Assembling Di- and Multiatomic Si Clusters in Graphene via Electron Beam Manipulation

We demonstrate assembly of di-, tri- and tetrameric Si clusters on the graphene surface using sub-atomically focused electron beam of a scanning transmission electron microscope. Here, an electron beam is used to introduce Si substitutional defects and defect clusters in graphene with spatial control of a few nanometers, and enable controlled motion of Si atoms. The Si substitutional defects are then further manipulated to form dimers, trimers and more complex structures. The dynamics of a beam induced atomic scale chemical process is captured in a time-series of images at atomic resolution. These studies suggest that control of the e-beam induced local processes offers the next step toward atom-by-atom nanofabrication and provides an enabling tool for study of atomic scale chemistry in 2D materials

The Synthescope: A Vision for Combining Synthesis with Atomic Fabrication

The scanning transmission electron microscope, a workhorse instrument in materials characterization, is being transformed into an atomic-scale material manipulation platform. With an eye on the trajectory of recent developments and the obstacles toward progress in this field, we provide a vision for a path toward an expanded set of capabilities and applications. We reconceptualize the microscope as an instrument for fabrication and synthesis with the capability to image and characterize atomic-scale structural formation as it occurs. Further development and refinement of this approach may have substantial impact on research in microelectronics, quantum information science, and catalysis where precise control over atomic scale structure and chemistry of a few "active sites" can have a dramatic impact on larger scale functionality and where developing a better understanding of atomic scale processes can help point the way to larger scale synthesis approaches

Single atom manipulation and control in a scanning transmission electron microscope

We demonstrate that the sub-atomically focused beam of a scanning transmission electron microscope (STEM) can be used to controllably manipulate individual dopant atoms in a 2D graphene lattice. We demonstrate the manipulation of adsorbed source materials and the graphene lattice with the electron beam such that individual vacancy defects can be controllably passivated by Si substitutional atoms. We further demonstrate that these Si defects may be directed through the lattice via e-beam control or modified (as yet, uncontrollably) to form new defects which can incorporate new atoms into the graphene lattice. These studies demonstrate the potential of STEM for atom-by-atom nanofabrication and fundamental studies of chemical reactions in 2D materials on the atomic level

Atomic mechanisms for the Si atom dynamics in graphene: chemical transformations at the edge and in the bulk

Recent advances in scanning transmission electron microscopy (STEM) allow to observe solid-state transformations and reactions in materials induced by thermal stimulus or electron beam on the atomic level. However, despite the rate at which large volumes of data can be generated (sometimes in the gigabyte to terabyte range per single experiment), approaches for the extraction of material-specific knowledge on the kinetics and thermodynamics of these processes are still lacking. One of the critical issues lies in being able to map the evolution of various atomic structures and determine the associated transition probabilities directly from raw experimental data characterized by high levels of noise and missing structural elements. Here, we demonstrate an approach based on the combination of multiple machine learning techniques to study the dynamic behavior of e-beam irradiated Si atoms in the bulk and at the edges of single-layer graphene in STEM experiments. First, a deep learning network is used to convert experimental STEM movies into coordinates of individual Si and carbon atoms. Then, a Gaussian mixture model is further used to establish the elementary atomic configurations of the Si atoms, defining the bonding geometries and chemical species and accounting for the discrete rotational symmetry of the host lattice. Finally, the frequencies and Markov transition probabilities between these states are determined. This analysis enables insight into the thermodynamics of defect populations and chemical reaction networks from the atomically resolved STEM data. Here, we observe a clear tendency for the formation of a 1D Si crystal along zigzag direction of graphene edges and for the Si impurity coupling to topological defects in bulk graphene