Silicon Substitution in Nanotubes and Graphene via Intermittent Vacancies

Single atoms and metal nanoclusters anchored to graphene vacancies

Fabricating dispersed single atoms and size-controlled metal nanoclusters remains a difficult challenge due to sintering. Here, we demonstrate that atoms and clusters can be immobilized using atomically clean defect-engineered graphene as the matrix. The graphene is first cleaned of surface contamination with laser heating, after which low-energy Ar irradiation is used to create spatially well-separated vacancies into it. Metal atoms are then evaporated either via thermal or ebeam evaporation onto graphene, where they diffuse until being trapped into a vacancy. The density of embedded structures can be controlled through irradiation dose, and the size of the structures through evaporation time. The resulting structures are confirmed through atomic-resolution scanning transmission electron microscopy and electron energy loss spectroscopy. We demonstrate here incorporation of Al, Ti, Fe, Ag and Au single atoms or nanoclusters, but the method should work equally well for other elements.

Two-dimensional few-atom noble gas clusters in a graphene sandwich

The van der Waals atomic solids of noble gases on metals at cryogenic temperatures were the first experimental examples of two-dimensional systems. Recently, such structures have also been created on surfaces under encapsulation by graphene, allowing studies at elevated temperatures through scanning tunnelling microscopy. However, for this technique, the encapsulation layer often obscures the arrangement of the noble gas atoms. Here we create Kr and Xe clusters in between two suspended graphene layers, and uncover their atomic structure through transmission electron microscopy. We show that small crystals (N < 9) arrange on the basis of the simple non-directional van der Waals interaction. Larger crystals show some deviations, possibly enabled by deformations in the encapsulating graphene lattice. We further discuss the dynamics of the clusters within the graphene sandwich, and show that although all the Xe clusters with up to N ≈ 100 remain solid, Kr clusters with already N ≈ 16 turn occasionally fluid under our experimental conditions (under a pressure of ~0.3 GPa). This study opens a way for the so-far unexplored frontier of encapsulated two-dimensional van der Waals solids with exciting possibilities for fundamental condensed-matter physics research and possible applications in quantum information technology.

Electron delocalization in defect-containing graphene and its influence on tetrel bond formation

Using the advanced analyses of electron density and fermionic potential, we show how electron delocalization influences the ability of defect-containing graphene to form tetrel bonds. The Cg atoms of a vacancy defect can produce one nonpolar interaction, alongside a peculiar polar Cg⋯Cg bond. The latter stems from the presence of a localized electron pair on a vacancy defect Cg atom and the local depletion of electron localization on another Cg atom. This interaction is an example of intralayer tetrel bond. In the presence of an absorbed molecule of bisphenol A diglycidyl ether (DGEBA), graphene is able to form incipient tetrel Cg⋯O bonds with an ether group oxygen. In contrast to an epoxy group oxygen, the disposition of the ether oxygen often causes the orientation of electron-rich π-domains of graphene carbon on the weakly expressed electrophilic region of the oxygen. In the case of graphene with a point Si defect, the Si atom can form quite strong Si⋯C interactions with the DGEBA aryl carbons. In contrast to other noncovalent bonds, this interaction significantly alters the electron (de)localization on the Si atom and in the aryl ring. The reliability of the obtained results is enhanced by the use of multiple 2D periodic models with defects located at different positions along the DGEBA skeleton.

Atom-by-Atom Direct Writing

Direct-write processes enable the alteration or deposition of materials in a continuous, directable, sequential fashion. In this work, we demonstrate an electron beam direct-write process in an aberration-corrected scanning transmission electron microscope. This process has several fundamental differences from conventional electron-beam-induced deposition techniques, where the electron beam dissociates precursor gases into chemically reactive products that bond to a substrate. Here, we use elemental tin (Sn) as a precursor and employ a different mechanism to facilitate deposition. The atomic-sized electron beam is used to generate chemically reactive point defects at desired locations in a graphene substrate. Temperature control of the sample is used to enable the precursor atoms to migrate across the surface and bond to the defect sites, thereby enabling atom-by-atom direct writing.

Identifying and manipulating single atoms with scanning transmission electron microscopy

The manipulation of individual atoms has developed from visionary speculation into an established experimental science. Using focused electron irradiation in a scanning transmission electron microscope instead of a physical tip in a scanning probe microscope confers several benefits, including thermal stability of the manipulated structures, the ability to reach into bulk crystals, and the chemical identification of single atoms. However, energetic electron irradiation also presents unique challenges, with an inevitable possibility of irradiation damage. Understanding the underlying mechanisms will undoubtedly continue to play an important role to guide experiments. Great progress has been made in several materials including graphene, carbon nanotubes, and crystalline silicon in the eight years since the discovery of electron-beam manipulation, but the important challenges that remain will determine how far we can expect to progress in the near future.

Nanotube Functionalization: Investigation, Methods and Demonstrated Applications

This review presents an update on nanotube functionalization, including an investigation of their methods and applications. The review starts with the discussion of microscopy and spectroscopy investigations of functionalized carbon nanotubes (CNTs). The results of transmission electron microscopy and scanning tunnelling microscopy, X-ray photoelectron spectroscopy, infrared spectroscopy, Raman spectroscopy and resistivity measurements are summarized. The update on the methods of the functionalization of CNTs, such as covalent and non-covalent modification or the substitution of carbon atoms, is presented. The demonstrated applications of functionalized CNTs in nanoelectronics, composites, electrochemical energy storage, electrode materials, sensors and biomedicine are discussed.

Beam-driven Dynamics of Aluminium Dopants in Graphene

Substituting heteroatoms into graphene can tune its properties for applications ranging from catalysis to spintronics. The further recent discovery that covalent impurities in graphene can be manipulated at atomic precision using a focused electron beam may open avenues towards sub-nanometer device architectures. However, the preparation of clean samples with a high density of dopants is still very challenging. Here, we report vacancy-mediated substitution of aluminium into laser-cleaned graphene, and without removal from our ultra-high vacuum apparatus, study their dynamics under 60 keV electron irradiation using aberration-corrected scanning transmission electron microscopy and spectroscopy. Three- and four-coordinated Al sites are identified, showing excellent agreement with ab initio predictions including binding energies and electron energy-loss spectrum simulations. We show that the direct exchange of carbon and aluminium atoms predicted earlier occurs under electron irradiation, although unexpectedly it is less probable than the same process for silicon. We also observe a previously unknown nitrogen-aluminium exchange that occurs at Al─N double-dopant sites at graphene divacancies created by our plasma treatment.

Towards automating structural discovery in scanning transmission electron microscopy *

Scanning transmission electron microscopy is now the primary tool for exploring functional materials on the atomic level. Often, features of interest are highly localized in specific regions in the material, such as ferroelectric domain walls, extended defects, or second phase inclusions. Selecting regions to image for structural and chemical discovery via atomically resolved imaging has traditionally proceeded via human operators making semi-informed judgements on sampling locations and parameters. Recent efforts at automation for structural and physical discovery have pointed towards the use of ‘active learning’ methods that utilize Bayesian optimization with surrogate models to quickly find relevant regions of interest. Yet despite the potential importance of this direction, there is a general lack of certainty in selecting relevant control algorithms and how to balance a priori knowledge of the material system with knowledge derived during experimentation. Here we address this gap by developing the automated experiment workflows with several combinations to both illustrate the effects of these choices and demonstrate the tradeoffs associated with each in terms of accuracy, robustness, and susceptibility to hyperparameters for structural discovery. We discuss possible methods to build descriptors using the raw image data and deep learning based semantic segmentation, as well as the implementation of variational autoencoder based representation. Furthermore, each workflow is applied to a range of feature sizes including NiO pillars within a La:SrMnO3 matrix, ferroelectric domains in BiFeO3, and topological defects in graphene. The code developed in this manuscript is open sourced and will be released at github.com/nccreang/AE_Workflows.

Atomic-Level Structural Engineering of Graphene on a Mesoscopic Scale

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.

Exploring order parameters and dynamic processes in disordered systems via variational autoencoders

We suggest and implement an approach for the bottom-up description of systems undergoing large-scale structural changes and chemical transformations from dynamic atomically resolved imaging data, where only partial or uncertain data on atomic positions are available. This approach is predicated on the synergy of two concepts, the parsimony of physical descriptors and general rotational invariance of noncrystalline solids, and is implemented using a rotationally invariant extension of the variational autoencoder applied to semantically segmented atom-resolved data seeking the most effective reduced representation for the system that still contains the maximum amount of original information. This approach allowed us to explore the dynamic evolution of electron beam-induced processes in a silicon-doped graphene system, but it can be also applied for a much broader range of atomic scale and mesoscopic phenomena to introduce the bottom-up order parameters and explore their dynamics with time and in response to external stimuli.

Direct imaging of light-element impurities in graphene reveals triple-coordinated oxygen

Along with hydrogen, carbon, nitrogen and oxygen are the arguably most important elements for organic chemistry. Due to their rich variety of possible bonding configurations, they can form a staggering number of compounds. Here, we present a detailed analysis of nitrogen and oxygen bonding configurations in a defective carbon (graphene) lattice. Using aberration-corrected scanning transmission electron microscopy and single-atom electron energy loss spectroscopy, we directly imaged oxygen atoms in graphene oxide, as well as nitrogen atoms implanted into graphene. The collected data allows us to compare nitrogen and oxygen bonding configurations, showing clear differences between the two elements. As expected, nitrogen forms either two or three bonds with neighboring carbon atoms, with three bonds being the preferred configuration. Oxygen, by contrast, tends to bind with only two carbon atoms. Remarkably, however, triple-coordinated oxygen with three carbon neighbors is also observed, a configuration that is exceedingly rare in organic compounds.

Annular dark field scanning transmission electron microscopy is able to distinguish the contrasts between light elements. Here, the authors directly image the bonding configurations of oxygen and nitrogen atoms in defective graphene, and surprisingly identify instances of unusual triple-coordinated oxygen with three carbon neighbors.