Ultramicroscopy最新文献

To fulfill power and energy demands, lithium-ion battery (LIB) is being considered as a promising energy storage device. For the development of LIBs, high-resolution electron microscopy characterization of battery materials is crucial. During this characterization, the interaction of beam-electrons with Li-containing materials causes damage through several processes, especially knock-on damage. In this study, we investigated this damage by determining the probability of knock-on damage and performing Monte Carlo simulation. For this objective, the threshold displacement energies (TDEs) were computed using sudden approximation technique for three sets of materials, including pure elements, LiX (X = F, Cl, Br), and Li₂MSiO₄ (M = Fe, Co, Mn). By including the Climbing-Image Nudge Elastic Band (CI-NEB) method into the sudden approximation approach, it was found that the accuracy of the predicted TDEs could be improved. Results also indicated that at moderate electron energies, the knock-on damage for Li in both its elemental and compound forms maximized. In addition, it was shown that the TDE should be the principal parameter for assessing the Li sensitivity to knock-on damage across similar structures. Nonetheless, other parameters, including cross-section, density, weight fraction, atomic weight, and atomic number, were found to impact the knock-on damage.

Novel event-based electron detector platforms provide an avenue to extend the temporal resolution of electron microscopy into the ultrafast domain. Here, we characterize the timing accuracy of a detector based on a TimePix3 architecture using femtosecond electron pulse trains as a reference. With a large dataset of event clusters triggered by individual incident electrons, a neural network is trained to predict the electron arrival time. Corrected timings of event clusters show a temporal resolution of 2 ns, a 1.6-fold improvement over cluster-averaged timings. This method is applicable to other fast electron detectors down to sub-nanosecond temporal resolutions, offering a promising solution to enhance the precision of electron timing for various electron microscopy applications.

Electron correlation microscopy (ECM) characterizes local structural relaxation dynamics in fluctuating systems like supercooled liquids with nanometer spatial resolution. We have developed a new type of ECM technique that provides moderate resolution in momentum transfer or k space using five-dimensional scanning transmission electron microscopy. k-resolved ECM on a Pt_57.5Cu_14.7Ni_5.3P_22.5 metallic supercooled liquids measures rich spatial and momentum structure in the relaxation time data $\tau \left(r,k\right)$. Relaxation time maps $\tau \left(r\right)$ at each azimuthal k are independent samples of the material's underlying relaxation time distribution, and $\tau$ of radial k shows more complex behavior than the de Gennes narrowing observed in analogous X-ray experiments. We have determined the requirements for electron counts per k-pixel, number of k-pixels per speckle, and time sampling to obtain reliable k-resolved ECM data.

Simulations of cryo-electron microscopy (cryo-EM) images of biological samples can be used to produce test datasets to support the development of instrumentation, methods, and software, as well as to assess data acquisition and analysis strategies. To be useful, these simulations need to be based on physically realistic models which include large volumes of amorphous ice. The gold standard model for EM image simulation is a physical atom-based ice model produced using molecular dynamics simulations. Although practical for small sample volumes; for simulation of cryo-EM data from large sample volumes, this can be too computationally expensive. We have evaluated a Gaussian Random Field (GRF) ice model which is shown to be more computationally efficient for large sample volumes. The simulated EM images are compared with the gold standard atom-based ice model approach and shown to be directly comparable. Comparison with experimentally acquired data shows the Gaussian random field ice model produces realistic simulations. The software required has been implemented in the Parakeet software package and the underlying atomic models are available online for use by the wider community.

Ptychography provides high dose efficiency images that can reveal light elements next to heavy atoms. However, despite ptychography having an otherwise single signed contrast transfer function, contrast reversals can occur when the projected potential becomes strong for both direct and iterative inversion ptychography methods. It has recently been shown that these reversals can often be counteracted in direct ptychography methods by adapting the focus. Here we provide an explanation of why the best contrast is often found with the probe focused to the middle of the sample. The phase contribution due to defocus at each sample slice above and below the central plane in this configuration effectively cancels out, which can prevent contrast reversals when dynamical scattering effects are not overly strong. In addition we show that the convergence angle can be an important consideration for removal of contrast reversals in relatively thin samples.

Recent advances in electron microscopy techniques have led to a significant scale up in volumetric imaging of biological tissue. The throughput of electron microscopes, however, remains a limiting factor for the volume that can be imaged in high resolution within reasonable time. Faster detection methods will improve throughput. Here, we have characterized and benchmarked a novel detection technique for scanning electron microscopy: optical scanning transmission electron microscopy (OSTEM). A qualitative and quantitative comparison was performed between OSTEM, secondary and backscattered electron detection and annular dark field detection in scanning transmission electron microscopy. Our analysis shows that OSTEM produces images similar to backscattered electron detection in terms of contrast, resolution and signal-to-noise ratio. OSTEM can complement large scale imaging with (scanning) transmission electron microscopy and has the potential to speed up imaging in single-beam scanning electron microscope.

In focused ion beam (FIB) tomography, a combination of FIB with a scanning electron microscope (SEM) is used for collecting a series of planar images of the microstructure of nanoporous materials. These planar images serve as the basis for reconstructing the three-dimensional microstructure through segmentation algorithms. However, the assumption of a constant distance between consecutively imaged sections is generally invalid due to random variations in the FIB milling process. This variation complicates the accurate reconstruction of the three-dimensional microstructure. Using synthetic FIB tomography data, we present an algorithm that repositions slices according to their actual thickness and interpolates the results using machine learning-based methods. We applied our algorithm to real datasets, comparing two standard approaches of microstructure reconstruction: on-the-fly via image processing and ruler-based via sample structuring. Our findings indicate that the ruler-based method, combined with our novel slice repositioning and interpolation algorithm, exhibits superior performance in reconstructing the microstructure.

We evaluated the usable specimen thickness of Si for lattice imaging on a transmission electron microscopy (TEM) instrument operating at 300 kV and equipped with a complementary metal-oxide-semiconductor camera by using an original reference material (RM) and comparing the lattice images obtained from Si patterns of the RM with various thicknesses. Lattice images of the {111} planes of crystalline Si are successfully observed for patterns with thicknesses of up to 508 nm. However, the contrast of these lattice fringes at a thickness of 508 nm is not distinct, even when recorded using a longer exposure time (5.0 s) than that required to obtain lattice images of patterns with thicknesses of 316 nm or less (0.5 s). Based on these results, we conclude that the practical thickness of crystalline Si specimens for accurate structural analysis and TEM magnification calibration via lattice imaging is less than approximately 500 nm under the experimental conditions.

Phase-shifting electron holography is an excellent method to reveal electron wave phase information with very high phase sensitivity over a large range of spatial frequencies. It circumvents the limiting trade-off between fringe spacing and visibility of standard off-axis holography. Previous implementations have been limited by the independent drift of biprism and sample. We demonstrate here an advanced drift correction scheme for the hologram series that exploits the presence of an interface of the TEM specimen to the vacuum area in the hologram. It allows to obtain reliable phase information up to 2π/452 at the 1 Å information limit of the Titan 80–300 kV environmental transmission electron microscope used, by applying a moderate voltage of 250 V to a single biprism for a fringe spacing of 1 Å. The obtained phase and amplitude information is validated at a thin Pt sample by use of multislice image simulation with the frozen lattice approximation and shows excellent agreement. The presented method is applicable in any TEM equipped with at least one electron biprism and thus enables achieving high resolution off-axis holography in various instruments including those for in-situ applications. A software implementation for the acquisition, calibration and reconstruction is provided.

A new material characterization technique is emerging for the transmission electron microscope (TEM). Using electron energy-loss spectroscopy, real space mappings of the underlying electronic transitions in the sample, so called orbital maps, can be produced. Thus, unprecedented insight into the electronic orbitals responsible for most of the electrical, magnetic and optical properties of bulk materials can be gained. However, the incredibly demanding requirements on spatial as well as spectral resolution paired with the low signal-to-noise ratio severely limits the day-to-day use of this new technique. With the use of simulations, we strive to alleviate these challenges as much as possible by identifying optimal experimental parameters. In this manner, we investigate representative examples of a transition metal oxide, a material consisting entirely of light elements, and an interface between two different materials to find and compare acceptable ranges for sample thickness, acceleration voltage and electron dose for a scanning probe as well as for parallel illumination.