Signatures of multiple jumps in surface diffusion on honeycomb surfaces

Townsend, Peter S. M.; Avidor, Nadav

doi:10.1103/physrevb.99.115419

Cited by 6 publications

(5 citation statements)

References 79 publications

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“…With the above observations in mind, it is possible to devise a dynamical model of the trimer, based on continuous (possibly diffusive) motion, punctuated by instantaneous flips (possibly incorporating the correlations just discussed), to compare with experiments (55)(56)(57)(58)(59)(60)(61)(62)(63)(64). This model is discussed further in the Supplementary Materials (51).…”

Section: Trimers: Flipping On a Honeycomb Latticementioning

confidence: 99%

Dynamics and interactions of Quincke roller clusters: From orbits and flips to excited states

2023

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Active matter systems may be characterized by the conversion of energy into active motion, e.g., the self-propulsion of microorganisms. Artificial active colloids form models that exhibit essential properties of more complex biological systems but are amenable to laboratory experiments. While most experimental models consist of spheres, active particles of different shapes are less understood. Furthermore, interactions between these anisotropic active colloids are even less explored. Here, we investigate the motion of active colloidal clusters and the interactions between them. We focus on self-assembled dumbbells and trimers powered by an external dc electric field. For dumbbells, we observe an activity-dependent behavior of spinning, circular, and orbital motions. Moreover, collisions between dumbbells lead to the hierarchical self-assembly of tetramers and hexamers, both of which form rotational excited states. On the other hand, trimers exhibit flipping motion that leads to trajectories reminiscent of a honeycomb lattice.

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Section: Trimers: Flipping On a Honeycomb Latticementioning

confidence: 99%

Dynamics and interactions of Quincke roller clusters: From orbits and flips to excited states

2023

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“…The walking style of these problems considers a simple random walk, that is, moving from a node to its nearest neighbor (NN) node. However, in real problems, particle diffusion may produce jumping behavior, that is, moving from a node to its non-nearest-neighbor (NNN) node, such as effective path selection in social traffic, extension of the effective path of wireless devices to the current, stability of the ferromagnetic ground state of organic ferromagnetic materials, surface diffusion of physical metals [29][30][31], preventing the spread and metastasis of cancer cells [4], etc. Wu et al studied the non-neighbor wandering trap problem on a class of 3-level SG networks [32], and obtained the analytic expression of the corresponding index.…”

Section: Introductionmentioning

confidence: 99%

The average trapping time of non-nearest-neighbor jumps on nested networks

Han,

2023

Phys. Scr.

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In this paper, we consider the trapping problem on the nearest-neighbor (NN) and non-nearest-neighbor (NNN) jumps on nested networks. Based on the nested construction of the network and the use of probability generating function tool, the iterative rules of two successive generations of the network are found, and the analytical expression of the average trapping time (ATT) is finally obtained. We allow two jump modes in the network at the same time, and the results show that the choice probability of the jump mode is not related to the exponential term of the scaling expression, but to its leading factor term. According to the analytic solution of ATT, we can find that the value of ATT expands superlinearly with the increase of network size. In addition, the numerical simulation results of parameters q (the probability of choosing NNN jump) and n (the generation of the network) show that with fixed n, ATT decreases with the increase of q; while with fixed q, ATT increases with the increase of n. In summary, this work can observe the effect of different hopping modes on random walk efficiency in complex networks.

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“…Further to Tuddenham et.al., Townsend and Avidor [12] have extended the hollow-site diffusion model to include up to fourth-order jumps. They have provided explicit expressions that allow calculation of [13], there are systems in which adsorbates jump between the top and bridge sites.…”

Section: Introductionmentioning

confidence: 99%

JDAM - Jump Diffusion by Analytic Models

Wang,

Avidor

2020

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Signatures of multiple jumps in surface diffusion on honeycomb surfaces

Cited by 6 publications

References 79 publications

Dynamics and interactions of Quincke roller clusters: From orbits and flips to excited states

Dynamics and interactions of Quincke roller clusters: From orbits and flips to excited states

The average trapping time of non-nearest-neighbor jumps on nested networks

JDAM - Jump Diffusion by Analytic Models

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