ArticleSmart molecules : open access2025
Unveiling the unexpected sinking and embedding dynamics of surface supported Mo/S clusters on 2D MoS
Article in Smart molecules : open access, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Global descriptors informed learning for organic melting-point prediction.RSC advances · 2026Article
- An Innovative Approach to Precisely Tailor the Composition of Syngas in COAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Unveiling the unexpected sinking and embedding dynamics of surface supported Mo/S clusters on 2D MoSSmart molecules : open access · 2025Article
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Authors and funding
7 authors.
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Abstract
Surface-supported clusters forming by aggregation of excessive adatoms could be the main defects of 2D materials after chemical vapor deposition. They will significantly impact the electronic/magnetic properties. Moreover, surface supported atoms are also widely explored for high active and selecting catalysts. Severe deformation, even dipping into the surface, of these clusters can be expected because of the very active edge of clusters and strong interaction between supported clusters and surfaces. However, most models of these clusters are supposed to simply float on the top of the surface because ab initio simulations cannot afford the complex reconstructions. Here, we develop an accurate graph neural network machine learning potential (MLP) from ab initio data by active learning architecture through fine-tuning pre-trained models, and then employ the MLP into Monte Carlo to explore the structural evolutions of Mo and S clusters (1-8 atoms) on perfect and various defective MoS
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