Visualizing biological structures and cellular processes in their native state is a major goal of many scientific laboratories. In the past 20 years, the technique of preserving samples by vitrification has greatly expanded, specifically for use in cryogenic electron microscopy (cryo-EM). Here, we report on improvements in the design and use of a portable manual cryogenic plunge freezer that is intended for use in laboratories that are not equipped for the cryopreservation of samples. The construction of the instrument is economical, can be produced by a local machine shop without specialized equipment, and lowers the entry barriers for newcomers with a reliable alternative to costly commercial equipment. The improved design allows for successful freezing of isolated proteins for single particle analysis as well as bacterial cells for cryo-electron tomography. With this instrument, groups will be able to prepare vitreous samples whenever and wherever necessary, which can then be imaged at local or national cryo-EM facilities.

Protocols for conducting in situ transmission electron microscopy (TEM) reactions using an environmental TEM with dry gases have been well established. However, many important reactions that are relevant to catalysis or high-temperature oxidation occur at atmospheric pressure and are influenced by the presence of water vapor. These experiments necessitate using a closed-cell gas reaction TEM holder. We have developed protocols for introducing and controlling water vapor concentrations in experimental gases from 2% at a full atmosphere to 100% at ~17 Torr, while measuring the gas composition using a residual gas analyzer (RGA) on the return side of the in situ gas reactor holder. Initially, as a model system, cube-shaped MgO crystals were used to help develop the protocols for handling the water vapor injection process and confirming that we could successfully inject water vapor into the gas cell. The interaction of water vapor with MgO triggered surface morphological and chemical changes as a result of the formation of Mg(OH)2, later validated with mass spectra obtained with our RGA system with and without water vapor. Integrating an RGA with an in situ scanning/TEM closed-cell gas reaction system can thus provide critical measurements correlating gas composition with dynamic surface restructuring of materials during reactions.

Taking advantage of recent advances in parallel computing, we studied compositional disorder along metal–oxygen atomic columns in a complex Mo,V-oxide bronze using multislice frozen-phonon calculations. Commonly, the virtual crystal approximation (VCA) is used to model compositional disorder at crystallographic sites in a unit cell for a number of different theoretical and experimental techniques. In the VCA, a weighted linear sum of atomic properties is used to approximate the model structure. When using the VCA, the extracted V content of Mo,V–O columns from experimental high-angle annular dark-field (HAADF) images will be about half the V content estimated from simulations, considering the distinct cation ordering. This discrepancy is larger than the spread of HAADF signals of different configurational orders at a given V concentration, which can be up to 20%. Certain “isophilic” atomic arrangements along the column can be distinguished from more random ones using HAADF-STEM imaging. The trends and ratios of the simulated intensity spreads due to different compositional ordering along 11 M–O columns along the c-axis of the Mo,V oxide bronze qualitatively match those observed in experimental HAADF-STEM data. Instrumental and sample-based noise adds to the variability but does not significantly distort the relative ratios of column intensity variation. We observed that we only required seven random configurations to represent the intensity variations along columns.

This study explores magnetization exhibited by nanoscale platinum-based structures embedded in pure silica plates. A superposition of laser pulses in the samples produced periodic linear arrangements of micro-sized structures. The samples were integrated by PtO2 microstructures (PtOΣs) with dispersed Pt oxide nanoparticles in their surroundings. The characterization of the materials was performed by high transmission electron microscopy studies. Furthermore, topographical and magnetic effects on the sample surfaces were analyzed by atomic force microscopy and magnetic force microscopy, respectively. The magnetic measurements indicated an enhancement in the gradient phase shift and in the gradient force related to the magnetic PtOΣs. The possibility of tuning the magnetic characteristics of the samples through contact with a Nd2Fe14B magnet was demonstrated. This process corresponds to an innovative method for obtaining magnetic PtOΣs induced by laser pulses. Moreover, an increase in the compactness of the silica with platinum-based structures was confirmed by an evaluation of the effective elastic modulus with reference to pure silica. The multimodal magnetic structures studied in this work seem to be candidates for developing high-density magnetic storage media.

This study tests the use of a constrained nonnegative matrix factorization (NMF) algorithm to explore the comparatively new field of chemometric microscopy to support tissue diagnosis. The algorithm can extract the spectral signature and the absolute concentration map of endogenous fluorophores from wide-field microscopic images. The resultant data distinguished normal and fibrous calvarial tissues, based on the changes in their spectral signatures. The absolute concentration map of endogenous fluorophores, nicotinamide adenine dinucleotide (NADH), flavin adenine dinucleotide (FAD), and lipofuscin were derived from microscopic images and compared with the fluorescence from pure fluorophores. While the absolute concentration of NADH increased, the same of FAD and lipofuscin decreased from a normal to fibrous calvarial condition. An increase in the optical redox ratio, possibly due to the metabolic changes during the development of fibrosis, was observed. Differentiating tissue types using the absolute concentration map was found to be considerably more precise than that achievable with relative concentration. The quantification of fluorophores with reference to the absolute concentration map can eliminate uncertainties due to system responses or measurement details, thereby generating more biologically apposite data. Wide-field microscopy augmented with a constrained NMF algorithm could emerge as an advanced diagnostic tool, potentially heralding the emergence of chemometric microscopy.

Complex material systems in which microstructure and microchemistry are nonuniformly dispersed require three-dimensional (3D) rendering(s) to provide an accurate determination of the physio-chemical nature of the system. Current scanning transmission electron microscope (STEM)-based tomography techniques enable 3D visualization but can be time-consuming, so only select systems or regions are analyzed in this manner. Here, it is presented that through high-efficiency multidimensional STEM acquisition and reconstruction, complex point cloud-like microstructural features can quickly and effectively be reconstructed in 3D. The proposed set of techniques is demonstrated, analyzed, and verified for a high-chromium steel with heterogeneously situated features induced using high-energy neutron bombardment.

Interfaces play critical roles in materials and are usually both structurally and compositionally complex microstructural features. The precise characterization of their nature in three-dimensions at the atomic scale is one of the grand challenges for microscopy and microanalysis, as this information is crucial to establish structure–property relationships. Atom probe tomography is well suited to analyzing the chemistry of interfaces at the nanoscale. However, optimizing such microanalysis of interfaces requires great care in the implementation across all aspects of the technique from specimen preparation to data analysis and ultimately the interpretation of this information. This article provides critical perspectives on key aspects pertaining to spatial resolution limits and the issues with the compositional analysis that can limit the quantification of interface measurements. Here, we use the example of grain boundaries in steels; however, the results are applicable for the characterization of grain boundaries and transformation interfaces in a very wide range of industrially relevant engineering materials.

We broaden the applicability of sparse coding, a machine learning method, to low-dose electron holography by using simulated holograms for learning and validation processes. The holograms, with shot noise, are prepared to generate a model, or a dictionary, that includes basic features representing interference fringes. The dictionary is applied to sparse representations of other simulated holograms with various signal-to-noise ratios (SNRs). Results demonstrate that this approach successfully removes noise for holograms with an extremely small SNR of 0.10, and that the denoised holograms provide the accurate phase distribution. Furthermore, this study demonstrates that the dictionary learned from the simulated holograms can be applied to denoising of experimental holograms of a p–n junction specimen recorded with different exposure times. The results indicate that the simulation-trained sparse coding is suitable for use over a wide range of imaging conditions, in particular for observing electron beam-sensitive materials.