Abstract
In the last decades, nanoparticles (NPs) have been assembled into clusters, low-dimensional superstructures, crystallites, and bulk materials. Typically, the self-assembly processes are controlled by competing and relatively complex interactions acting between the nanoscale components, which depend on the types of NPs, solvents, and external fields. Here, we show how selected mean-field, coarse-grained, atomistic, and quantum simulation methods are used at different scales to describe systems of self-assembling NPs studied experimentally. These simulation methods can provide in-depth understanding of the processes active during the formation of these systems.
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