Atomic-Level Structural Engineering of Graphene on a Mesoscopic Scale

Abstract

Structural engineering is the first step toward changing properties of materials. While this can be at relative ease done for bulk materials, for example, using ion irradiation, similar engineering of 2D materials and other low-dimensional structures remains a challenge. The difficulties range from the preparation of clean and uniform samples to the sensitivity of these structures to the overwhelming task of sample-wide characterization of the subjected modifications at the atomic scale. Here, we overcome these issues using a near ultrahigh vacuum system comprised of an aberration-corrected scanning transmission electron microscope and setups for sample cleaning and manipulation, which are combined with automated atomic-resolution imaging of large sample areas and a convolutional neural network approach for image analysis. This allows us to create and fully characterize atomically clean free-standing graphene with a controlled defect distribution, thus providing the important first step toward atomically tailored two-dimensional materials.

Defect-Dependent Corrugation in Graphene

“…Graphene’s remarkable properties strongly depend on its morphology with many physical phenomena arising as a consequence of its intrinsic ripples and corrugation − or by the presence of defects. − For instance, introducing eight-membered-ring defects can enhance graphene’s ion permeability. − This makes graphene an ideal candidate for nanoengineering where material properties are tuned by modifying the atomic morphology. , To this end, a plethora of experimental techniques has emerged ranging from the atomically precise insertion of defects via electron beam − or ion bombardment ,− to chemical etching with KOH , and the regulation of rippling patterns by inducing strain . More recent approaches like laser-assisted chemical vapor deposition or high-temperature quenching go one step further by incorporating the desired morphology a priori in the growth process.…”

Carbon Nano-onions: Potassium Intercalation and Reductive Covalent Functionalization

“…They were then moved in the argon atmosphere to the vacuum system connected to the microscope. 61 Pristine samples were transferred through air. All images were recorded with an acceleration voltage of 60 kV using the medium angle annular dark field (MAADF) detector.…”

An Automated Scanning Transmission Electron Microscope Guided by Sparse Data Analytics

“…Among its many applications, ML has been used to effectively quantify and track atomic-scale structural motifs 49,50 , and has shown recent successes as part of automated microscope platforms. 39,51 Despite these benefits, CNNs are inherently constrained, since they typically require large volumes (100 to > 10k images) of tediously hand-labeled or simulated training data. 52 Due to the wide variety of experiments and systems studied in the microscope, such data is often time-consuming or impossible to acquire.…”