Stabilization of Sub-Nanometer Pt Clusters on CoOx Nano-Islands by Area-Selective Atomic Layer Deposition and Machine Learning Insights
Abstract
Sub-nanometer metallic clusters have attracted considerable interest owing to their high surface area and size-dependent properties. However, their high surface energies cause thermal instability, leading to aggregation and sintering that limit practical applications. In this study, we obtained sub-nanometer Pt clusters (average size ∼0.76 nm) with highly stable configuration, deposited on CoO x nano-islands by area-selective deposition (ASD). The Pt-CoO x structures exhibited low Pt loading and high deposition selectivity. During ASD, Pt clusters were selectively deposited on CoO x regions, where strong metal-support interactions (MSI) between Pt and CoO x supported effective anchoring. Subsequent H 2 post-treatment promoted electron transfer between Pt and CoO x as well as Pt cluster migration from the Al 2 O 3 substrate to the CoO x nano-islands, particularly at the Al 2 O 3 -CoO x interface, further improving selectivity. Potential simulations by machine learning revealed directional Pt migration and provided atomic-level insights into stabilization mechanisms. After high-temperature (at 600 °C) aging, Pt clusters remained highly dispersed without noticeable sintering, owing to the synergistic effects of physical isolation by CoO x nano-islands and strong MSI. This synergistic strategy holds practical relevance for industrial applications and provides a robust framework for designing durable catalytic structures.
Fields of Study & Subjects
Machine Learning in Materials Science
Electrocatalysts for Energy Conversion
Advanced Chemical Physics Studies
Publication details
- Journal / source
- Engineering
- Publisher
- Elsevier BV
- Publication date
- 1 January 2026
- Language
- EN