Revealing the Emergence and Dynamics of Nanoparticle Moiré Patterns at the Nanoscale

Moiré patterns from misaligned periodic structures can bring merit to not only artistic designs but to material properties, a salient example being magic angle graphene where superconducting phase can be observed. Here, with liquid-phase transmission electron microscope (TEM), we construct nanoparticle superlattices and obtain for the first time Moiré patterns at the nanoscale in real time and real space, where we investigate laws of order emergence and evolution from a dispersion of nanosized entities. To be specific, layers of hexagonal lattices are assembled from individual gold nanoparticles. Distinct from 2D materials where the interlayer and intralayer interactions are with limited control, we control the nanoparticle shape to manipulate the interlayer and intralayer interactions, which leads to different Moiré patterns. We apply neural network-based machine learning to investigate the structures and single particle dynamics with high spatiotemporal resolution, which further helps to reveal the interplay between the Moiré pattern and the grain boundary evolution. Furthermore, calculations based on pairwise interaction potential show distinct local position adjustment in different Moiré patterns both in plane and out of plan, resulting in normal, reduced order and disordered Moiré patterns. This work provides better understandings on nanoscale interactions, which can serve as a guideline for bottom-up material design and helps to study related optical properties.