Structure, Thermodynamics, and Rearrangement Mechanisms in Gold Clusters-insights from the Energy Landscapes Framework
Overview
Authors
Affiliations
We consider finite-size and temperature effects on the structure of model Au 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.
Exploration of Free Energy Surface of the Au Nanocluster at Finite Temperature.
Rojas-Gonzalez F, Castillo-Quevedo C, Rodriguez-Kessler P, Jimenez-Halla J, Vasquez-Espinal A, Eithiraj R Molecules. 2024; 29(14).
PMID: 39064952 PMC: 11279810. DOI: 10.3390/molecules29143374.
Charting Nanocluster Structures via Convolutional Neural Networks.
Telari E, Tinti A, Settem M, Maragliano L, Ferrando R, Giacomello A ACS Nano. 2023; 17(21):21287-21296.
PMID: 37856254 PMC: 10655179. DOI: 10.1021/acsnano.3c05653.
Li T, Yang W, Pan J, Huang R, Shao G, Wen Y ACS Omega. 2022; 7(42):37436-37441.
PMID: 36312425 PMC: 9607661. DOI: 10.1021/acsomega.2c04214.
Buelna-Garcia C, Castillo-Quevedo C, Quiroz-Castillo J, Paredes-Sotelo E, Cortez-Valadez M, Martin-Del-Campo-Solis M Front Chem. 2022; 10:841964.
PMID: 35300385 PMC: 8921525. DOI: 10.3389/fchem.2022.841964.
Exploring AuRh Nanoalloys: A Computational Perspective on the Formation and Physical Properties.
Vanzan M, Jones R, Corni S, DAgosta R, Baletto F Chemphyschem. 2022; 23(8):e202200035.
PMID: 35156760 PMC: 9314847. DOI: 10.1002/cphc.202200035.