Ultramicroscopy最新文献

Miniaturized quartz tuning forks (QTFs) have been adopted as force sensors for non-contact atomic force microscopy (AFM). However, the coupled oscillation behaviors of the QTF prongs are not well understood, preventing quantitative measurement of the nanoscale tip-sample interaction forces. This article presents a lumped model that accurately delineates the coupled mechanical oscillations of QTF prongs, establishing rigorous relationships between experimental observables and tip-sample interaction forces. The first-order resonance spectra of a commercial QTF were fully characterized by correlating its piezoelectric response with the actual mechanical oscillation measured with a Fabry-Pérot interferometer. In order to uniquely determine the modeling parameters (i.e., the effective masses, spring constants, and damping constants), the experimental results were compared with the lumped model predictions while masses were added to one prong. The results reveal that the QTF’s center of mass is highly damped, preventing the observation of a symmetric resonance mode. In addition, the mass loading experiment demonstrates that the mechanical oscillations of the QTF prongs are strongly coupled, accounting for 59% (84%) of the effective stiffness at the in-plane (out-of-plane), antisymmetric resonance mode. We believe that the obtained QTF characterization results will pave the way for quantitative measurements of non-contact interaction forces in QTF-based AFM platforms, significantly improving the precision and reliability of nanoscale force measurements.

The main feature of vicinal surfaces of crystals characterized by the Miller indices $\left(hhm\right)$ is rather small width (less than 10 nm) and substantially large length (more than 200 nm) of atomically-flat terraces. This makes difficult to apply standard methods of image processing and correct visualization of crystalline lattices at the terraces and multiatomic steps. Here we consider two procedures allowing us to minimize effects of both small-scale noise and global tilt of sample: (i) analysis of the difference of two Gaussian blurred images, and (ii) subtraction of the plane, whose parameters are determined by optimization of the histogram of the visible heights, from raw topography image. It is shown that both methods provide nondistorted images demonstrating atomic structures on vicinal Si(5 5 6) and Si(5 5 7) surfaces.

Quantitative interpretation of transmission electron microscopy (TEM) data of crystalline specimens often requires the accurate knowledge of the local crystal orientation. A method is presented which exploits momentum-resolved scanning TEM (STEM) data to determine the local mistilt from a major zone axis. It is based on a geometric analysis of Kikuchi bands within a single diffraction pattern, yielding the center of the Laue circle. Whereas the approach is not limited to convergent illumination, it is here developed using unit-cell averaged diffraction patterns corresponding to high-resolution STEM settings. In simulation studies, an accuracy of approximately 0.1 mrad is found. The method is implemented in automated software and applied to crystallographic tilt and in-plane rotation mapping in two experimental cases. In particular, orientation maps of high-Mn steel and an epitaxially grown La${}_{\text{0.7}}$Sr${}_{\text{0.3}}$MnO${}_{\text{3}}$-SrTiO${}_{\text{3}}$ interface are presented. The results confirm the estimates of the simulation study and indicate that tilt mapping can be performed consistently over a wide field of view with diameters well above 100 nm at unit cell real space sampling.

Imaging nanomaterials in hybrid systems is critical to understanding the structure and functionality of these systems. However, current technologies such as scanning electron microscopy (SEM) may obtain high resolution/contrast images at the cost of damaging or contaminating the sample. For example, to prevent the charging of organic substrate/matrix, a very thin layer of metal is coated on the surface, which will permanently contaminate the sample and eliminate the possibility of reusing it for following processes. Conversely, examining the sample without any modifications, in pursuit of high-fidelity digital images of its unperturbed state, can come at the cost of low-quality images that are challenging to process. Here, a solution is proposed for the case where no brightness threshold is available to reliably judge whether a region is covered with nanomaterials. The method examines local brightness variability to detect nanomaterial deposits. Very good agreement with manually obtained values of the coverage is observed, and a strong case is made for the method's automatability. Although the developed methodology is showcased in the context of SEM images of Polydimethylsiloxane (PDMS) substrates on which silicone dioxide (SiO₂) nanoparticles are assembled, the underlying concepts may be extended to situations where straightforward brightness thresholding is not viable.