Structural and Electronic Property Study of (ZnO)_n, n ≤ 168: Transition from Zinc Oxide Molecular Clusters to Ultrasmall Nanoparticles

Abstract

Global minimum energy structures of (ZnO) n , n ≤ 168, were determined by using a hybrid genetic algorithm followed by a local geometry optimization at the density functional theory level. New “magic number” structures were found for the (ZnO) n clusters and ultrasmall nanoparticles. Particles with morphologies of single-, double-, and triple-layered octahedral cages exhibit higher stability than particles with other morphologies. (ZnO)132 and (ZnO)168 are found to be triple-layer cages with a diameter of ∼2 nm in each dimension. The normalized clustering energies (average cohesive energies) of the multilayered zinc oxide cages can be extrapolated to provide an estimate of the bulk limit. The surface energy densities of the ultrasmall nanoparticles are almost constant. The relatively high stability of the multilayered particles is attributed to the lack of terminal surface atoms and the effective interlayer stacking of hexagonal cells, as the layers in the particles are intact and hexagonally tiled. The epitaxial structural evolution pattern for zinc oxide ultrasmall nanoparticles can be used to predict the most energetically favorable structural evolution pathways connecting clusters and nanoparticles with different morphologies. It is hypothesized that zinc oxide nanoparticles with different morphologies (such as cylinder and octahedron) can be synthesized by using different seeds to initialize the epitaxial growth. The zinc oxide nanoparticles synthesized following our proposed growth mechanism will be predominately terminated by the wurtzite 0001 surface. The band gap of a spherical zinc oxide nanoparticle is predicted to be a linear function of the inverse of the nanoparticle diameter.

Energy landscape of ZnO clusters and low-density polymorphs

“…For (ZnO) 12 , the energy difference between (ii) and GM is one order of magnitude higher than for n = 16 and 24, which agrees well with the results in the literature 30,41 . Due to its high stability, (ZnO) 12 is also referred to as a "magic" cluster 34 , where the GM is fully trigonally coordinated but the second lowest energy structure (12 (ii)) is not. The second lowest-energy structure of (ZnO) 12 and (ZnO) 24 clusters are both distorted cages consisting primarily of squares, hexagons and octagons.…”

“…Overall, the results agree that a structural crossover from 2D rings to 3D cages/tubes occurs at n = 8, the origin of which has been extensively discussed in the literature 30 . With increasing computational resources, larger clusters have recently been investigated, both using global geometry optimization methods as well as on hypothetical fullerene structures and clusters cut from bulk [31][32][33][34] .…”

“…Despite the extensive work on ZnO materials in the literature, large part of the configurational space in ZnO still remains unexplored due to the high complexity of its potential energy landscape. In fact, for large clusters (ZnO) n with n > 32 the reported structures and therefore their properties are mostly derived from chemical intuition 41 , and only limited studies using a systematic structure search method have been performed 34 due to the high computational cost. To address this issue, in this work we trained a highly transferable, efficient interatomic neural network potential based on the charge equilibration via neural network technique (CENT) 42,43 , which allowed us to deal with large systems.…”

ZnO and TiO2 clusters as catalyst in the addition and abstraction reaction of acrylic acid with the OH radical

“…From the literature survey, it is well described about the formation of both ZnO [Refs. 36,37] and TiO 2 [Refs. [38][39][40][41] bare metal oxide clusters.…”

What is the best or most relevant global minimum for nanoclusters? Predicting, comparing and recycling cluster structures with WASP@N

“…[1][2][3][4] Crucially, each system can be described as an energy landscape and the initial target or targets are the location of the global minimum (GM) or the locations of low energy local minima (LM). 5 Today when one wants to study a new compound of interest within certain sets of parameters, including stoichiometry, size, environment, etc., a key question springs to mind: is it worth running new simulations that employ one or several contemporary global structure optimisation algorithms?…”