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.

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.

As a one-atom thick, mechanically strong, and chemically stable material with unique electronic properties, graphene can serve as the basis for a large number of applications. One way to tailor its properties is the controlled introduction of covalently bound heteroatoms into the lattice. In this study, we demonstrate efficient implantation of individual gold atoms into graphene up to a concentration of 1.7×1011 atoms/cm2 via a two-step low-energy ion implantation technique that overcomes the limitation posed by momentum conservation on the mass of the implanted species. Atomic resolution scanning transmission electron microscopy imaging and electron energy-loss spectroscopy reveal gold atoms occupying double vacancy sites in the graphene lattice. The covalently bound gold atoms can sustain intense electron irradiation at 60 kV during the microscopy experiments. At best, only limited indication of plasmonic enhancement is observed. The method demonstrated here can be used to introduce a controlled concentration of gold atoms into graphene, and should also work for other heavier elements with similar electronic structure.

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Cellular micromotion—a tiny movement of cell membranes on the nm-µm scale—has been proposed as a pathway for inter-cellular signal transduction and as a label-free proxy signal to neural activity. Here we harness several recent approaches of signal processing to detect such micromotion in video recordings of unlabeled cells. Our survey includes spectral filtering of the video signal, matched filtering, as well as 1D and 3D convolutional neural networks acting on pixel-wise time-domain data and a whole recording respectively.