Atomistic simulations of the structures of Pd-Pt bimetallic nanoparticles and nanowires
Kayoung Yun, Pil-Ryung Cha, Jaegab Lee, Jiyoung Kim, and Ho-Seok Nam

TL;DR
This study uses simulated annealing Monte Carlo simulations to predict stable atomic structures of Pd-Pt bimetallic nanoparticles and nanowires, revealing quasi-ordered configurations and surface segregation effects relevant for catalysis and nanoelectronics.
Contribution
It provides the first detailed computational analysis of atomic arrangements in Pd-Pt nanoalloys, highlighting structural preferences and segregation phenomena.
Findings
Nanoparticles and nanowires show quasi-ordered structures similar to bulk alloys.
Surface segregation significantly influences atomic configurations.
Predicted structures can guide the design of bimetallic nanomaterials.
Abstract
Bimetallic nanoalloys such as nanoparticles and nanowires are attracting significant attention due to their vast potential applications such as in catalysis and nanoelectronics. Notably, Pd-Pt nanoparticles/nanowires are being widely recognized as catalysts and hydrogen sensors. Compared to unary systems, alloys present more structural complexity with various compositional configurations. Therefore, it is important to understand energetically preferred atomic structures of bimetallic nanoalloys. In this study, we performed a series of simulated annealing Monte Carlo simulations to predict the energetically stable atomic arrangement of Pd-Pt nanoparticles and nanowires as a function of composition based on a set of carefully designed empirical potential models. Both the Pd-Pt nanoparticles and nanowires exhibit quasi-ordered configurations, quite similar to bulk alloy phases such as the…
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Taxonomy
Topicsnanoparticles nucleation surface interactions · Machine Learning in Materials Science · Advanced Chemical Physics Studies
