Ultramicroscopy最新文献

In this work we instigated the fragmentation of Au microparticles supported on a thin amorphous carbon film by irradiating them with a gradually convergent electron beam inside the Transmission Electron Microscope. This phenomenon has been generically labeled as “electron beam-induced fragmentation” or EBIF and its physical origin remains contested. On the one hand, EBIF has been primarily characterized as a consequence of beam-induced heating. On the other, EBIF has been attributed to beam-induced charging eventually leading to Coulomb explosion. To test the feasibility of the charging framework for EBIF, we instigated the fragmentation of Au particles under two different experimental conditions. First, with the magnetic objective lens of the microscope operating at full capacity, i.e. background magnetic field $B=2$ T, and with the magnetic objective lens switched off (Lorenz mode), i.e. $B=0$ T. We observe that the presence or absence of the magnetic field noticeably affects the critical current density at which EBIF occurs. This strongly suggests that magnetic field effects play a crucial role in instigating EBIF on the microparticles. The dependence of the value of the critical current density on the absence or presence of an ambient magnetic field cannot be accounted for by the beam-induced heating model. Consequently, this work presents robust experimental evidence suggesting that Coulomb explosion driven by electrostatic charging is the root cause of EBIF.

Ewald sphere curvature correction, which extends beyond the projection approximation, stretches the shallow depth of field in cryo-EM reconstructions of thick particles. Here we show that even for previously assumed thin particles, reconstruction artifacts which we refer to as ghosts can appear. By retrieving the lost phases of the electron exitwaves and accounting for the first Born approximation scattering within the particle, we show that these ghosts can be effectively eliminated. Our simulations demonstrate how such ghostbusting can improve reconstructions as compared to existing state-of-the-art software. Like ptychographic cryo-EM, our Ghostbuster algorithm uses phase retrieval to improve reconstructions, but unlike the former, we do not need to modify the existing data acquisition pipelines.

Nanostructured materials continue to find applications in various electronic and sensing devices, chromatography, separations, drug delivery, renewable energy, and catalysis. While major advancements on the synthesis and characterization of these materials have already been made, getting information about their structures at sub-nanometer resolution remains challenging. It is also unfortunate to find that many emerging or already available powerful analytical methods take time to be fully adopted for characterization of various nanomaterials. The scanning low energy electron microscopy (SLEEM) is a good example to this. In this report, we show how clearer structural and surface information at nanoscale can be obtained by SLEEM, coupled with deep learning. The method is demonstrated using Au nanoparticles-loaded mesoporous silica as a model system. Moreover, unlike conventional scanning electron microscopy (SEM), SLEEM does not require the samples to be coated with conductive films for analysis; thus, not only it is convenient to use but it also does not give artifacts. The results further reveal that SLEEM and deep learning can serve as great tools to analyze materials at nanoscale well. The biggest advantage of the presented method is its availability, as most modern SEMs are able to operate at low energies and deep learning methods are already being widely used in many fields.

In this study, we report a strain visualization method using large-angle convergent-beam electron diffraction (LACBED).¹ We compare the proposed method with the strain maps acquired via STEM-NBD, a combination of scanning transmission electron microscopy (STEM) and nanobeam electron diffraction (NBD). Although STEM-NBD can precisely measure the lattice parameters, it requires a large amount of data and personal computer (PC) resources to obtain a two-dimensional strain map. Deficiency lines in the transmitted disk of LACBED reflect the crystalline structure information and move, curve, or disappear in the deformed area. Properly setting the optical conditions makes it possible to acquire real-space images over a broad area in conjunction with deficiency lines on the transmitted disk. The proposed method acquires images by changing the relative position between the specimen and the deficiency line and can grasp the strain information with a small number of images. In addition, the proposed method does not require high-resolution images. It can reduce the required PC memory or storage consumption in comparison with that of STEM-NBD, which requires a high-resolution diffraction pattern (DP) from each point of the region of interest. Compared with the two-dimensional maps of LACBED and NBD, NBD could detect large distortions in the area where the deficiency line curved, moved, or disappeared. The curving or moving direction of the deficiency line is qualitatively consistent with the NBD results. If quantitative strain values are not essential, strain visualization using LACBED can be considered an effective technique. We believe that the strain information of a sample can be obtained effectively using both methods.

Atomic-scale electron microscopy traditionally probes thin specimens, with thickness below 100 nm, and its feasibility for bulk samples has not been documented. In this study, we explore the practicality of scanning transmission electron microscope (STEM) imaging with secondary electrons (SE), using a silicon-wedge specimen having a maximum thickness of 18 μm. We find that the atomic structure is present in the entire thickness range of the SE images although the background intensity increases moderately with thickness. The consistent intensity of secondary electron (SE) images at atomic positions and the modest increase in background intensity observed in silicon suggest a limited contribution from SEs generated by backscattered electrons, a conclusion supported by our multislice calculations. We conclude that achieving atomic resolution in SE imaging for bulk specimens is indeed attainable using aberration-corrected STEM and an aberration-corrected scanning electron microscope (SEM) may have the capacity for atomic-level resolution, holding great promise for future strides in materials research.

We present the design, fabrication and discuss the performance of a new combined high-resolution Scanning Tunneling and Thermopower Microscope (STM/SThEM). We also describe the development of the electronic control, the user interface, the vacuum system, and arrangements to reduce acoustical noise and vibrations. We demonstrate the microscope’s performance with atomic-resolution topographic images of highly oriented pyrolytic graphite (HOPG) and local thermopower measurements in the semimetal ${\mathrm{Bi}}_2{\mathrm{Te}}_3$. Our system offers a tool to investigate the relationship between electronic structure and thermoelectric properties at the nanoscale.

Compressive sensing (CS) can reconstruct the rest information almost without distortion by advanced computational algorithm, which significantly simplifies the process of atomic force microscope (AFM) scanning with high imaging quality. In common CS-AFM, the partial measurements randomly come from the whole region to be measured, which easily leads to detail loss and poor image quality in regions of interest (ROIs). Consequently, important microscopic phenomena are missed probably. In this paper, we developed an adaptive under-sampling strategy for CS-AFM to optimize the process of sampling. Under a certain under-sampling ratio, the weight coefficient of ROIs and regions of base (ROBs) were set to control the distribution of under-sampling points and corresponding measurement matrix. A series of simulations were completed to demonstrate the relationship between the weight coefficient of ROIs and image quality. After that, we verified the effectiveness of the method on our homemade AFM. Through a lot of simulations and experiments, we demonstrated how the proposed method optimized the sampling process of CS-AFM, which speeded up the process of AFM imaging with high quality.

Neutral helium atom microscopy is a novel microscopy technique which offers strictly surface-sensitive, non-destructive imaging. Several experiments have been published in recent years where images are obtained by scanning a helium beam spot across a surface and recording the variation in scattered intensity at a fixed total scattering angle ${\theta }_{SD}$ and fixed incident angle ${\theta }_i$ relative to the overall surface normal. These experiments used a spot obtained by collimating the beam (referred to as helium pinhole microscopy). Alternatively, a beam spot can be created by focusing the beam with an atom optical element. However up till now imaging with a focused helium beam has only been demonstrated in transmission (using a zone plate). Here we present the first reflection images obtained with a focused helium beam (also using a zone plate). Images are obtained with a spot size (FWHM) down to $4.7\mu m$ $\pm 0.5\mu$m, and we demonstrate focusing down to a spot size of about $1\mu m$. Furthermore, we present experiments measuring the scattering distribution from a focused helium beam spot. The experiments are done by varying the incoming beam angle ${\theta }_i$ while keeping the beam-detector angle ${\theta }_{SD}$ and the point where the beam spot hits the surface fixed - in essence, a microscopy scale realization of a standard helium atom scattering experiment. Our experiments are done using an electron bombardment detector with adjustable signal accumulation, developed particularly for helium microscopy.

The high resolution of a scanning tunneling microscope (STM) relies on the stability of its scan unit. In this study, we present an isolated scan unit featuring non-magnetic design and ultra-high stability, as well as bidirectional movement capability. Different types of piezoelectric motors can be incorporated into the scan unit to create a highly stable STM. The standalone structure of scan unit ensures a stable atomic imaging process by decreasing noise generated by motor. The non-magnetic design makes the scan unit work stable in high magnetic field conditions. Moreover, we have successfully constructed a novel STM based on the isolated scan unit, in which two inertial piezoelectric motors act as the coarse approach actuators. The exceptional performance of homebuilt STM is proved by the high-resolution atomic images and dI/dV spectrums on NbSe₂ surface at varying temperatures, as well as the raw-data images of graphite obtained at ultra-high magnetic fields of 23 T. According to the literature research, no STM has previously reported the atomic image at extreme conditions of 2 K low temperature and 23 T ultra-high magnetic field. Additionally, we present the ultra-low drift rates between the tip and sample at varying temperatures, as well as when raising the magnetic fields from 0 T to 23 T, indicating the ultra-high stability of the STM in high magnetic field conditions. The outstanding performance of our stable STM hold great potential for investigating the materials in ultra-high magnetic fields.

Nanoparticles in microscopy images are usually analyzed qualitatively or manually and there is a need for autonomous quantitative analysis of these objects. In this paper, we present a physics-based computational model for accurate segmentation and geometrical analysis of one-dimensional deformable overlapping objects from microscopy images. This model, named Nano1D, has four steps of preprocessing, segmentation, separating overlapped objects and geometrical measurements. The model is tested on SEM images of Ag and Au nanowire taken from different microscopes, and thermally fragmented Ag nanowires transformed into nanoparticles with different lengths, diameters, and population densities. It successfully segments and analyzes their geometrical characteristics including lengths and average diameter. The function of the algorithm is not undermined by the size, number, density, orientation and overlapping of objects in images. The main strength of the model is shown to be its ability to segment and analyze overlapping objects successfully with more than 99 % accuracy, while current machine learning and computational models suffer from inaccuracy and inability to segment overlapping objects. Benefiting from a graphical user interface, Nano1D can analyze 1D nanoparticles including nanowires, nanotubes, nanorods in addition to other 1D features of microstructures like microcracks, dislocations etc.