Self-Assembly of heterogeneous nano-chain and nano-sheet through the "breaking-to-assembling" route

Cooperative self-assembly can result in complex nano-networks with new hyperbolic geometry. However, the relation between the hyperbolicity and spectral and dynamical features of these structures remains unclear. Using the model of aggregation of simplexes introduced in I [Sci. Rep., 8:1987Rep., 8: , 2018, here we study topological and spectral properties of a large class of self-assembled structures consisting of monodisperse building blocks (cliques of size n = 3, 4, 5, 6) which self-assemble via sharing the geometrical shapes of a lower order. The size of the shared sub-structure is tunned by varying the chemical affinity ν such that for significant positive ν sharing the largest face is the most probable, while for ν < 0, attaching via a single node dominates. Our results reveal that, while the parameter of hyperbolicity remains δmax = 1 across the assemblies, their structure and spectral dimension ds vary with the size of cliques n and the affinity when ν ≥ 0. In this range, we findthat ds > 4 can be reached for n ≥ 5 and sufficiently large ν. For the aggregates of triangles and tetrahedra, the spectral dimension remains in the range ds ∈ [2, 4), as well as for the higher cliques at vanishing affinity. On the other end, for ν < 0, we find ds 1.57 independently on n. Moreover, the spectral distribution of the normalised Laplacian eigenvalues has a characteristic shape with peaks and a pronounced minimum, representing the hierarchical architecture of the simplicial complexes. These findings show how the structures compatible with complex dynamical properties can be assembled by controlling the higher-order connectivity among the building blocks.PACS numbers:

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Self-Assembly of heterogeneous nano-chain and nano-sheet through the "breaking-to-assembling" route

Cited by 2 publications

References 18 publications

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The magnetic property of CoFe2O4 assembly by the gradient magnetic field

Spectral properties of hyperbolic nanonetworks with tunable aggregation of simplexes

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