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The theory of grain boundary (the interface between crystallites, GB) structure has a long history 1 and the concept of GBs undergoing phase transformations was proposed 50 years ago 2 , 3 . The underlying assumption was that multiple stable and metastable states exist for different GB orientations 4 – 6 . The terminology ‘complexion’ was recently proposed to distinguish between interfacial states that differ in any equilibrium thermodynamic property 7 . Different types of complexion and transitions between complexions have been characterized, mostly in binary or multicomponent systems 8 – 19 . Simulations have provided insight into the phase behaviour of interfaces and shown that GB transitions can occur in many material systems 20 – 24 . However, the direct experimental observation and transformation kinetics of GBs in an elemental metal have remained elusive. Here we demonstrate atomic-scale GB phase coexistence and transformations at symmetric and asymmetric [ 11 1 ¯ ] tilt GBs in elemental copper. Atomic-resolution imaging reveals the coexistence of two different structures at Σ19b GBs (where Σ19 is the density of coincident sites and b is a GB variant), in agreement with evolutionary GB structure search and clustering analysis 21 , 25 , 26 . We also use finite-temperature molecular dynamics simulations to explore the coexistence and transformation kinetics of these GB phases. Our results demonstrate how GB phases can be kinetically trapped, enabling atomic-scale room-temperature observations. Our work paves the way for atomic-scale in situ studies of metallic GB phase transformations, which were previously detected only indirectly 9 , 15 , 27 – 29 , through their influence on abnormal grain growth, non-Arrhenius-type diffusion or liquid metal embrittlement. Atomic-resolution observations combined with simulations show that grain boundaries within elemental copper undergo temperature-induced solid-state phase transformation to different structures; grain boundary phases can also coexist and are kinetically trapped structures.

Single crystal Ni-based superalloys have long been an essential material for gas turbines in aero engines and power plants due to their outstanding high temperature creep, fatigue and oxidation resistance. A turning point was the addition of only 3 wt.% Re in the second generation of single crystal Ni-based superalloys which almost doubled the creep lifetime. Despite the significance of this improvement, the mechanisms underlying the so-called “Re effect” have remained controversial. Here, we provide direct evidence of Re enrichment to crystalline defects formed during creep deformation, using combined transmission electron microscopy, atom probe tomography and phase field modelling. We reveal that Re enriches to partial dislocations and imposes a drag effect on dislocation movement, thus reducing the creep strain rate and thereby improving creep properties. These insights can guide design of better superalloys, a quest which is key to reducing CO 2 emissions in air-traffic. 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.

The phase behavior of grain boundaries can have a strong influence on interfacial properties. Little is known about the emergence of grain boundary phases in elemental metal systems and how they transform. Here, we observe the nanoscale patterning of a grain boundary by two alternating grain boundary phases with distinct atomic structures in elemental copper by atomic resolution imaging. The same grain boundary phases are found by computational grain boundary structure search indicating a first-order transformation. Finite temperature atomistic simulations reveal a congruent, diffusionless transition between these phases under ambient pressure. The patterning of the grain boundary at room temperature is dominated by the grain boundary phase junctions separating the phase segments. Our analysis suggests that the reduced mobility of the phase junctions at low temperatures kinetically limits the transformation, but repulsive elastic interactions between them and disconnections could additionally stabilize the pattern formation. The phase behavior of grain boundaries can influence the interfacial properties. Here the authors demonstrate nanoscale patterning of a grain boundary by two alternating phases in Cu that exhibit a congruent, diffusionless transition between the two phases.

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. This study demonstrates that tuning the grain boundary density in nanoparticle assemblies by controlling nanoparticle collisions significantly enhances their activity, selectivity, and stability towards electrocatalytic reactions.

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. Interplay between structure and composition of grain boundaries remains elusive, particularly at the atomic level. Here, the authors discover the atomic motifs, which is the smallest structural unit, control the most important chemical properties of grain boundaries.

Hydrogen pick-up leading to hydride formation is often observed in commercially pure Ti (CP-Ti) and Ti-based alloys prepared for microscopic observation by conventional methods, such as electro-polishing and room temperature focused ion beam (FIB) milling. Here, we demonstrate that cryogenic FIB milling can effectively prevent undesired hydrogen pick-up. Specimens of CP-Ti and a Ti dual-phase alloy (Ti-6Al-2Sn-4Zr-6Mo, Ti6246, in wt.%) were prepared using a xenon-plasma FIB microscope equipped with a cryogenic stage reaching −135 °C. Transmission electron microscopy (TEM), selected area electron diffraction, and scanning TEM indicated no hydride formation in cryo-milled CP-Ti lamellae. Atom probe tomography further demonstrated that cryo-FIB significantly reduces hydrogen levels within the Ti6246 matrix compared with conventional methods. Supported by molecular dynamics simulations, we show that significantly lowering the thermal activation for H diffusion inhibits undesired environmental hydrogen pick-up during preparation and prevents pre-charged hydrogen from diffusing out of the sample, allowing for hydrogen embrittlement mechanisms of Ti-based alloys to be investigated at the nanoscale. 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.

The recent development of electron-sensitive and pixelated detectors has attracted the use of four-dimensional scanning transmission electron microscopy (4D-STEM). Here, we present a precession electron diffraction-assisted 4D-STEM technique for automated orientation mapping using diffraction spot patterns directly captured by an in-column scintillator-based complementary metal-oxide-semiconductor (CMOS) detector. We compare the results to a conventional approach, which utilizes a fluorescent screen filmed by an external charge charge-coupled device camera. The high-dynamic range and signal-to-noise characteristics of the detector greatly improve the image quality of the diffraction patterns, especially the visibility of diffraction spots at high scattering angles. In the orientation maps reconstructed via the template matching process, the CMOS data yield a significant reduction of false indexing and higher reliability compared to the conventional approach. The angular resolution of misorientation measurement could also be improved by masking reflections close to the direct beam. This is because the orientation sensitive, weak, and small diffraction spots at high scattering angles are more significant. The results show that fine details, such as nanograins, nanotwins, and sub-grain boundaries, can be resolved with a sub-degree angular resolution which is comparable to orientation mapping using Kikuchi diffraction patterns.

Characterizing crystal structures and interfaces down to the atomic level is an important step for designing advanced materials. Modern electron microscopy routinely achieves atomic resolution and is capable to resolve complex arrangements of atoms with picometer precision. Here, we present AI-STEM, an automatic, artificial-intelligence based method, for accurately identifying key characteristics from atomic-resolution scanning transmission electron microscopy (STEM) images of polycrystalline materials. The method is based on a Bayesian convolutional neural network (BNN) that is trained only on simulated images. AI-STEM automatically and accurately identifies crystal structure, lattice orientation, and location of interface regions in synthetic and experimental images. The model is trained on cubic and hexagonal crystal structures, yielding classifications and uncertainty estimates, while no explicit information on structural patterns at the interfaces is included during training. This work combines principles from probabilistic modeling, deep learning, and information theory, enabling automatic analysis of experimental, atomic-resolution images.

Copper (Cu)‐based nanomaterials are one of the most efficient heterogeneous electrocatalysts for the CO2 reduction reaction. However, their selectivity and stability are strongly determined by their morphology, crystal structure, composition, grain size, grain boundary density, etc. Hence, gaining quantitative insights into their dynamic evolution under synthesis and/or working conditions is critical for developing optimal Cu‐based electrocatalysts and unveiling their structure‐property relationship. In this work, the possibility of addressing these issues is demonstrated by integrating in situ liquid phase transmission electron microscopy (LP‐TEM) with 4D scanning transmission electron microscopy (4D‐STEM). Here, the dynamic morphology and phase evolution of Cu nanoparticles during electrodeposition and electrooxidation processes are revealed in liquid. Virtual imaging and selected area electron diffraction provide novel insights into the evolution of defective nanocrystalline Cu nanoparticles during electrodeposition. It is shown that virtual off‐axis dark field imaging can be used to map the distribution of Cu2O and Cu within partially oxidized Cu nanoparticles, opening new opportunities for quantitatively probing electrocatalysts under operando conditions. By integrating in situ liquid phase transmission electron microscopy (LP‐TEM) with 4D scanning transmission electron microscopy (4D‐STEM), this work not only reveals the morphology and phase evolution of Cu nanoparticles during electrodeposition and electrooxidation processes but also demonstrates the possibility of mapping the grain size and phase distribution of partially oxidized nanocomposites in the liquid.