This review explores platinum catalysts for propane dehydrogenation, highlighting performance optimization and machine learning applications.
Propane dehydrogenation (PDH) is a key process for increasing the production of propylene, which is an important part of the chemical industry. Platinum‐based catalysts have emerged as efficient catalysts for this reaction due to their excellent activity and selectivity. However, challenges such as high platinum cost, catalyst deactivation, and side reactions remain significant barriers to their widespread use in industry. This review provides a comprehensive overview of recent advances in platinum‐based catalysts for PDH, focusing on strategies to optimize their performance. We discuss the design and synthesis of Pt‐based catalysts, emphasizing the role of promoters, such as Sn, Zn, Ga, and other promoters, in improving selectivity and stability. We also explore the effects of support materials and zeolite encapsulated catalysts on dispersion and activity for Pt‐based catalysts. In addition, we highlight the use of machine learning to predict catalyst performance and guide the development of next‐generation Pt‐based catalyst materials. This review synthesizes insights from experimental studies and machine learning computational modeling and aims to provide a route for overcoming the limitations of Pt‐based catalysts and advancing the PDH process.
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Wu et al. (2025) studied this question.
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