Adatom-Driven Oxygen Intermixing during the Deposition of Oxide Thin Films by Molecular Beam Epitaxy.

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.

Visualizing the iron atom exchange front in the Fe(II)-catalyzed recrystallization of goethite by atom probe tomography.

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.

Self-accelerated corrosion of nuclear waste forms at material interfaces.

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.

Alpha Shape Analysis (ASA) Framework for Post- Clustering Property Determination in Atom Probe Tomographic Data.

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.

Community-Driven Methods for Open and Reproducible Software Tools for Analyzing Datasets from Atom Probe Microscopy.

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.

Atomic origins of water-vapour-promoted alloy oxidation.

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.

The Application of the OPTICS Algorithm to Cluster Analysis in Atom Probe Tomography Data.

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.

Atom Probe Tomography Interlaboratory Study on Clustering Analysis in Experimental Data Using the Maximum Separation Distance Approach.

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.

Modeling selective intergranular oxidation of binary alloys.

Intergranular attack of alloys under hydrothermal conditions is a complex problem that depends on metal and oxygen transport kinetics via solid-state and channel-like pathways to an advancing oxidation front. Experiments reveal very different rates of intergranular attack and minor element depletion distances ahead of the oxidation front for nickel-based binary alloys depending on the minor element. For example, a significant Cr depletion up to 9 µm ahead of grain boundary crack tips was documented for Ni-5Cr binary alloy, in contrast to relatively moderate Al depletion for Ni-5Al (∼100 s of nm). We present a mathematical kinetics model that adapts Wagner's model for thick film growth to intergranular attack of binary alloys. The transport coefficients of elements O, Ni, Cr, and Al in bulk alloys and along grain boundaries were estimated from the literature. For planar surface oxidation, a critical concentration of the minor element can be determined from the model where the oxide of minor element becomes dominant over the major element. This generic model for simple grain boundary oxidation can predict oxidation penetration velocities and minor element depletion distances ahead of the advancing front that are comparable to experimental data. The significant distance of depletion of Cr in Ni-5Cr in contrast to the localized Al depletion in Ni-5Al can be explained by the model due to the combination of the relatively faster diffusion of Cr along the grain boundary and slower diffusion in bulk grains, relative to Al.

Multiscale model of metal alloy oxidation at grain boundaries.

High temperature intergranular oxidation and corrosion of metal alloys is one of the primary causes of materials degradation in nuclear systems. In order to gain insights into grain boundary oxidation processes, a mesoscale metal alloy oxidation model is established by combining quantum Density Functional Theory (DFT) and mesoscopic Poisson-Nernst-Planck/classical DFT with predictions focused on Ni alloyed with either Cr or Al. Analysis of species and fluxes at steady-state conditions indicates that the oxidation process involves vacancy-mediated transport of Ni and the minor alloying element to the oxidation front and the formation of stable metal oxides. The simulations further demonstrate that the mechanism of oxidation for Ni-5Cr and Ni-4Al is qualitatively different. Intergranular oxidation of Ni-5Cr involves the selective oxidation of the minor element and not matrix Ni, due to slower diffusion of Ni relative to Cr in the alloy and due to the significantly smaller energy gain upon the formation of nickel oxide compared to that of Cr2O3. This essentially one-component oxidation process results in continuous oxide formation and a monotonic Cr vacancy distribution ahead of the oxidation front, peaking at alloy/oxide interface. In contrast, Ni and Al are both oxidized in Ni-4Al forming a mixed spinel NiAl2O4. Different diffusivities of Ni and Al give rise to a complex elemental distribution in the vicinity of the oxidation front. Slower diffusing Ni accumulates in the oxide and metal within 3 nm of the interface, while Al penetrates deeper into the oxide phase. Ni and Al are both depleted from the region 3-10 nm ahead of the oxidation front creating voids. The oxide microstructure is also different. Cr2O3 has a plate-like structure with 1.2-1.7 nm wide pores running along the grain boundary, while NiAl2O4 has 1.5 nm wide pores in the direction parallel to the grain boundary and 0.6 nm pores in the perpendicular direction providing an additional pathway for oxygen diffusion through the oxide. The proposed theoretical methodology provides a framework for modeling metal alloy oxidation processes from first principles and on the experimentally relevant length scales.

Selective atomic sieving across metal/oxide interface for super-oxidation resistance.

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.

Metal particle emissions in the exhaust stream of diesel engines: an electron microscope study.

Scanning electron microscopy and transmission electron microscopy were applied to investigate the morphology, mode of occurrence and chemical composition of metal particles (diesel ash) in the exhaust stream of a small truck outfitted with a typical after-treatment system (a diesel oxidation catalyst (DOC) and a downstream diesel particulate filter (DPF)). Ash consists of Ca-Zn-P-Mg-S-Na-Al-K-phases (lube-oil related), Fe, Cr, Ni, Sn, Pb, Sn (engine wear), and Pd (DOC coating). Soot agglomerates of variable sizes (<0.5-5 µm) are abundant upstream of the DPF and are ash-free or contain notably little attached ash. Post-DPF soot agglomerates are very few, typically large (>1-5 µm, exceptionally 13 µm), rarely <0.5 µm, and contain abundant ash carried mostly from inside the DPF. The ash that reaches the atmosphere also occurs as separate aggregates ca. 0.2-2 µm in size consisting of sintered primary phases, ca. 20-400 nm large. Insoluble particles of these sizes may harm the respiratory and cardiovascular systems. The DPF probably promotes breakout of large soot agglomerates (mostly ash-bearing) by favoring sintering. Noble metals detached from the DOC coating may reach the ambient air. Finally, very few agglomerates of Fe-oxide nanoparticles form newly from engine wear and escape into the atmosphere.

Catalyst incorporation at defects during nanowire growth.

Scanning and transmission electron microscopy was used to correlate the structure of planar defects with the prevalence of Au catalyst atom incorporation in Si nanowires. Site-specific high-resolution imaging along orthogonal zone axes, enabled by advances in focused ion beam cross sectioning, reveals substantial incorporation of catalyst atoms at grain boundaries in <110> oriented nanowires. In contrast, (111) stacking faults that generate new polytypes in <112> oriented nanowires do not show preferential catalyst incorporation. Tomographic reconstruction of the catalyst-nanowire interface is used to suggest criteria for the stability of planar defects that trap impurity atoms in catalyst-mediated nanowires.

One dimensional wormhole corrosion in metals.

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.

Atomic structural analysis of nanowire defects and polytypes enabled through cross-sectional lattice imaging.

Correlated transmission electron microscopy imaging, electron diffraction, and Raman spectroscopy are used to investigate the structure of Si nanowires with planar defects. In addition to plan-view imaging, individual defective nanowires are imaged in axial cross-section at specific locations selected in plan-view imaging. This correlated characterization approach enables definitive identification of complex defect structures that give rise to diffraction patterns that have been misinterpreted in the literature. Conclusive evidence for the 9R Si polytype is presented, and the atomic structure of this phase is correlated with kinematically-forbidden reflections in Si diffraction patterns. Despite striking similarities between imaging and diffraction data from twinned nanowires and the 9R polytype, clear distinctions between the structures can be made. Finally, the structural origins of ⅓{422} reflections in Si [111] diffraction patterns are identified.

A method for directly correlating site-specific cross-sectional and plan-view transmission electron microscopy of individual nanostructures.

A sample preparation method is described for enabling direct correlation of site-specific plan-view and cross-sectional transmission electron microscopy (TEM) analysis of individual nanostructures by employing a dual-beam focused-ion beam (FIB) microscope. This technique is demonstrated using Si nanowires dispersed on a TEM sample support (lacey carbon or Si-nitride). Individual nanowires are first imaged in the plan-view orientation to identify a region of interest; in this case, impurity atoms distributed at crystalline defects that require further investigation in the cross-sectional orientation. Subsequently, the region of interest is capped with a series of ex situ and in situ deposited layers to protect the nanowire and facilitate site-specific lift-out and cross-sectioning using a dual-beam FIB microscope. The lift-out specimen is thinned to electron transparency with site-specific positioning to within ≈ 200 nm of a target position along the length of the nanowire. Using the described technique, it is possible to produce correlated plan-view and cross-sectional view lattice-resolved TEM images that enable a quasi-3D analysis of crystalline defect structures in a specific nanowire. While the current study is focused on nanowires, the procedure described herein is general for any electron-transparent sample and is broadly applicable for many nanostructures, such as nanowires, nanoparticles, patterned thin films, and devices.

Atom probe analysis of electrode materials for Li-ion batteries: challenges and ways forward.

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.