Xie Maichong, Shimogawa Ryuichi, Liu Yang, Zhang Lihua, Foucher Alexandre C, Routh Prahlad K, Stach Eric A, Frenkel Anatoly I, Knecht Marc R
Department of Chemistry, University of Miami, Coral Gables, Florida 33146, United States.
Department of Materials Science and Chemical Engineering, Stony Brook University, Stony Brook, New York 11794, United States.
ACS Nano. 2024 Jan 30;18(4):3286-3294. doi: 10.1021/acsnano.3c10016. Epub 2024 Jan 16.
The controlled design of bimetallic nanoparticles (BNPs) is a key goal in tailoring their catalytic properties. Recently, biomimetic pathways demonstrated potent control over the distribution of different metals within BNPs, but a direct understanding of the peptide effect on the compositional distribution at the interparticle and intraparticle levels remains lacking. We synthesized two sets of PtAu systems with two peptides and correlated their structure, composition, and distributions with the catalytic activity. Structural and compositional analyses were performed by a combined machine learning-assisted refinement of X-ray absorption spectra and Z-contrast measurements by scanning transmission electron microscopy. The difference in the catalytic activities between nanoparticles synthesized with different peptides was attributed to the details of interparticle distribution of Pt and Au across these markedly heterogeneous systems, comprising Pt-rich, Au-rich, and Au core/Pt shell nanoparticles. The total amount of Pt in the shells of the BNPs was proposed to be the key catalytic activity descriptor. This approach can be extended to other systems of metals and peptides to facilitate the targeted design of catalysts with the desired activity.
双金属纳米颗粒(BNP)的可控设计是调整其催化性能的关键目标。最近,仿生途径显示出对BNP中不同金属分布的有效控制,但仍缺乏对肽在颗粒间和颗粒内水平上对成分分布影响的直接理解。我们用两种肽合成了两组PtAu体系,并将它们的结构、组成和分布与催化活性相关联。通过结合机器学习辅助的X射线吸收光谱精修和扫描透射电子显微镜的Z对比测量进行结构和成分分析。用不同肽合成的纳米颗粒之间催化活性的差异归因于Pt和Au在这些明显异质体系中的颗粒间分布细节,这些体系包括富Pt、富Au和Au核/Pt壳纳米颗粒。BNP壳层中Pt的总量被认为是关键的催化活性描述符。这种方法可以扩展到其他金属和肽体系,以促进具有所需活性的催化剂的定向设计。