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A new misfit layered compound with the stoichiometry (EuS)1+δ(NbSe2)2 (δ ≈ 0.13) has been successfully synthesized. High-resolution transmission electron microscopy and powder X-ray diffraction confirm the misfit structure with (EuS)-(EuS) spacing of 18.30(1) Å. Magnetization, electrical resistivity, heat capacity, and thermal transport measurements show that the material is a heavily doped semiconductor or poor metal with a low thermal conductivity of â¼1 W/m K and an antiferromagnetic ordering transition at TN = 4.7 K. In contrast to the parent materials, the misfit is neither ferromagnetic nor superconducting down to T = 0.4 K. We find evidence of a field-driven transition to a ferromagnetic state due to reorientation of ferromagnetic EuS layers at µoH = 0.5 T at T = 2 K.
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Grain boundaries are critical in determining the properties of materials, including mechanical stability, conductivity, and corrosion resistance. The specific properties of materials depend not only on the misorientation of the crystals, the three most commonly characterized parameters, but also on the angle of the grain boundary plane between the two crystals, the final two parameters in the five-parameter macroscopic description of the grain boundary. The method presented here allows for the direct measurement of all five parameters of the grain boundary in a transmission electron microscopy specimen of various morphologies. This is especially applicable to atom probe specimens, where only a single-tilt axis is generally available, allowing the crystallographic description to be matched to the detailed chemical data available in the atom probe tomography. This method provides a platform for efficient grain boundary analysis in unique samples, saving operator time and allowing for ease of acquisition and interpretation in comparison with traditional electron diffraction methods.
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Iron-chromium and nickel-chromium binary alloys containing sufficient quantities of chromium serve as the prototypical corrosion-resistant metals owing to the presence of a nanometre-thick protective passive oxide film1-8. Should this film be compromised by a scratch or abrasive wear, it reforms with little accompanying metal dissolution, a key criterion for good passive behaviour. This is a principal reason that stainless steels and other chromium-containing alloys are used in critical applications ranging from biomedical implants to nuclear reactor components9,10. Unravelling the compositional dependence of this electrochemical behaviour is a long-standing unanswered question in corrosion science. Herein, we develop a percolation theory of alloy passivation based on two-dimensional to three-dimensional crossover effects that accounts for selective dissolution and the quantity of metal dissolved during the initial stage of passive film formation. We validate this theory both experimentally and by kinetic Monte Carlo simulation. Our results reveal a path forward for the design of corrosion-resistant metallic alloys.
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Fused filament fabrication three-dimensional (3D) printers have been shown to emit ultrafine particles (UFPs) and volatile organic compounds (VOCs). Previous studies have quantified bulk 3D printer particle and VOC emission rates, as well as described particle chemical composition via ex situ analysis. Here, we present size-resolved aerosol composition measurements from in situ aerosol mass spectrometry and ex situ transmission electron microscopy (TEM). Particles were sampled for in situ analysis during acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA) 3D printing activities and ex situ analysis during ABS printing. We examined the effect of a high-efficiency particulate air filter attachment on ABS emissions and particle chemical composition and demonstrate that filtration was effective in preventing UFP emissions and that particles sampled during filtered prints did not have a high contribution (â¼4% vs â¼10%) from aromatic ions in the mass spectrum. Ex situ analysis of particles collected during ABS printing was performed via TEM and electron energy loss spectroscopy, which indicated a high level of sp2 bonding type consistent with polymeric styrene. One 3D print with PLA resulted in an aerosol mass size distribution with a peak at â¼300 nm. Unfiltered ABS prints resulted in particle mass size distributions with peak diameters of â¼100 nm.
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Contaminación del Aire Interior , Compuestos Orgánicos Volátiles , Aerosoles , Tamaño de la Partícula , Material Particulado , EstirenoRESUMEN
MXenes have shown promise in myriad applications, such as energy storage, catalysis, EMI shielding, among many others. However, MXene oxidation in aqueous colloidal suspensions when stored in water at ambient conditions remains a challenge. It is now shown that by simply capping the edges of individual MXene flakes, Ti3 C2 Tz and V2 CTz , by polyanions such as polyphosphates, polysilicates or polyborates, it is possible to quite significantly reduce their propensity for oxidation even when held in aerated water for weeks. This breakthrough resulted from the realization that the edges of MXene sheets are positively charged. It is thus an example of selectively functionalizing the edges differently from the MXene sheet surfaces.
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Deficiency in insulin secretion and function that characterize type 2 diabetes often requires administration of extraneous insulin, leading to injection-site amyloidosis. Insulin aggregation at neutral pH is not well understood. Although oligomer formation is believed to play an important role, insulin oligomers have not been fully characterized yet. Here, we elucidate similarities and differences between in vitro insulin aggregation at acidic and neutral pH for a range of insulin concentrations (2.5-100 µM) by using kinetic thioflavin T fluorescence, circular dichroism, atomic force and electron microscopy imaging. Importantly, we characterize the size distribution of insulin oligomers at different assembly stages by the application of covalent cross-linking and gel electrophoresis. Our results show that at the earliest assembly stage, oligomers comprise up to 40% and 70% of soluble insulin at acidic and neutral pH, respectively. While the highest oligomer order increases with insulin concentration at acidic pH, the opposite tendency is observed at neutral pH, where oligomers up to heptamers are formed in 10 µM insulin. These findings suggest that oligomers may be on- and off-pathway assemblies for insulin at acidic and neutral pH, respectively. Agitation, which is required to induce insulin aggregation at neutral pH, is shown to increase fibril formation rate and fibrillar mass both by an order of magnitude. Insulin incubated under agitated conditions at neutral pH rapidly aggregates into large micrometer-sized aggregates, which may be of physiological relevance and provides insight into injection-site amyloidosis and toxic pulmonary aggregates induced by administration of extraneous insulin.
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Amiloide/química , Amiloide/metabolismo , Insulina/química , Insulina/metabolismo , Benzotiazoles , Dicroismo Circular , Humanos , Concentración de Iones de Hidrógeno , Microscopía de Fuerza Atómica , Microscopía Electrónica de Transmisión , Peso Molecular , Agregado de Proteínas , TiazolesRESUMEN
We use in situ transmission electron microscopy to directly observe, at high temporal and spatial resolution, the interaction of ferroelectric domains and dislocation networks within BiFeO3 thin films. The experimental observations are compared with a phase field model constructed to simulate the dynamics of domains in the presence of dislocations and their resulting strain fields. We demonstrate that a global network of misfit dislocations at the film-substrate interface can act as nucleation sites and slow down domain propagation in the vicinity of the dislocations. Networks of individual threading dislocations emanating from the film-electrode interface play a more dramatic role in pinning domain motion. These dislocations may be responsible for the domain behavior in ferroelectric thin-film devices deviating from conventional Kolmogorov-Avrami-Ishibashi dynamics toward a Nucleation Limited Switching model.
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Self-assembled core-shell structured rare-earth nanoparticles (TbErAs) are observed in a III-V semiconductor host matrix (In0.53Ga0.47As) nominally lattice-matched to InP, grown via molecular beam epitaxy. Atom probe tomography demonstrates that the TbErAs nanoparticles have a core-shell structure, as seen both in the tomographic atom-by-atom reconstruction and concentration profiles. A simple thermodynamic model is created to determine when it is energetically favorable to have core-shell structures; the results strongly agree with the observations.
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In situ Electron Energy Loss Spectroscopy (EELS) combined with Transmission Electron Microscopy (TEM) has traditionally been pivotal for understanding how material processing choices affect local structure and composition. However, the ability to monitor and respond to ultrafast transient changes, now achievable with EELS and TEM, necessitates innovative analytical frameworks. Here, we introduce a machine learning (ML) framework tailored for the real-time assessment and characterization of in operando EELS Spectrum Images (EELS-SI). We focus on 2D MXenes as the sample material system, specifically targeting the understanding and control of their atomic-scale structural transformations that critically influence their electronic and optical properties. This approach requires fewer labeled training data points than typical deep learning classification methods. By integrating computationally generated structures of MXenes and experimental datasets into a unified latent space using Variational Autoencoders (VAE) in a unique training method, our framework accurately predicts structural evolutions at latencies pertinent to closed-loop processing within the TEM. This study presents a critical advancement in enabling automated, on-the-fly synthesis and characterization, significantly enhancing capabilities for materials discovery and the precision engineering of functional materials at the atomic scale.
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The development of radiation-tolerant structural materials is an essential element for the success of advanced nuclear energy concepts. A proven strategy to increase radiation resistance is to create microstructures with a high density of internal defect sinks, such as grain boundaries (GBs). However, as GBs absorb defects, they undergo internal transformations that limit their ability to capture defects indefinitely. Here, we show that, as the sink efficiency of GBs becomes exhausted with increasing irradiation dose, networks of irradiation loops form in the vicinity of saturated or near-saturated GB, maintaining and even increasing their capacity to continue absorbing defects. The formation of these networks fundamentally changes the driving force for defect absorption at GB, from "chemical" to "elastic." Using thermally-activated dislocation dynamics simulations, we show that these networks are consistent with experimental measurements of defect densities near GB. Our results point to these networks as a natural continuation of the GB once they exhaust their internal defect absorption capacity.
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The advent of aberration correction for transmission electron microscopy has transformed atomic resolution imaging into a nearly routine technique for structural analysis. Now an emerging frontier in electron microscopy is the development of in situ capabilities to observe reactions at atomic resolution in real time and within realistic environments. Here we present a new in situ gas cell holder that is designed for compatibility with a wide variety of sample type (i.e., dimpled 3-mm discs, standard mesh grids, various types of focused ion beam lamellae attached to half grids). Its capabilities include localized heating and precise control of the gas pressure and composition while simultaneously allowing atomic resolution imaging at ambient pressure. The results show that 0.25-nm lattice fringes are directly visible for nanoparticles imaged at ambient pressure with gas path lengths up to 20 µm. Additionally, we quantitatively demonstrate that while the attainable contrast and resolution decrease with increasing pressure and gas path length, resolutions better than 0.2 nm should be accessible at ambient pressure with gas path lengths less than the 15 µm utilized for these experiments.
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Gases , Microscopía Electrónica de Transmisión/instrumentación , Microscopía Electrónica de Transmisión/métodos , Nanopartículas/análisis , Calefacción , Rayos Láser , Plomo/análisis , Óxidos/análisis , Titanio/análisisRESUMEN
The rapid collection and indexing of electron diffraction patterns as produced via electron backscatter diffraction (EBSD) has enabled crystallographic orientation and structural determination, as well as additional property-determining strain and dislocation density information with increasing speed, resolution, and efficiency. Pattern indexing quality is reliant on the noise of the collected electron diffraction patterns, which is often convoluted by sample preparation and data collection parameters. EBSD acquisition is sensitive to many factors and thus can result in low confidence index (CI), poor image quality (IQ), and improper minimization of fit, which can result in noisy datasets and misrepresent the microstructure. In an attempt to enable both higher speed EBSD data collection and enable greater orientation fit accuracy with noisy datasets, an image denoising autoencoder was implemented to improve pattern quality. We show that EBSD data processed through the autoencoder results in a higher CI, IQ, and a more accurate degree of fit. In addition, using denoised datasets in HR-EBSD cross correlative strain analysis can result in reduced phantom strain from erroneous calculations due to the increased indexing accuracy and improved correspondence between collected and simulated patterns.
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Structural characterization is crucial to understanding protein function. Compared with X-ray diffraction methods, electron crystallography can be performed on nanometer-sized crystals and can provide additional information from the resulting Coulomb potential map. Whereas electron crystallography has successfully resolved three-dimensional structures of vitrified protein crystals, its widespread use as a structural biology tool has been limited. One main reason is the fragility of such crystals. Protein crystals can be easily damaged by mechanical stress, change in temperature, or buffer conditions as well as by electron irradiation. This work demonstrates a methodology to preserve these nanocrystals in their natural environment at room temperature for electron diffraction experiments as an alternative to existing cryogenic techniques. Lysozyme crystals in their crystallization solution are hermetically sealed via graphene-coated grids, and their radiation damage is minimized by employing a low-dose data collection strategy in combination with a hybrid-pixel direct electron detector. Diffraction patterns with reflections of up to 3 Å are obtained and successfully indexed using a template-matching algorithm. These results demonstrate the feasibility of in situ protein electron diffraction. The method described will also be applicable to structural studies of hydrated nanocrystals important in many research and technological developments.
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Electrones , Proteínas , Temperatura , Proteínas/química , Cristalografía por Rayos X , Difracción de Rayos XRESUMEN
We report on the crystallite growth and phase change of electrodeposited CdSe coatings on ZnO nanowires during annealing. Both in situ transmission electron microscopy (TEM) and x-ray diffraction (XRD) reveal that the nanocrystal size increases from â¼3 to â¼10 nm upon annealing at 350 °C for 1 h and then to more than 30 nm during another 1 h at 400 °C, exhibiting two distinct growth regimes. Nanocrystal growth occurs together with a structural change from zinc blende to wurtzite. The structural transition begins at 350 °C, which results in the formation of stacking faults. Increased crystallite size, comparable to the coating thickness, can improve charge separation in extremely thin absorber solar cells. We demonstrate a nearly two-fold improvement in power conversion efficiency upon annealing.
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MXenes are a growing family of 2D transition-metal carbides and nitrides, which display excellent performance in myriad of applications. Theoretical calculations suggest that manipulation of the MXene surface termination (such as =O or -F) could strongly alter their functional properties; however, experimental control of the MXene surface termination is still in the developmental stage. Here, we demonstrate that annealing MXenes in an Ar + O2 low-power plasma results in increased =O functionalization with minimal formation of secondary phases. We apply this method to two MXenes, Ti2CT x and Mo2TiC2T x (T x represents the mixed surface termination), and show that in both cases, the increased =O content increases the electrical resistance and decreases the surface transition-metal's electron count. For Mo2TiC2O x , we show that the O content can be reversibly altered through successive vacuum and plasma annealing. This work provides an effective way to tune MXene surface functionalization, which may unlock exciting surface-dependent properties.
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Helium bubbles are known to form in nuclear reactor structural components when displacement damage occurs in conjunction with helium exposure and/or transmutation. If left unchecked, bubble production can cause swelling, blistering, and embrittlement, all of which substantially degrade materials and-moreover-diminish mechanical properties. On the mission to produce more robust materials, nanocrystalline (NC) metals show great potential and are postulated to exhibit superior radiation resistance due to their high defect and particle sink densities; however, much is still unknown about the mechanisms of defect evolution in these systems under extreme conditions. Here, the performances of NC nickel (Ni) and iron (Fe) are investigated under helium bombardment via transmission electron microscopy (TEM). Bubble density statistics are measured as a function of grain size in specimens implanted under similar conditions. While the overall trends revealed an increase in bubble density up to saturation in both samples, bubble density in Fe was over 300% greater than in Ni. To interrogate the kinetics of helium diffusion and trapping, a rate theory model is developed that substantiates that helium is more readily captured within grains in helium-vacancy complexes in NC Fe, whereas helium is more prone to traversing the grain matrices and migrating to GBs in NC Ni. Our results suggest that (1) grain boundaries can affect bubble swelling in grain matrices significantly and can have a dominant effect over crystal structure, and (2) an NC-Ni-based material can yield superior resistance to irradiation-induced bubble growth compared to an NC-Fe-based material and exhibits high potential for use in extreme environments where swelling due to He bubble formation is of significant concern.
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Transition metal phosphorus trisulfide materials have received considerable research interest since the 1980-1990s as they exhibit promising energy conversion and storage properties. However, the mechanistic insights into Li-ion storage in these materials are poorly understood to date. Here, we explore the lithiation of NiPS3 material by employing in situ pair-distribution function analysis, Monte Carlo molecular dynamics calculations, and a series of ex situ characterizations. Our findings elucidate complex ion insertion and storage dynamics around a layered polyanionic compound, which undergoes intercalation and conversion reactions in a sequential manner. This study of NiPS3 material exemplifies the Li-ion storage mechanism in transition metal phosphorus sulfide materials and provides insights into the challenges associated with achieving reliable, high-energy phosphorus trisulfide systems.
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Recent advances in detectors for imaging and spectroscopy have afforded in situ, rapid acquisition of hyperspectral data. While electron energy loss spectroscopy (EELS) data acquisition speeds with electron counting are regularly reaching 400 frames per second with near-zero read noise, signal to noise ratio (SNR) remains a challenge owing to fundamental counting statistics. In order to advance understanding of transient materials phenomena during rapid acquisition EELS, trustworthy analysis of noisy spectra must be demonstrated. In this study, we applied machine learning techniques to denoise high frame rate spectra, benchmarking with slower frame rate "ground truths". The results provide a foundation for reliable use of low SNR data acquired in rapid, in-situ spectroscopy experiments. Such a tool-set is a first step toward both automation in microscopy as well as use of these methods to interrogate otherwise poorly understood transformations.