Electron beam triggered single-atom dynamics in two-dimensional materials

Abstract

Abstract Controlling atomic structure and dynamics with single-atom precision is the ultimate goal in nanoscience and nanotechnology. Despite great successes being achieved by scanning tunneling microscopy (STM) over the past a few decades, fundamental limitations, such as ultralow temperature, and low throughput, significantly hinder the fabrication of a large array of atomically defined structures by STM. The advent of aberration correction in scanning transmission electron microscopy (STEM) revolutionized the field of nanomaterials characterization pushing the detection limit down to single-atom sensitivity. The sub-angstrom focused electron beam (e-beam) of STEM is capable of interacting with an individual atom, thereby it is the ideal platform to direct and control matter at the level of a single atom or a small cluster. In this article, we discuss the transfer of energy and momentum from the incident e-beam to atoms and their subsequent potential dynamics under different e-beam conditions in 2D materials, particularly transition metal dichalcogenides (TMDs). Next, we systematically discuss the e-beam triggered structural evolutions of atomic defects, line defects, grain boundaries, and stacking faults in a few representative 2D materials. Their formation mechanisms, kinetic paths, and practical applications are comprehensively discussed. We show that desired structural evolution or atom-by-atom assembly can be precisely manipulated by e-beam irradiation which could introduce intriguing functionalities to 2D materials. In particular, we highlight the recent progress on controlling single Si atom migration in real-time on monolayer graphene along an extended path with high throughput in automated STEM. These results unprecedentedly demonstrate that single-atom dynamics can be realized by an atomically focused e-beam. With the burgeoning of artificial intelligence and big data, we can expect that fully automated microscopes with real-time data analysis and feedback could readily design and fabricate large scale nanostructures with unique functionalities in the near future.