Sawant Kaustubh J, Stockwell David, Debellis Anthony, Dorazio Lucas, Sautet Philippe
Chemical and Biomolecular Engineering Department, University of California Los Angeles, California, USA.
BASF Corporation, New Jersey, USA.
Angew Chem Int Ed Engl. 2025 Sep 15;64(38):e202506711. doi: 10.1002/anie.202506711. Epub 2025 Aug 21.
Amorphous silica-alumina are critical materials in catalysis, particularly for fluid catalytic cracking (FCC). However, the atomic scale understanding of the active sites has been challenging, because of the nonuniform atomic distribution and the material's amorphous nature. Here, we use density functional theory (DFT), machine learning potentials and sampling methods to investigate the relationship between structure and acidity in silica-modified alumina. Under FCC conditions, we predict an ensemble of acid sites with diverse local structures and a spectrum of acid strengths, including zeolite-like bridging Brønsted acid sites (BAS) and pseudo-bridging silanol BAS. This distribution is influenced by surface structure, Si coverage, and extent of hydroxylation, shaped by synthesis methods and reaction conditions. Experiments using a model Si-stabilized alumina catalyst confirm that Brønsted acidity increases with Si content, peaking at an optimal value before declining. These insights provide a foundation for designing efficient solid acid catalysts for industrial applications.
无定形硅铝是催化领域的关键材料，尤其在流化催化裂化（FCC）中。然而，由于原子分布不均匀以及材料的无定形性质，对活性位点的原子尺度理解一直具有挑战性。在此，我们使用密度泛函理论（DFT）、机器学习势和采样方法来研究二氧化硅改性氧化铝中结构与酸度之间的关系。在FCC条件下，我们预测了具有不同局部结构和一系列酸强度的酸位点集合，包括类沸石桥连布朗斯特酸位点（BAS）和假桥连硅醇BAS。这种分布受表面结构、硅覆盖率和羟基化程度的影响，这些因素由合成方法和反应条件决定。使用模型硅稳定氧化铝催化剂的实验证实，布朗斯特酸度随硅含量增加而增加，在达到最佳值后达到峰值，然后下降。这些见解为设计用于工业应用的高效固体酸催化剂奠定了基础。
