Ultramicroscopy最新文献

Scanning ion conductance microscopy (SICM) has developed rapidly and has wide applications in biomedicine, single-cell science and other fields. SICM scanning speed is limited by the conventional raster-type scanning method, which spends most of time on imaging the substrate and does not focus enough on the target area. In order to solve this problem, a target region focused (TRF) method is proposed, which can effectively avoid the scanning of unnecessary substrate areas and enables SICM to image the target area only to achieve high-speed and effective local scanning. TRF method and conventional hopping mode scanning method are compared in the experiments using breast cancer cells and rat basophilic leukemia cells as experimental materials. It was demonstrated that our method can reduce the scanning time for a single sample image significantly without losing scanning information or compromising the quality of imaging. The TRF method developed in this paper can provide an efficient and fast scanning strategy for improving the imaging performance of SICM systems, which can be applied to the dynamic features of cell samples in the fields of biology and pharmacology analysis.

Diffraction pattern analysis can be used to reveal the crystalline structure of materials, and this information is used to nano- and micro-structure of advanced engineering materials that enable modern life. For nano-structured materials typically diffraction pattern analysis is performed in the transmission electron microscope (TEM) and TEM diffraction patterns typically have a limited angular range (less than a few degrees) due to the long camera length, and this requires analysis of multiple patterns to probe a unit cell. As a different approach, wide angle Kikuchi patterns can be captured using an on-axis detector in the scanning electron microscope (SEM) with a shorter camera length. These ‘transmission Kikuchi diffraction’ (TKD) patterns present a direct projection of the unit cell and can be routinely analysed using EBSD-based methods and dynamical diffraction theory. In the present work, we enhance this analysis significantly and present a multi-exposure diffraction pattern fusion method that increases the dynamic range of the detected patterns captured with a Timepix3-based direct electron detector (DED). This method uses an easy-to-apply exposure fusion routine to collect data and extend the dynamic range, as well as normalise the intensity distribution within these very wide (>95°) angle patterns. The potential of this method is demonstrated with full diffraction sphere reprojection and highlight potential of the approach to rapidly probe the structure of nano-structured materials in the scanning electron microscope.

Tri-beam microscopes comprising a fs-laser beam, a Xe+ plasma focused ion beam (PFIB) and an electron beam all in one chamber open up exciting opportunities for site-specific correlative microscopy. They offer the possibility of rapid ablation and material removal by fs-laser, subsequent polishing by Xe-PFIB milling and electron imaging of the same area. While tri-beam systems are capable of probing large (mm) volumes providing high resolution microscopical characterisation of 2D and 3D images across exceptionally wide range of materials and biomaterials applications, presenting high quality/low damage surfaces to the electron beam can present a significant challenge, especially given the large parameter space for optimisation. Here the optimal conditions and artefacts associated with large scale volume milling, mini test piece manufacture, serial sectioning and surface polishing are investigated, both in terms of surface roughness and surface quality for metallic, ceramic, mixed complex phase, carbonaceous, and biological materials. This provides a good starting place for those wishing to examine large areas or volumes by tri-beam microscopy across a range of materials.

We report new advancements in the determination and high-resolution structural analysis of beam-sensitive metal organic frameworks (MOFs) using microcrystal electron diffraction (MicroED) coupled with focused ion beam milling at cryogenic temperatures (cryo-FIB). A microcrystal of the beam-sensitive MOF, ZIF-8, was ion-beam milled in a thin lamella approximately 150 nm thick. MicroED data were collected from this thin lamella using an energy filter and a direct electron detector operating in counting mode. Using this approach, we achieved a greatly improved resolution of 0.59 Å with a minimal total exposure of only 0.64 e⁻/A². These innovations not only improve model statistics but also further demonstrate that ion-beam milling is compatible with beam-sensitive materials, augmenting the capabilities of electron diffraction in MOF research.

Interfacial phenomena between active cathode materials and solid electrolytes play an important role in the function of solid-state batteries. (S)TEM imaging can give valuable insight into the atomic structure and composition at the various interfaces, yet the preparation of TEM specimen by FIB (focused ion beam) is challenging for loosely bound samples like composites, as they easily break apart during conventional preparation routines. We propose a novel preparation method that uses a frame made of deposition layers from the FIB's gas injection system to prevent the sample from breaking apart. This technique can of course be also applied to other loosely bound samples, not only those in the field of batteries.

Direct electron detection is currently revolutionizing many fields of electron microscopy due to its lower noise, its reduced point-spread function, and its increased quantum efficiency. More specifically to this work, Timepix3 is a hybrid-pixel direct electron detector capable of outputting temporal information of individual hits in its pixel array. Its architecture results in a data-driven detector, also called event-based, in which individual hits trigger the data off the chip for readout as fast as possible. The presence of a pixel threshold value results in an almost readout-noise-free detector while also defining the hit time of arrival and the time the signal stays over the pixel threshold. In this work, we have performed various experiments to calibrate and correct the Timepix3 temporal information, specifically in the context of electron microscopy. These include the energy calibration, and the time-walk and pixel delay corrections, reaching an average temporal resolution throughout the entire pixel matrix of $1.37\pm 0.04\mathrm{ns}$. Additionally, we have also studied cosmic rays tracks to characterize the charge dynamics along the volume of the sensor layer, allowing us to estimate the limits of the detector’s temporal response depending on different bias voltages, sensor thickness, and the electron beam ionization volume. We have estimated the uncertainty due to the ionization volume ranging from about 0.8 ns for 60 keV electrons to 8.8 ns for 300 keV electrons.

Segmentation methods are very useful tools in the Electron Microscopy inspection of materials, enabling the extraction of quantitative results from microscopy images. Back-Scattered Electron (BSE) images carry information of the mean atomic number in the interaction volume and hence can be used to quantify the phase composition in multiphase materials. Since phase composition and proportion affects the material properties and hence its applications, the segmentation accuracy of such images rendered of critical importance for material science. In this work, the notion of segmentability for BSE images is proposed to define the ability of an image to be segmented accurately. This notion can be used to guide the image acquisition process so that segmentability is maximized and segmentation accuracy is ensured. An index is devised to quantify segmentability based on a combination of the modified Fisher Discrimination Ratio and of the second Minkowski functional capturing intensity and spatial aspects of BSE images respectively. The suggested Segmentability Index (SI) is validated in synthetic BSE images which are generated with a novel algorithm allowing the independent control of spatial distribution of phases and their grayscale intensity histograms. Additionally, SI is applied in real-synthetic BSE images, where the real greyscale distributions of Ordinary Portland Cement (OPC) clinker crystallographic phases are used, to demonstrate the ability of SI to indicate the optimum choice of critical image acquisition settings leading to the more accurate segmentation output.

In-situ liquid cell transmission electron microscopy (LCTEM) with electrical biasing capabilities has emerged as an invaluable tool for directly imaging electrode processes with high temporal and spatial resolution. However, accurately quantifying structural changes that occur on the electrode and subsequently correlating them to the applied stimulus remains challenging. Here, we present structural dissimilarity (DSSIM) analysis as segmentation-free video processing algorithm for locally detecting and quantifying structural change occurring in LCTEM videos. In this study, DSSIM analysis is applied to two in-situ LCTEM videos to demonstrate how to implement this algorithm and interpret the results. We show DSSIM analysis can be used as a visualization tool for qualitative data analysis by highlighting structural changes which are easily missed when viewing the raw data. Furthermore, we demonstrate how DSSIM analysis can serve as a quantitative metric and efficiently convert 3-dimensional microscopy videos to 1-dimenional plots which makes it easy to interpret and compare events occurring at different timepoints in a video. In the analyses presented here, DSSIM is used to directly correlate the magnitude and temporal scale of structural change to the features of the applied electrical bias. ImageJ, Python, and MATLAB programs, including a user-friendly interface and accompanying documentation, are published alongside this manuscript to make DSSIM analysis easily accessible to the scientific community.

Electron magnetic circular dichroism (EMCD) is a powerful technique for estimating element-specific magnetic moments of materials on nanoscale with the potential to reach atomic resolution in transmission electron microscopes. However, the fundamentally weak EMCD signal strength complicates quantification of magnetic moments, as this requires very high precision, especially in the denominator of the sum rules. Here, we employ a statistical resampling technique known as bootstrapping to an experimental EMCD dataset to produce an empirical estimate of the noise-dependent error distribution resulting from application of EMCD sum rules to bcc iron in a 3-beam orientation. We observe clear experimental evidence that noisy EMCD signals preferentially bias the estimation of magnetic moments, further supporting this with error distributions produced by Monte-Carlo simulations. Finally, we propose guidelines for the recognition and minimization of this bias in the estimation of magnetic moments.