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Abstract Grain boundaries in noble metal catalysts have been identified as critical sites for enhancing catalytic activity in electrochemical reactions such as the oxygen reduction reaction. However, conventional methods to modify grain boundary density often alter particle size, shape, and morphology, obscuring the specific role of grain boundaries in catalytic performance. This study addresses these challenges by employing gold nanoparticle assemblies to control grain boundary density through the manipulation of nanoparticle collision frequency during synthesis. We demonstrate a direct correlation between increased grain boundary density and enhanced two-electron oxygen reduction reaction activity, achieving a significant improvement in both specific and mass activity. Additionally, the gold nanoparticle assemblies with high grain boundary density exhibit remarkable electrochemical stability, attributed to boron segregation at the grain boundaries, which prevents structural degradation. This work provides a promising strategy for optimizing the activity, selectivity, and stability of noble metal catalysts through precise grain boundary engineering.

Abstract Aluminum alloys play an important role in circular metallurgy due to their good recyclability and 95% energy gain when made from scrap. Their low density and high strength translate linearly to lower greenhouse gas emissions in transportation, and their excellent corrosion resistance enhances product longevity. The durability of Al alloys stems from the dense barrier oxide film strongly bonded to the surface, preventing further degradation. However, despite decades of research, the individual elemental reactions and their influence on the nanoscale characteristics of the oxide film during corrosion in multicomponent Al alloys remain unresolved questions. Here, we build up a direct correlation between the near-atomistic picture of the corrosion oxide film and the solute reactivity in the aqueous corrosion of a high-strength Al-Zn-Mg-Cu alloy. We reveal the formation of nanocrystalline Al oxide and highlight the solute partitioning between the oxide and the matrix and segregation to the internal interface. The sharp decrease in partitioning content of Mg in the peak-aged alloy emphasizes the impact of heat treatment on the oxide stability and corrosion kinetics. Through H isotopic labelling with deuterium, we provide direct evidence that the oxide acts as a trap for this element, pointing at the essential role of the Al oxide might act as a kinetic barrier in preventing H embrittlement. Our findings advance the mechanistic understanding of further improving the stability of Al oxide, guiding the design of corrosion-resistant alloys for potential applications.

Abstract Chemical short-range order (CSRO) refers to atoms of specific elements self-organising within a disordered crystalline matrix to form particular atomic neighbourhoods. CSRO is typically characterized indirectly, using volume-averaged or through projection microscopy techniques that fail to capture the three-dimensional atomistic architectures. Here, we present a machine-learning enhanced approach to break the inherent resolution limits of atom probe tomography enabling three-dimensional imaging of multiple CSROs. We showcase our approach by addressing a long-standing question encountered in body-centred-cubic Fe-Al alloys that see anomalous property changes upon heat treatment. We use it to evidence non-statistical B2-CSRO instead of the generally-expected D03-CSRO. We introduce quantitative correlations among annealing temperature, CSRO, and nano-hardness and electrical resistivity. Our approach is further validated on modified D03-CSRO detected in Fe-Ga. The proposed strategy can be generally employed to investigate short/medium/long-range ordering phenomena in different materials and help design future high-performance materials.

Abstract Grain boundaries, the two-dimensional defects between differently oriented crystals, tend to preferentially attract solutes for segregation. Solute segregation has a significant effect on the mechanical and transport properties of materials. At the atomic level, however, the interplay of structure and composition of grain boundaries remains elusive, especially with respect to light interstitial solutes like B and C. Here, we use Fe alloyed with B and C to exploit the strong interdependence of interface structure and chemistry via charge-density imaging and atom probe tomography methods. Direct imaging and quantifying of light interstitial solutes at grain boundaries provide insight into decoration tendencies governed by atomic motifs. We find that even a change in the inclination of the grain boundary plane with identical misorientation impacts grain boundary composition and atomic arrangement. Thus, it is the smallest structural hierarchical level, the atomic motifs, that controls the most important chemical properties of the grain boundaries. This insight not only closes a missing link between the structure and chemical composition of such defects but also enables the targeted design and passivation of the chemical state of grain boundaries to free them from their role as entry gates for corrosion, hydrogen embrittlement, or mechanical failure.

Abstract Retrieving information on the chemical and bonding states of atoms in a material in three-dimensions is challenging even for the most advanced imaging techniques. Here, we demonstrate that this information is accessible via straight-flight-path atom probe tomography experimental data, however it requires additional processing. Using an activation energy model that involves linear field dependance, and complementing it with DFT simulations, we extract the ion energy loss related to the kinetics of the field evaporation process from the mass peak shape. In turn, we reconstruct how evaporated atoms were originally bound to the surface. We name our data processing approach evaporation energy loss spectroscopy (FEELS), and showcase its application by analyzing microstructural features and defects in an array of metallic materials. Finally, we discuss the general applicability of FEELS to any atom probe data set.

High-strength Al alloys are sensitive to stress corrosion cracking and hydrogen embrittlement that limit their applications. Here the authors examine them at near-atomic scale using advanced microscopy and reveal hydrogen at dislocations and grain boundaries, and subsequent microstructural changes.

Production defects prevent many industrially important materials from being adopted by metal additive manufacturing. Here, the authors propose a universal thermodynamics-guided alloy design approach to assist the discovery of crack-free materials.

Interstitials can substantially strengthen metals. Here the authors show a massive interstitial solid solution (MISS) approach enabling a model multicomponent alloy to achieve near-theoretical strength together with large deformability.

Common wisdom to improve ductility of bulk metallic glasses (BMGs) is to introduce local loose packing regions at the expense of strength. Here the authors enhance structural fluctuations of BMGs by introducing dense local packing regions, resulting in simultaneous increase of ductility and strength.

Wear-resistant metals have long been a pursuit of reducing wear-related energy and material loss. Here the authors present the ‘reactive wear protection’ strategy via friction-induced in situ formation of strong and deformable oxide nanocomposites on a surface.

Abstract The development of strong-scaling computational tools for high-throughput methods with an open-source code and transparent metadata standards has successfully transformed many computational materials science communities. While such tools are mature already in the condensed-matter physics community, the situation is still very different for many experimentalists. Atom probe tomography (APT) is one example. This microscopy and microanalysis technique has matured into a versatile nano-analytical characterization tool with applications that range from materials science to geology and possibly beyond. Here, data science tools are required for extracting chemo-structural spatial correlations from the reconstructed point cloud. For APT and other high-end analysis techniques, post-processing is mostly executed with proprietary software tools, which are opaque in their execution and have often limited performance. Software development by members of the scientific community has improved the situation but compared to the sophistication in the field of computational materials science several gaps remain. This is particularly the case for open-source tools that support scientific computing hardware, tools which enable high-throughput workflows, and open well-documented metadata standards to align experimental research better with the fair data stewardship principles. To this end, we introduce paraprobe, an open-source tool for scientific computing and high-throughput studying of point cloud data, here exemplified with APT. We show how to quantify uncertainties while applying several computational geometry, spatial statistics, and clustering tasks for post-processing APT datasets as large as two billion ions. These tools work well in concert with Python and HDF5 to enable several orders of magnitude performance gain, automation, and reproducibility.

Abstract Segregation to grain boundaries affects their cohesion, corrosion, and embrittlement and plays a critical role in heterogeneous nucleation. In order to quantitatively study segregation and low-dimensional phase separation at grain boundaries, here, we apply a density-based phase-field model. The current model describes the grain-boundary thermodynamic properties based on available bulk thermodynamic data, while the grain-boundary-density profile is obtained using atomistic simulations. To benchmark the performance of the model, Mn grain-boundary segregation in the Fe–Mn system is studied. 3D simulation results are compared against atom probe tomography measurements conducted for three alloy compositions. We show that a continuous increase in the alloy composition results in a discontinuous jump in the segregation isotherm. The jump corresponds to a spinodal phase separation at grain boundary. For alloy compositions above the jump, we reveal an interfacial transient spinodal phase separation. The transient spinodal phenomenon opens opportunities for knowledge-based microstructure design through the chemical manipulation of grain boundaries. The proposed density-based model provides a powerful tool to study thermodynamics and kinetics of segregation and phase changes at grain boundaries.

The longevity of a lithium-ion battery is limited by cathode degradation. Combining atom probe tomography and scanning transmission electron microscopy reveals that the degradation results from atomic-scale irreversible structural changes once lithium leaves the cathode during charging, thereby inhibiting lithium intercalation back into the cathode as the battery discharges. This information unveils possible routes for improving the lifetime of lithium-ion batteries.

Atom probe tomography can image chemical composition at the nanoscale, but our understanding of how it images voids, or empty spaces, is still lacking. Here, the authors combine atom probe tomography, scanning transmission electron microscopy, and field-evaporation theory to show how voids are imaged and subsequently measured.

Adding minute amounts of rhenium to Ni-based single crystal superalloys extends their high temperature performance in engines, but the reasons behind that are still unclear. Here, the authors combine high resolution imaging and modelling to show that rhenium enriches and slows down partial dislocations to improve creep performance.

Quantitative imaging on the doping in phase-change materials for data storage remains scarce. Here, the authors combine electron microscopy, atom probe tomography, and simulations to determine the role of indium and silver dopants during recrystallization.

Hydrogen contamination in metals during sample preparation for high-resolution microscopy remains a challenge, especially when hydrogen itself is being investigated. Here, the authors show that using cryogenic milling significantly reduces hydrogen pick-up during sample preparation of titanium and titanium alloys.

Sodium doping is necessary to achieve high performance in polycrystalline chalcopyrite solar cells, but retards gallium interdiffusion, and thus efficiency optimisation. Here, Colombara et al. show that in contrast to the polycrystalline case, sodium accelerates atomic interdiffusion in monocrystalline samples.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.