quality improvement. The paper concludes with an outlook on the future development of these technologies in chemical engineering.

Keywords: artificial intelligence, machine learning, chemical engineering, optimization, predictive analytics.

Fedorova A.E. ¹, Fattakhov I.G. ¹ APPLICATION OF MACHINE LEARNING, ARTIFICIAL INTELLIGENCE IN THE CHEMICAL INDUSTRY // Природные энергоносители и углеродные материалы & Natural energy sources and carbon materials. – 2025. – № 02;
URL: energy-sources.esrae.ru/140-330 (Date Access: 14.12.2025).

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