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Surface passivation, a desirable natural consequence during initial oxidation of alloys, is the foundation for functioning of corrosion and oxidation resistant alloys ranging from industrial stainless steel to kitchen utensils. This initial oxidation has been long perceived to vary with crystal facet, however, the underlying mechanism remains elusive. Here, using in situ environmental transmission electron microscopy, we gain atomic details on crystal facet dependent initial oxidation behavior in a model Ni-5Cr alloy. We find the (001) surface shows higher initial oxidation resistance as compared to the (111) surface. We reveal the crystal facet dependent oxidation is related to an interfacial atomic sieving effect, wherein the oxide/metal interface selectively promotes diffusion of certain atomic species. Density functional theory calculations rationalize the oxygen diffusion across Ni(111)/NiO(111) interface, as contrasted with Ni(001)/NiO(111), is enhanced. We unveil that crystal facet with initial fast oxidation rate could conversely switch to a slow steady state oxidation.
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Corrosion is a ubiquitous failure mode of materials. Often, the progression of localized corrosion is accompanied by the evolution of porosity in materials previously reported to be either three-dimensional or two-dimensional. However, using new tools and analysis techniques, we have realized that a more localized form of corrosion, which we call 1D wormhole corrosion, has previously been miscategorized in some situations. Using electron tomography, we show multiple examples of this 1D and percolating morphology. To understand the origin of this mechanism in a Ni-Cr alloy corroded by molten salt, we combined energy-filtered four-dimensional scanning transmission electron microscopy and ab initio density functional theory calculations to develop a vacancy mapping method with nanometer-resolution, identifying a remarkably high vacancy concentration in the diffusion-induced grain boundary migration zone, up to 100 times the equilibrium value at the melting point. Deciphering the origins of 1D corrosion is an important step towards designing structural materials with enhanced corrosion resistance.
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Thin film deposition from the vapor phase is a complex process involving adatom adsorption, movement, and incorporation into the growing film. Here, we present quantitative experimental data that reveals anion intermixing over long length scales during the deposition of epitaxial Fe2O3 and Cr2O3 films and heterostructures by oxygen-plasma-assisted molecular beam epitaxy. We track this diffusion by incorporating well-defined tracer layers containing 18O and/or 57Fe and measure their redistribution on the nanometer scale with atom probe tomography. Molecular dynamics simulations suggest potential intermixing events, which are then examined via nudged elastic band calculations. We reveal that adatoms on the film surface act to "pull up" subsurface O and Fe. Subsequent ring-like rotation mechanisms involving both adatom and subsurface anions then facilitate their mixing. In addition to film deposition, these intermixing mechanisms may be operant during other surface-mediated processes such as heterogeneous catalysis and corrosion.
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The worldwide development of electric vehicles as well as large-scale or grid-scale energy storage to compensate for the intermittent nature of renewable energy generation has led to a surge of interest in battery technology. Understanding the factors controlling battery capacity and, critically, their degradation mechanisms to ensure long-term, sustainable and safe operation requires detailed knowledge of their microstructure and chemistry, and their evolution under operating conditions, on the nanoscale. Atom probe tomography (APT) provides compositional mapping of materials in three dimensions with sub-nanometre resolution, and is poised to play a key role in battery research. However, APT is underpinned by an intense electric field that can drive lithium migration, and many battery materials are reactive oxides, requiring careful handling and sample transfer. Here, we report on the analysis of both anode and cathode materials and show that electric-field driven migration can be suppressed by using shielding by embedding powder particles in a metallic matrix or by using a thin conducting surface layer. We demonstrate that for a typical cathode material, cryogenic specimen preparation and transport under ultra-high vacuum leads to major delithiation of the specimen during the analysis. In contrast, the transport of specimens through air enables the analysis of the material. Finally, we discuss the possible physical underpinnings and discuss ways forward to enable shielding from the electric field, which helps address the challenges inherent to the APT analysis of battery materials.
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This study investigates the impacts of Ni doping on technetium-99 (Tc) sequestration in aqueous solutions through transformation of Fe(OH)2(s) to iron spinel (magnetite) under alkaline conditions. Extensive solid characterization was performed for the mineral phases produced, as well as the Tc/Ni speciation and distribution within these phases. X-ray diffraction results show that iron spinel was the dominant mineral product without detectable Ni incorporation. The doped Ni ions mainly precipitated as fine Fe/Ni oxide/hydroxide particles, including strongly reduced nanometer-sized spheroidal Ni-rich and metallic Ni phases. High-resolution analytical scanning transmission electron microscopy using energy dispersive X-ray spectroscopy and electron energy loss spectroscopy on the produced solid samples (focused ion beam-prepared specimens) revealed three Tc distribution domains dominated by nanocrystals and, especially, a Tc-rich metallic phase. Instances of metallic Tc were specifically found in spheroidal, Ni-rich and metallic nanoparticles exhibiting a core/shell microstructure that suggests strong reduction and sequential precipitation of Ni-Tc-Ni. Mass balance analysis showed nearly 100% Tc removal from the 4.8 × 10-4 M Tc solutions. The finding of the metallic Tc encapsulation indicates that Tc sequestration through Ni-doped Fe(OH)2(s)-to-iron spinel transformation process likely provides an alternative treatment pathway for Tc removal and could be combined into further waste treatment approaches.
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Atom probe tomography, and related methods, probe the composition and the three-dimensional architecture of materials. The software tools which microscopists use, and how these tools are connected into workflows, make a substantial contribution to the accuracy and precision of such material characterization experiments. Typically, we adapt methods from other communities like mathematics, data science, computational geometry, artificial intelligence, or scientific computing. We also realize that improving on research data management is a challenge when it comes to align with the FAIR data stewardship principles. Faced with this global challenge, we are convinced it is useful to join forces. Here, we report the results and challenges with an inter-laboratory call for developing test cases for several types of atom probe microscopy software tools. The results support why defining detailed recipes of software workflows and sharing these recipes is necessary and rewarding: Open source tools and (meta)data exchange can help to make our day-to-day data processing tasks become more efficient, the training of new users and knowledge transfer become easier, and assist us with automated quantification of uncertainties to gain access to substantiated results.
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While application of clustering algorithms to atom probe tomography data have enabled quantification of solute clusters in terms of number density, size, and subcomposition there exist other properties (e.g., volume, surface area, and composition) that are better determined by defining an interface between the cluster and the surrounding matrix. The limitation in composition results from an ion selection step where the expected matrix ion types are omitted from the cluster search algorithm to enhance the contrast between the matrix and cluster and to reduce the complexity of the search. Previously, composition determination within solute clusters has utilized a secondary envelopment and erosion step on top of conventional methods such as maximum separation. In this work, we present a novel stochastic method that combines the particle identification fidelity of a conventional clustering algorithm with the analytical flexibility of mesh-based approaches through the generation of alpha shapes for each identified cluster. The corresponding mesh accounts for concave components of the clusters and determines the volume and surface area of the clusters; additionally, the mesh boundary is utilized to update the total composition according to the internal ions.
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Gas-solid interfacial reaction is critical to many technological applications from heterogeneous catalysis to stress corrosion cracking. A prominent question that remains unclear is how gas and solid interact beyond chemisorption to form a stable interphase for bridging subsequent gas-solid reactions. Here, we report real-time atomic-scale observations of Ni-Al alloy oxidation reaction from initial surface adsorption to interfacial reaction into the bulk. We found distinct atomistic mechanisms for oxide growth in O2 and H2O vapor, featuring a "step-edge" mechanism with severe interfacial strain in O2, and a "subsurface" one in H2O. Ab initio density functional theory simulations rationalize the H2O dissociation to favor the formation of a disordered oxide, which promotes ion diffusion to the oxide-metal interface and leads to an eased interfacial strain, therefore enhancing inward oxidation. Our findings depict a complete pathway for the Ni-Al surface oxidation reaction and delineate the delicate coupling of chemomechanical effect on gas-solid interactions.
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The US plan for high-level nuclear waste includes the immobilization of long-lived radionuclides in glass or ceramic waste forms in stainless-steel canisters for disposal in deep geological repositories. Here we report that, under simulated repository conditions, corrosion could be significantly accelerated at the interfaces of different barrier materials, which has not been considered in the current safety and performance assessment models. Severe localized corrosion was found at the interfaces between stainless steel and a model nuclear waste glass and between stainless steel and a ceramic waste form. The accelerated corrosion can be attributed to changes of solution chemistry and local acidity/alkalinity within a confined space, which significantly alter the corrosion of both the waste-form materials and the metallic canisters. The corrosion that is accelerated by the interface interaction between dissimilar materials could profoundly impact the service life of the nuclear waste packages, which, therefore, should be carefully considered when evaluating the performance of waste forms and their packages. Moreover, compatible barriers should be selected to further optimize the performance of the geological repository system.
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Atom probe tomography (APT) is a powerful technique to characterize buried three-dimensional nanostructures in a variety of materials. Accurate characterization of those nanometer-scale clusters and precipitates is of great scientific significance to understand the structure-property relationships and the microstructural evolution. The current widely used cluster analysis method, a variant of the density-based spatial clustering of applications with noise algorithm, can only accurately extract clusters of the same atomic density, neglecting several experimental realities, such as density variations within and between clusters and the nonuniformity of the atomic density in the APT reconstruction itself (e.g., crystallographic poles and other field evaporation artifacts). This clustering method relies heavily on multiple input parameters, but ideal selection of those parameters is challenging and oftentimes ambiguous. In this study, we utilize a well-known cluster analysis algorithm, called ordering points to identify the clustering structures, and an automatic cluster extraction algorithm to analyze clusters of varying atomic density in APT data. This approach requires only one free parameter, and other inputs can be estimated or bounded based on physical parameters, such as the lattice parameter and solute concentration. The effectiveness of this method is demonstrated by application to several small-scale model datasets and a real APT dataset obtained from an oxide-dispersion strengthened ferritic alloy specimen.
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We summarize the findings from an interlaboratory study conducted between ten international research groups and investigate the use of the commonly used maximum separation distance and local concentration thresholding methods for solute clustering quantification. The study objectives are: to bring clarity to the range of applicability of the methods; identify existing and/or needed modifications; and interpretation of past published data. Participants collected experimental data from a proton-irradiated 304 stainless steel and analyzed Cu-rich and Ni-Si rich clusters. The datasets were also analyzed by one researcher to clarify variability originating from different operators. The Cu distribution fulfills the ideal requirements of the maximum separation method (MSM), namely a dilute matrix Cu concentration and concentrated Cu clusters. This enabled a relatively tight distribution of the cluster number density among the participants. By contrast, the group analysis of the Ni-Si rich clusters by the MSM was complicated by a high Ni matrix concentration and by the presence of Si-decorated dislocations, leading to larger variability among researchers. While local concentration filtering could, in principle, tighten the results, the cluster identification step inevitably maintained a high scatter. Recommendations regarding reporting, selection of analysis method, and expected variability when interpreting published data are discussed.
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The autocatalytic redox interaction between aqueous Fe(II) and Fe(III)-(oxyhydr)oxide minerals such as goethite and hematite leads to rapid recrystallization marked, in principle, by an atom exchange (AE) front, according to bulk iron isotopic tracer studies. However, direct evidence for this AE front has been elusive given the analytical challenges of mass-resolved imaging at the nanoscale on individual crystallites. We report successful isolation and characterization of the AE front in goethite microrods by 3D atom probe tomography (APT). The microrods were reacted with Fe(II) enriched in tracer 57Fe at conditions consistent with prior bulk studies. APT analyses and 3D reconstructions on cross-sections of the microrods reveal an AE front that is spatially heterogeneous, at times penetrating several nanometers into the lattice, in a manner consistent with defect-accelerated exchange. Evidence for exchange along microstructural domain boundaries was also found, suggesting another important link between exchange extent and initial defect content. The findings provide an unprecedented view into the spatial and temporal characteristics of Fe(II)-catalyzed recrystallization at the atomic scale, and substantiate speculation regarding the role of defects controlling the dynamics of electron transfer and AE interaction at this important redox interface.
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The presence of water vapour, intentional or unavoidable, is crucial to many materials applications, such as in steam generators, turbine engines, fuel cells, catalysts and corrosion1-4. Phenomenologically, water vapour has been noted to accelerate oxidation of metals and alloys5,6. However, the atomistic mechanisms behind such oxidation remain elusive. Through direct in situ atomic-scale transmission electron microscopy observations and density functional theory calculations, we reveal that water-vapour-enhanced oxidation of a nickel-chromium alloy is associated with proton-dissolution-promoted formation, migration, and clustering of both cation and anion vacancies. Protons derived from water dissociation can occupy interstitial positions in the oxide lattice, consequently lowering vacancy formation energy and decreasing the diffusion barrier of both cations and anions, which leads to enhanced oxidation in moist environments at elevated temperatures. This work provides insights into water-vapour-enhanced alloy oxidation and has significant implications in other material and chemical processes involving water vapour, such as corrosion, heterogeneous catalysis and ionic conduction.
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Accelerator-based ion beam irradiation techniques have been used to study radiation effects in materials for decades. Although carbon contamination induced by ion beams in target materials is a well-known issue in some material systems, it has not been fully characterized nor quantified for studies in ferritic/martensitic (F/M) steels that are candidate materials for applications such as core structural components in advanced nuclear reactors. It is an especially important issue for this class of material because of the strong effect of carbon level on precipitate formation. In this paper, the ability to quantify carbon contamination using three common techniques, namely time-of-flight secondary ion mass spectroscopy (ToF-SIMS), atom probe tomography (APT), and transmission electron microscopy (TEM) is compared. Their effectiveness and shortcomings in determining carbon contamination are presented and discussed. The corresponding microstructural changes related to carbon contamination in ion irradiated F/M steels are also presented and briefly discussed.
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We report the in situ atomic-scale visualization of the dynamic three-dimensional growth of NiO during the initial oxidation of Ni-10at%Cr using environmental transmission electron microscopy. A step-by-step adatom growth mechanism in 3D is observed and a change in the surface planes of growing oxide islands can be induced by local surface kinetic variations.
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Hematite (α-Fe2 O3) is engineered to improve photoexcited electron-hole pair separation by synthesizing Fe2O3-Cr2O3 superlattices (SLs) with precise atomic control. The different surface terminations exhibited by Fe2O3 and Cr2O3 determine the hetero-junction interface structure and result in controllable, noncommutative band offset values. This controllable band alignment is harnessed to generate a built-in potential as large as 0.8 eV in Fe2 O3-Cr2O3 SLs.
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Knowledge of solid-state and interfacial species diffusion kinetics is of paramount importance for understanding mechanisms of grain boundary (GB) oxidation causing environmental degradation and cracking of Ni-base structural alloys. In this study, first-principles calculations of vacancy-mediated diffusion are performed across a wide series of alloying elements commonly used in Ni-based superalloys, as well as interstitial diffusion of atomic oxygen and sulfur in the bulk, at the (111) surface, ⟨110⟩ symmetric tilt GBs of Ni corresponding to model low- (Σ = 3/(111)) and high-energy (Σ = 9/(221)) GBs. A substantial enhancement of diffusion is found for all species at the high-energy GB as compared with the bulk and the low-energy GB, with Cr, Mn, and Ti exhibiting remarkably small activation barriers (<0.1 eV; ~10 times lower than in the bulk). Calculations also show that the bulk diffusion mechanism and kinetics differ for oxygen and sulfur, with oxygen having a faster mobility and preferentially diffusing through the tetrahedral interstitial sites in Ni matrix, where it can be trapped in a local minimum.