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In the scanning transmission electron microscope, both phase imaging of beam-sensitive materials and characterization of a material's functional properties using in situ experiments are becoming more widely available. As the practicable scan speed of 4D-STEM detectors improves, so too does the temporal resolution achievable for both differential phase contrast (DPC) and ptychography. However, the read-out burden of pixelated detectors, and the size of the gigabyte to terabyte sized data sets, remain a challenge for both temporal resolution and their practical adoption. In this work, we combine ultra-fast scan coils and detector signal digitization to show that a high-fidelity DPC phase reconstruction can be achieved from an annular segmented detector. Unlike conventional analog data phase reconstructions from digitized DPC-segment images yield reliable data, even at the fastest scan speeds. Finally, dose fractionation by fast scanning and multi-framing allows for postprocess binning of frame streams to balance signal-to-noise ratio and temporal resolution for low-dose phase imaging for in situ experiments.
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Low-voltage scanning electron microscopy is a powerful tool for examining surface features and imaging beam-sensitive materials. Improving resolution during low-voltage imaging is then an important area of development. Decreasing the effect of chromatic aberration is one solution to improving the resolution and can be achieved by reducing the energy spread of the electron source. Our approach involves retrofitting a light source onto a thermionic lanthanum hexaboride (LaB6) electron gun as a cost-effective low energy-spread photoelectron emitter. The energy spread of the emitter's photoelectrons is theorized to be between 0.11 and 0.38 eV, depending on the photon energy of the ultraviolet (UV) light source. Proof-of-principle images have been recorded using this retrofitted photoelectron gun, and an analysis of its performance is presented.
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Fast frame rates are desirable in scanning transmission electron microscopy for a number of reasons: controlling electron beam dose, capturing in situ events, or reducing the appearance of scan distortions. While several strategies exist for increasing frame rates, many impact image quality or require investment in advanced scan hardware. Here, we present an interlaced imaging approach to achieve minimal loss of image quality with faster frame rates that can be implemented on many existing scan controllers. We further demonstrate that our interlacing approach provides the best possible strain precision for a given electron dose compared with other contemporary approaches.
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With increasing interest in high-speed imaging, there should be an increased interest in the response times of our scanning transmission electron microscope detectors. Previous works have highlighted and contrasted the performance of various detectors for quantitative compositional or structural studies, but here, we shift the focus to detector temporal response, and the effect this has on captured images. The rise and decay times of eight detectors' single-electron response are reported, as well as measurements of their flatness, roundness, smoothness, and ellipticity. We develop and apply a methodology for incorporating the temporal detector response into simulations, showing that a loss of resolution is apparent in both the images and their Fourier transforms. We conclude that the solid-state detector outperforms the photomultiplier tube-based detectors in all areas bar a slightly less elliptical central hole and is likely the best detector to use for the majority of applications. However, using the tools introduced here, we encourage users to effectively evaluate which detector is most suitable for their experimental needs.
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Low-voltage transmission electron microscopy (≤80 kV) has many applications in imaging beam-sensitive samples, such as metallic nanoparticles, which may become damaged at higher voltages. To improve resolution, spherical aberration can be corrected for in a scanning transmission electron microscope (STEM); however, chromatic aberration may then dominate, limiting the ultimate resolution of the microscope. Using image simulations, we examine how a chromatic aberration corrector, different objective lenses, and different beam energy spreads each affect the image quality of a gold nanoparticle imaged at low voltages in a spherical aberration-corrected STEM. A quantitative analysis of the simulated examples can inform the choice of instrumentation for low-voltage imaging. We here demonstrate a methodology whereby the optimum energy spread to operate a specific STEM can be deduced. This methodology can then be adapted to the specific sample and instrument of the reader, enabling them to make an informed economical choice as to what would be most beneficial for their STEM in the cost-conscious landscape of scientific infrastructure.
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When characterizing beam-sensitive materials in the scanning transmission electron microscope (STEM), low-dose techniques are essential for the reliable observation of samples in their true state. A simple route to minimize both the total electron-dose and the dose-rate is to reduce the electron beam-current and/or raster the probe at higher speeds. At the limit of these settings, and with current detectors, the resulting images suffer from unacceptable artifacts, including signal-streaking, detector-afterglow, and poor signal-to-noise ratios (SNRs). In this article, we present an alternative approach to capture dark-field STEM images by pulse-counting individual electrons as they are scattered to the annular dark-field (ADF) detector. Digital images formed in this way are immune from analog artifacts of streaking or afterglow and allow clean, high-SNR images to be obtained even at low beam-currents. We present results from both a ThermoFisher FEI Titan G2 operated at 300 kV and a Nion UltraSTEM200 operated at 200 kV, and compare the images to conventional analog recordings. ADF data are compared with analog counterparts for each instrument, a digital detector-response scan is performed on the Titan, and the overall rastering efficiency is evaluated for various scanning parameters.
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We propose a new method to measure atomic scale dynamics of nanoparticles from experimental high-resolution annular dark field scanning transmission electron microscopy images. By using the so-called hidden Markov model, which explicitly models the possibility of structural changes, the number of atoms in each atomic column can be quantified over time. This newly proposed method outperforms the current atom-counting procedure and enables the determination of the probabilities and cross sections for surface diffusion. This method is therefore of great importance for revealing and quantifying the atomic structure when it evolves over time via adatom dynamics, surface diffusion, beam effects, or during in situ experiments.
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It is well-established that the inclusion of small atomic species such as boron (B) in powder metal catalysts can subtly modify catalytic properties, and the associated changes in the metal lattice imply that the B atoms are located in the interstitial sites. However, there is no compelling evidence for the occurrence of interstitial B atoms, and there is a concomitant lack of detailed structural information describing the nature of this occupancy and its effects on the metal host. In this work, we use an innovative combination of high-resolution 11B magic-angle-spinning (MAS) and 105Pd static solid-state NMR nuclear magnetic resonance (NMR), synchrotron X-ray diffraction (SXRD), in situ X-ray pair distribution function (XPDF), scanning transmission electron microscopy-annular dark field imaging (STEM-ADF), electron ptychography, and electron energy loss spectroscopy (EELS) to investigate the B atom positions, properties, and structural modifications to the palladium lattice of an industrial type interstitial boron doped palladium nanoparticle catalyst system (Pd-intB/C NPs). In this study, we report that upon B incorporation into the Pd lattice, the overall face centered cubic (FCC) lattice is maintained; however, short-range disorder is introduced. The 105Pd static solid-state NMR illustrates how different types (and levels) of structural strain and disorder are introduced in the nanoparticle history. These structural distortions can lead to the appearance of small amounts of local hexagonal close packed (HCP) structured material in localized regions. The short-range lattice tailoring of the Pd framework to accommodate interstitial B dopants in the octahedral sites of the distorted FCC structure can be imaged by electron ptychography. This study describes new toolsets that enable the characterization of industrial metal nanocatalysts across length scales from macro- to microanalysis, which gives important guidance to the structure-activity relationship of the system.
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Understanding nanostructures down to the atomic level is the key to optimizing the design of advanced materials with revolutionary novel properties. This requires characterization methods capable of quantifying the three-dimensional (3D) atomic structure with the highest possible precision. A successful approach to reach this goal is to count the number of atoms in each atomic column from 2D annular dark field scanning transmission electron microscopy images. To count atoms with single atom sensitivity, a minimum electron dose has been shown to be necessary, while on the other hand beam damage, induced by the high energy electrons, puts a limit on the tolerable dose. An important challenge is therefore to develop experimental strategies to optimize the electron dose by balancing atom-counting fidelity vs the risk of knock-on damage. To achieve this goal, a statistical framework combined with physics-based modeling of the dose-dependent processes is here proposed and experimentally verified. This model enables an investigator to theoretically predict, in advance of an experimental measurement, the optimal electron dose resulting in an unambiguous quantification of nanostructures in their native state with the highest attainable precision.
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Many studies of heterogeneous catalysis, both experimental and computational, make use of idealized structures such as extended surfaces or regular polyhedral nanoparticles. This simplification neglects the morphological diversity in real commercial oxygen reduction reaction (ORR) catalysts used in fuel-cell cathodes. Here we introduce an approach that combines 3D nanoparticle structures obtained from high-throughput high-precision electron microscopy with density functional theory. Discrepancies between experimental observations and cuboctahedral/truncated-octahedral particles are revealed and discussed using a range of widely used descriptors, such as electron-density, d-band centers, and generalized coordination numbers. We use this new approach to determine the optimum particle size for which both detrimental surface roughness and particle shape effects are minimized.
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Heterogeneous nanoparticle catalyst development relies on an understanding of their structure-property relationships, ideally at atomic resolution and in three-dimensions. Current transmission electron microscopy techniques such as discrete tomography can provide this but require multiple images of each nanoparticle and are incompatible with samples that change under electron irradiation or with surveying large numbers of particles to gain significant statistics. Here, we make use of recent advances in quantitative dark-field scanning transmission electron microscopy to count the number atoms in each atomic column of a single image from a platinum nanoparticle. These atom-counts, along with the prior knowledge of the face-centered cubic geometry, are used to create atomistic models. An energy minimization is then used to relax the nanoparticle's 3D structure. This rapid approach enables high-throughput statistical studies or the analysis of dynamic processes such as facet-restructuring or particle damage.
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Three-dimensional (3D) tomography is a powerful investigative tool for many scientific domains, going from materials science, to engineering, to medicine. Many factors may limit the 3D resolution, often spatially anisotropic, compromising the precision of the information retrievable. A neural network, designed for video-frame interpolation, is employed to enhance tomographic images, achieving cubic-voxel resolution. The method is applied to distinct domains: the investigation of the morphology of printed graphene nanosheets networks, obtained via focused ion beam-scanning electron microscope (FIB-SEM), magnetic resonance imaging of the human brain, and X-ray computed tomography scans of the abdomen. The accuracy of the 3D tomographic maps can be quantified through computer-vision metrics, but most importantly with the precision on the physical quantities retrievable from the reconstructions, in the case of FIB-SEM the porosity, tortuosity, and effective diffusivity. This work showcases a versatile image-augmentation strategy for optimizing 3D tomography acquisition conditions, while preserving the information content.
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Faster scanning in scanning transmission electron microscopy has long been desired for the ability to better control dose, minimise effects of environmental distortions, and to capture the dynamics of in-situ experiments. Advances in scan controllers and scan deflection systems have enabled scanning with pixel dwell times on the order of tens of nanoseconds. At these speeds, the finite response time of the electron detector must be considered as the signal from one electron detection event can contribute to multiple pixels, blurring the features within the image. Here we introduce a temporal transfer function (TTF) to describe and model the effects of detector response time on imaging, as well as a framework for incorporating these effects into simulation.
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Here, we demonstrate the production of 2D nanosheets of arsenic disulfide (As2S3) via liquid-phase exfoliation of the naturally occurring mineral, orpiment. The resultant nanosheets had mean lateral dimensions and thicknesses of 400 and 10 nm, and had structures indistinguishable from the bulk. The nanosheets were solution mixed with carbon nanotubes and cast into nanocomposite films for use as anodes in potassium-ion batteries. These anodes exhibited outstanding electrochemical performance, demonstrating an impressive discharge capacity of 619 mAh/g at a current density of 50 mA/g. Even after 1000 cycles at 500 mA/g, the anodes retained an impressive 94% of their capacity. Quantitative analysis of the rate performance yielded a capacity at a very low rate of 838 mAh/g, about two-thirds of the theoretical capacity of As2S3 (1305 mAh/g). However, this analysis also implied As2S3 to have a very small solid-state diffusion coefficient (â¼10-17 m2/s), somewhat limiting its potential for high-rate applications.
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With the recent progress in the development of detectors in electron microscopy, it has become possible to directly count the number of electrons per pixel, even with a scintillator-type detector, by incorporating a pulse-counting module. To optimize a denoising method for electron counting imaging, in this study, we propose a Poisson denoising method for atomic-resolution scanning transmission electron microscopy images. Our method is based on the Markov random field model and Bayesian inference, and we can reduce the electron dose by a factor of about 15 times or further below. Moreover, we showed that the method of reconstruction from multiple images without integrating them performs better than that from an integrated image.