Zhao Qian-Cheng, Chen Lin, Ma Sicong, Liu Zhi-Pan
State Key Laboratory of Porous Materials for Separation and Conversion, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, Key Laboratory of Computational Physical Science, Department of Chemistry, Fudan University, Shanghai, 200433, China.
State Key Laboratory of Metal Organic Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 200032, China.
Nat Commun. 2025 Apr 19;16(1):3720. doi: 10.1038/s41467-025-58960-7.
Zeolite-confined metal is an important class of heterogeneous catalysts, demonstrating exceptional catalytic performance in many reactions, but the identification of a stable metal-zeolite combination with a simple synthetic method remains a top challenge. Here artificial intelligence methods, particularly global neural network potential based large-scale atomic simulation, are utilized to design Pt-containing zeolite frameworks for propane-to-propene conversion. We show that out of the zeolite database (>220 structure framework) and more than 100,000 Pt/Ge differently distributed configurations, there are only three Ge-containing zeolites, germanosilicate (MFI, IWW and SAO) that are predicted to be capable of stabilizing Pt single atom embedded in zeolite skeleton and at the meantime allowing propane fast diffusion. Among, the Pt@Ge-MFI catalyst is successfully synthesized via a simple one-pot synthesis without a lengthy post-treatment procedure, and characterized by high-resolution experimental techniques. We demonstrate that the catalyst features an in-situ formed [GePtOH] active site under the reductive reaction condition that can achieve long-term (>750 h) high activity and selectivity (98%) for propane dehydrogenation. Our simple catalyst synthesis holds promise for scale-up industrial applications that can now be rooted in first principles via data-driven catalyst design.
沸石限域金属是一类重要的多相催化剂，在许多反应中表现出卓越的催化性能，但通过简单合成方法确定稳定的金属-沸石组合仍然是一项首要挑战。在此，利用人工智能方法，特别是基于全局神经网络势的大规模原子模拟，来设计用于丙烷制丙烯转化的含铂沸石骨架。我们表明，在沸石数据库（>220种结构骨架）和超过100,000种不同分布的Pt/Ge构型中，只有三种含锗沸石，即锗硅沸石（MFI、IWW和SAO）预计能够稳定嵌入沸石骨架中的铂单原子，并同时允许丙烷快速扩散。其中，Pt@Ge-MFI催化剂通过简单的一锅法成功合成，无需冗长的后处理程序，并采用高分辨率实验技术进行了表征。我们证明，该催化剂在还原反应条件下具有原位形成的[GePtOH]活性位点，可实现丙烷脱氢的长期（>750小时）高活性和选择性（98%）。我们简单的催化剂合成方法有望实现规模化工业应用，现在可以通过数据驱动的催化剂设计扎根于第一性原理。
