Abstract: Cryogenic electronmicroscopy can provide high-resolution reconstructionsof macromolecules embedded in a thin layer of ice from which atomicmodels can be built de novo. However, the interactionbetween the ionizing electron beam and the sample results in beam-inducedmotion and image distortion, which limit the attainable resolutions.Sample charging is one contributing factor of beam-induced motionsand image distortions, which is normally alleviated by including partof the supporting conducting film within the beam-exposed region.However, routine data collection schemes avoid strategies wherebythe beam is not in contact with the supporting film, whose rationaleis not fully understood. Here we characterize electrostatic chargingof vitreous samples, both in imaging and in diffraction mode. We mitigatesample charging by depositing a single layer of conductive grapheneon top of regular EM grids. We obtained high-resolution single-particleanalysis (SPA) reconstructions at 2 & ANGS; when the electron beamonly irradiates the middle of the hole on graphene-coated grids, usingdata collection schemes that previously failed to produce sub 3 & ANGS;reconstructions without the graphene layer. We also observe that theSPA data obtained with the graphene-coated grids exhibit a higher b factor and reduced particle movement compared to dataobtained without the graphene layer. This mitigation of charging couldhave broad implications for various EM techniques, including SPA andcryotomography, and for the study of radiation damage and the developmentof future sample carriers. Furthermore, it may facilitate the explorationof more dose-efficient, scanning transmission EM based SPA techniques.

Abstract: Electron tomography is an essential imaging technique for the investigation of morphology and 3D structure of nanomaterials. This method, however, suffers from well-known missing wedge artifacts due to a restricted tilt range, which limits the objectiveness, repeatability and efficiency of quantitative structural analysis. Discrete tomography represents one of the promising reconstruction techniques for materials science, potentially capable of delivering higher fidelity reconstructions by exploiting the prior knowledge of the limited number of material compositions in a specimen. However, the application of discrete tomography to practical datasets remains a difficult task due to the underlying challenging mathematical problem. In practice, it is often hard to obtain consistent reconstructions from experimental datasets. In addition, numerous parameters need to be tuned manually, which can lead to bias and non-repeatability. In this paper, we present the application of a new
iterative reconstruction technique, named TVR-DART, for discrete electron tomography. The technique is capable of consistently delivering reconstructions with significantly reduced missing wedge artifacts for a variety of challenging data and imaging conditions, and can automatically estimate its key parameters. We describe the principles of the technique and apply it to datasets from three different types of samples acquired under diverse imaging modes. By further reducing the available tilt range and number of projections, we show that the
proposed technique can still produce consistent reconstructions with minimized missing wedge artifacts. This new development promises to provide the electron microscopy community with an easy-to-use and robust tool for high-fidelity 3D characterization of nanomaterials.

Abstract: A focused electron beam in a scanning transmission electron microscope (STEM) is used to create arrays of core-shell structures in a specimen of amorphous SiO2 doped with Ge. The same electron microscope is then used to measure the changes that occurred in the specimen in three dimensions using electron tomography. The results show that transformations in insulators that have been subjected to intense irradiation using charged particles can be studied directly in three dimensions. The fabricated structures include core-shell nano-columns, sputtered regions, voids, and clusters. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4731765]