When selecting a method for determining modal mineralogy and elemental composition of geological samples (e.g., meteorites), a number of factors should be considered, includingthe number of objects or the area to be analyzed; the scale of expected chemical variation; instrument time restrictions; and post-processing time. This study presents a method that minimizes acquisition time while maintaining the ability to distinguish minerals based on combinations of intensities of electron probe micro-analyzer-generated X-ray element maps. While some other methods yield similar outcomes, this method's post-processing utilizes standard parameterized, X-ray intensity “map math” in an algorithm that is adaptable and requires minimal supervision once implemented. This study's minimized supervision in the post-processing of X-ray intensity maps decreases analysis time and its adaptability increases the number of potential applications. The method also facilitates calibration of the exact locations of analysis using laser ablation methods. While the method described here has advantages, the choice of method always depends on the question being asked.

This paper describes initial experimental results from an extreme ultraviolet (EUV) radiation-pulsed atom probe microscope. Femtosecond-pulsed coherent EUV radiation of 29.6 nm wavelength (41.85 eV photon energy), obtained through high harmonic generation in an Ar-filled hollow capillary waveguide, successfully triggered controlled field ion emission from the apex of amorphous SiO2 specimens. The calculated composition is stoichiometric within the error of the measurement and effectively invariant of the specimen base temperature in the range of 25 K to 150 K. Photon energies available in the EUV band are significantly higher than those currently used in the state-of-the-art near-ultraviolet laser-pulsed atom probe, which enables the possibility of additional ionization and desorption pathways. Pulsed coherent EUV light is a new and potential alternative to near-ultraviolet radiation for atom probe tomography.

In this paper, an improved quantification technique for STEM/EDX measurements of 1D dopant profiles based on the Cliff-Lorimer equation is presented. The technique uses an iterative absorption correction procedure based on density models correlating the local mass density and composition of the specimen. Moreover, a calibration and error estimation procedure based on linear regression and error propagation is proposed in order to estimate the total measurement error in the dopant density. The proposed approach is applied to the measurement of the As profile in a nanodevice test structure. For the calibration, two crystalline Si specimens implanted with different As doses have been used, and the calibration of the Cliff-Lorimer coefficients has been carried out using Rutherford Back Scattering measurements. The As profile measurement has been carried out on an FinFET test structure, showing that quantitative results can be obtained in the nanometer scale and for dopant atomic densities lower than 1%. Using the proposed approach, the measurement error and detection limit for our experimental setup are calculated and the possibility to improve this limit by increasing the observation time is discussed.

Atomic-resolution cryogenic scanning transmission electron microscopy (cryo-STEM) has provided a path to probing the microscopic nature of select low-temperature phases in quantum materials. Expanding cryo-STEM techniques to broadly tunable temperatures will give access to the rich temperature-dependent phase diagrams of these materials. With existing cryo-holders, however, variations in sample temperature significantly disrupt the thermal equilibrium of the system, resulting in large-scale sample drift. The ability to tune the temperature without negative impact on the overall instrument stability is crucial, particularly for high-resolution experiments. Here, we test a new side-entry continuously variable temperature dual-tilt cryo-holder which integrates liquid nitrogen cooling with a 6-pin micro-electromechanical system (MEMS) sample heater to overcome some of these experimental challenges. We measure consistently low drift rates of 0.3–0.4 Å/s and demonstrate atomic-resolution cryo-STEM imaging across a continuously variable temperature range from ~100 K to well above room temperature. We conduct additional drift stability measurements across several commercial sample stages and discuss implications for further developments of ultra-stable, flexible cryo-stages.

Many nanoparticles in fields such as heterogeneous catalysis undergo surface structural fluctuations during chemical reactions, which may control functionality. These dynamic structural changes may be ideally investigated with time-resolved in situ electron microscopy. We have explored approaches for extracting quantitative information from large time-resolved image data sets with a low signal to noise recorded with a direct electron detector on an aberration-corrected transmission electron microscope. We focus on quantitatively characterizing beam-induced dynamic structural rearrangements taking place on the surface of CeO2 (ceria). A 2D Gaussian fitting procedure is employed to determine the position and occupancy of each atomic column in the nanoparticle with a temporal resolution of 2.5 ms and a spatial precision of 0.25 Å. Local rapid lattice expansions/contractions and atomic migration were revealed to occur on the (100) surface, whereas (111) surfaces were relatively stable throughout the experiment. The application of this methodology to other materials will provide new insights into the behavior of nanoparticle surface reconstructions that were previously inaccessible using other methods, which will have important consequences for the understanding of dynamic structure–property relationships.

Biological transmission of arthropod-borne viruses (arboviruses) to vertebrate hosts by hematophagous insects poses a global threat because such arboviruses can result in a range of serious public health infectious diseases. Sindbis virus (SINV), the prototype Alphavirus, was used to track infections in the posterior midgut (PMG) of Aedes aegypti adult mosquitoes. Females were fed viremic blood containing a virus reporter, SINV [Thosea asigna virus-green fluorescent protein (TaV-GFP)], that leaves a fluorescent signal in infected cells. We assessed whole-mount PMGs to identify primary foci, secondary target tissues, distribution, and virus persistence. Following a viremic blood meal, PMGs were dissected and analyzed at various days of post blood-feeding. We report that virus foci indicated by GFP in midgut epithelial cells resulted in a 9.8% PMG infection and a 10.8% dissemination from these infected guts. The number of virus foci ranged from 1 to 3 per individual PMG and was more prevalent in the PMG-middle > PMG-frontal > PMG-caudal regions. SINV TaV-GFP was first observed in the PMG (primary target tissue) at 3 days post blood-feeding, was sequestered in circumscribed foci, replicated in PMG peristaltic muscles (secondary target tissue) following dissemination, and GFP was observed to persist in PMGs for 30 days postinfection.

Electron backscatter diffraction (EBSD) is one of the primary tools in materials development and analysis. The technique can perform simultaneous analyses at multiple length scales, providing local sub-micron information mapped globally to centimeter scale. Recently, a series of technological revolutions simultaneously increased diffraction pattern quality and collection rate. After collection, current EBSD pattern indexing techniques (whether Hough-based or dictionary pattern matching based) are capable of reliably differentiating between a “user selected” set of phases, if those phases contain sufficiently different crystal structures. EBSD is currently less well suited for the problem of phase identification where the phases in the sample are unknown. A pattern analysis technique capable of phase identification, utilizing the information-rich diffraction patterns potentially coupled with other data, such as EDS-derived chemistry, would enable EBSD to become a high-throughput technique replacing many slower (X-ray diffraction) or more expensive (neutron diffraction) methods. We utilize a machine learning technique to develop a general methodology for the space group classification of diffraction patterns; this is demonstrated within the $\lpar 4/m\comma \;\bar{3}\comma \;\;2/m\rpar$ point group. We evaluate the machine learning algorithm's performance in real-world situations using materials outside the training set, simultaneously elucidating the role of atomic scattering factors, orientation, and pattern quality on classification accuracy.