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Structure, thermodynamics, and rearrangement mechanisms in gold clusters—insights from the energy landscapes framework† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c7nr07123j
| Content Provider | Semantic Scholar |
|---|---|
| Author | Schebarchov, D. Baletto, Francesca Wales, David J. |
| Copyright Year | 2018 |
| Abstract | We consider finite-size and temperature effects on the structure of model AuN clusters (30 ≤ N ≤ 147) bound by the Gupta potential. Equilibrium behaviour is examined in the harmonic superposition approximation, and the size-dependent melting temperature is also bracketed using molecular dynamics simulations. We identify structural transitions between distinctly different morphologies, characterised by various defect features. Reentrant behaviour and trends with respect to cluster size and temperature are discussed in detail. For N = 55, 85, and 147 we visualise the topography of the underlying potential energy landscape using disconnectivity graphs, colour-coded by the cluster morphology; and we use discrete path sampling to characterise the rearrangement mechanisms between competing structures separated by high energy barriers (up to 1 eV). The fastest transition pathways generally involve metastable states with multiple fivefold disclinations and/or a high degree of amorphisation, indicative of melting. For N = 55 we find that reoptimising low-lying minima using density functional theory (DFT) alters their energetic ordering and produces a new putative global minimum at the DFT level; however, the equilibrium structure predicted by the Gupta potential at room temperature is consistent with previous experiments. |
| Starting Page | 2004 |
| Ending Page | 2016 |
| Page Count | 13 |
| File Format | PDF HTM / HTML |
| DOI | 10.1039/c7nr07123j |
| PubMed reference number | 29319705 |
| Journal | Medline |
| Volume Number | 10 |
| Alternate Webpage(s) | https://www.dspace.cam.ac.uk/bitstream/handle/1810/274567/c7nr07123j.pdf?isAllowed=y&sequence=4 |
| Alternate Webpage(s) | https://doi.org/10.1039/c7nr07123j |
| Journal | Nanoscale |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
