Aiming at increasing the yield strength of transformation and twinning induced plasticity (TRIP and TWIP) titanium alloys, a dual-phase $\alpha$/$\beta$ alloy is designed and studied. The composition Ti 7Cr 1.5Sn (wt.%) is proposed, based on an approach coupling Calphad calculations and classical Bo-Md design tool used in Ti-alloys. Its microstructure is made of 20% of $\alpha$ precipitates in a $\beta$ matrix, the matrix having optimal Bo and Md parameters for deformation twinning and martensitic transformation. The alloy indeed displays a yield strength of 760 MPa, about 200 MPa above that of a Ti 8.5Cr 1.5Sn (wt.%) single beta phase TRIP/TWIP alloy, combined with good ductility and work-hardening. In situ synchrotron X ray diffraction and post-mortem electron back-scattered analyses are performed to characterize the deformation mechanisms. They evidence that the TRIP and TWIP mechanisms are successfully obtained in the material, validating the design strategy. The interaction of the precipitates with the {332}<113> $\beta$ twins is analyzed, evidencing that the precipitates are sheared when hit by a twin, and therefore do not hinder the propagation of the twins. The detailed nature of the interaction is discussed, as well as the impact of the precipitates on the mechanical properties.

Hydrogen embrittlement (HE) affects all major high-strength structural materials and as such is a major impediment to lightweighting e.g. vehicles and help reduce carbon-emissions and reach net-zero. The high-strength 7xxx series aluminium alloys can fulfil the need for light, high strength materials, and are already extensively used in aerospace for weight reduction purposes. However, depending on the thermomechanical and loading state, these alloys can be sensitive to stress-corrosion cracking (SCC) through anodic dissolution and hydrogen embrittlement. Here, we study at the near-atomic-scale the intra- and inter-granular microstructure ahead and in the wake of a propagating SCC crack. Moving away from model cases not strictly relevant to application, we performed an industry-standard test on an engineering Al-7XXX alloy. H is found segregated to planar arrays of dislocations and to grain boundaries that we can associate to the combined effects of hydrogen-enhanced localized plasticity (HELP) and hydrogen-enhanced decohesion (HEDE) mechanisms. We report on a Mg-rich H-rich amorphous oxide on the corroded crack surface and evidence of Mg-related diffusional processes leading to dissolution of the strengthening eta-phase precipitates ahead of the crack. We show ingress of up to 1 at% O, i.e. well above the solubility limit of O in Al, near the oxide-metal interface, while no increased level of H is found in the matrix. We provide an array of discussion points relative to the interplay of structural defects, transport of solutes, thereby changing the resistance against crack propagation, which have been overlooked across the SCC literature and prevent accurate service life predictions.

High-entropy alloys are solid solutions of multiple principal elements, capable of reaching composition and feature regimes inaccessible for dilute materials. Discovering those with valuable properties, however, relies on serendipity, as thermodynamic alloy design rules alone often fail in high-dimensional composition spaces. Here, we propose an active-learning strategy to accelerate the design of novel high-entropy Invar alloys in a practically infinite compositional space, based on very sparse data. Our approach works as a closed-loop, integrating machine learning with density-functional theory, thermodynamic calculations, and experiments. After processing and characterizing 17 new alloys (out of millions of possible compositions), we identified 2 high-entropy Invar alloys with extremely low thermal expansion coefficients around 2*10-6 K-1 at 300 K. Our study thus opens a new pathway for the fast and automated discovery of high-entropy alloys with optimal thermal, magnetic and electrical properties.

Due to a large discrepancy between theory and experiment, the electronic character of crystalline boron carbide B$_{13}$C$_{2}$ has been a controversial topic in the field of icosahedral boron-rich solids. We demonstrate that this discrepancy is removed when configurational disorder is accurately considered in the theoretical calculations. We find that while ordered ground state B$_{13}$C$_{2}$ is metallic, configurationally disordered B$_{13}$C$_{2}$, modeled with a superatom-special quasirandom structure method, goes through a metal to non-metal transition as the degree of disorder is increased with increasing temperature. Specifically, one of the chain-end carbon atoms in the CBC chains substitutes a neighboring equatorial boron atom in a B$_{12}$ icosahedron bonded to it, giving rise to a B$_{11}$C$^{e}$(BBC) unit. The atomic configuration of the substitutionally disordered B$_{13}$C$_{2}$ thus tends to be dominated by a mixture between B$_{12}$(CBC) and B$_{11}$C$^{e}$(BBC). Due to splitting of valence states in B$_{11}$C$^{e}$(BBC), the electron deficiency in B$_{12}$(CBC) is gradually compensated.

Predicting the structural response of advanced multiphase alloys and understanding the underlying microscopic mechanisms that are responsible for it are two critically important roles modeling plays in alloy development. An alloys demonstration of superior properties, such as high strength, creep resistance, high ductility, and fracture toughness, is not sufficient to secure its use in widespread application. Still, a good model is needed, to take measurable alloy properties, such as microstructure and chemical composition, and forecast how the alloy will perform in specified mechanical deformation conditions, including temperature, time, and rate. In this bulletin, we highlight recent achievements by multiscale modeling in elucidating the coupled effects of alloying, microstructure, and the dynamics of mechanisms on the mechanical properties of polycrystalline alloys. Much of the understanding gained by these efforts relied on integration of computational tools that varied over many length and time scales, from first principles density functional theory, atomistic simulation methods, dislocation and defect theory, micromechanics, phase field modeling, single crystal plasticity, and polycrystalline plasticity.

We investigate the hot cracking susceptibility and creep resistance of three versions of a nickel-based superalloy with different contents of boron, carbon and zirconium fabricated by laser powder bed fusion. Crack-free and creep resistant components are achieved for alloys with boron, carbon and no zirconium. We then rationalize this result by evaluating how boron, carbon and zirconium are distributed at grain boundaries in the as-built and heat-treated microstructures of an alloy containing all these elements. Observations are conducted by scanning and transmission electron microscopy, and atom probe tomography. In the as-built microstructure, boron, carbon and zirconium segregate at high-angle grain boundaries as a result of solute partitioning to the liquid and limited solid-state diffusion during solidification and cooling. After heat-treatment, the amount of boron and carbon segregating at grain boundaries increases significantly. In contrast, zirconium is not found at grain boundaries but it partitions at the gamma' precipitates formed during the heat treatment. The presence of zirconium at grain boundaries in the as-built condition is known to be susceptible to enhance hot cracking, while its absence in the heat-treated microstructure strongly suggests that this element has no major effect on the creep resistance. Based on our observations, we propose alloy design guidelines to at the same time avoid hot cracking during fabrication and achieve the required creep performance after heat-treatment.

Science is and always has been based on data, but the terms "data-centric" and the "4th paradigm of" materials research indicate a radical change in how information is retrieved, handled and research is performed. It signifies a transformative shift towards managing vast data collections, digital repositories, and innovative data analytics methods. The integration of Artificial Intelligence (AI) and its subset Machine Learning (ML), has become pivotal in addressing all these challenges. This Roadmap on Data-Centric Materials Science explores fundamental concepts and methodologies, illustrating diverse applications in electronic-structure theory, soft matter theory, microstructure research, and experimental techniques like photoemission, atom probe tomography, and electron microscopy. While the roadmap delves into specific areas within the broad interdisciplinary field of materials science, the provided examples elucidate key concepts applicable to a wider range of topics. The discussed instances offer insights into addressing the multifaceted challenges encountered in contemporary materials research.

Site-specific atom probe tomography (APT) from aluminum alloys has been limited by sample preparation issues. Indeed, Ga, which is conventionally used in focused-ion beam (FIB) preparations, has a high affinity for Al grain boundaries and causes their embrittlement. This leads to high concentrations of Ga at grain boundaries after specimen preparation, unreliable compositional analyses and low specimen yield. Here, to tackle this problem, we propose to use cryo-FIB for APT specimen preparation specifically from grain boundaries in a commercial Al-alloy. We demonstrate how this setup, easily implementable on conventional Ga-FIB instruments, is efficient to prevent Ga diffusion to grain boundaries. Specimens were prepared at room temperature and at cryogenic temperature (below approx. 90K) are compared, and we confirm that at room temperature, a compositional enrichment above 15 at.% of Ga is found at the grain boundary, whereas no enrichment could be detected for the cryo-prepared sample. We propose that this is due to the decrease of the diffusion rate of Ga at low temperature. The present results could have a high impact on the understanding of aluminum and Al-alloys.

Hydrogen embrittlement in 304L (18wt.% Cr, 8-10wt.% Ni) austenitic stainless steel (ASS) fabricated by laser powder-bed-fusion (LPBF) was investigated by tensile testing after electrochemical hydrogen pre-charging and compared to conventionally available 304L ASSs with two different processing histories, (i) casting plus annealing (CA) and (ii) CA plus thermomechanical treatment (TMT). It was revealed that hydrogen-charging led to a significant reduction in ductility for the CA sample, but only a small effect of hydrogen was observed for the LPBF and CA-TMT samples. Hydrogen-assisted cracking behavior was found to be strongly linked to strain-induced martensitic transformation. In addition, the amount of alpha' martensite was much higher in the CA sample than in other samples, suggesting that severe hydrogen embrittlement can be correlated with the low mechanical stability of austenite. Detailed microstructural characterization showed that low austenite stability of the CA sample was mainly attributed to the retained content of delta ferrite and the chemical inhomogeneity inside the gamma matrix (gamma close to delta has ~2 wt.% higher Cr but ~2 wt.% lower Ni), but TMT enhanced the chemical homogeneity and thus austenite stability. By contrast, the LPBF process led directly, i.e. without any thermomechanical treatment, to a fully austenitic structure with homogeneous elemental distribution in the ASS. These results confirmed that the presence of delta and the chemical inhomogeneity inside gamma matrix, which promoted the deformation-induced martensitic transformation and the associated H enrichment at the gamma-alpha' interface, was the primary reason for the severe H-assisted failure.

Superconductivity is identified by the emergence of a macroscopic zero-resistance state, typically inferred from a vanishing four-probe voltage at finite current. That inference assumes spatially uniform conduction-e.g., at least one continuous superconducting path between the current leads and voltage electrodes that sample a finite potential gradient-and can fail if the drive current bypasses the electrodes or if narrow filaments short the current contacts. Here we introduce a methodology to test these assumptions in superconductors, by using spatially resolved measurements of local variations in dc using cryogenic conductive atomic-force microscopy (cAFM). Using Fe(Se,Te) as a model system, we find that despite bulk measurements consistent with a homogeneous superconducting state, the material exhibits a heterogeneous conducting landscape: micrometre-scale superconducting regions coexist with relatively insulating areas. We further show that cAFM resolves conductance fluctuations at 20 K (> TC) that vary between repeated scans, consistent with expectations for short-lived, pre-formed Cooper pairs in the BCS-BEC crossover regime. These results establish cAFM as a practical tool to validate assumptions underlying four-probe transport and underscore the need for direct spatial probes in materials whose macroscopic response can conceal nanoscale inhomogeneity. Accurate identification of macroscopic properties is critical for materials classes like superconductors that are defined by their macroscopic properties.

Stepped well-ordered semiconductor surfaces are important as nanotemplates for the fabrication of one-dimensional nanostructures which are candidates of intriguing electronic properties. Therefore a detailed understanding of the underlying stepped substrates is crucial for advances in this field. Although measurements of step edges are challenging for scanning force microscopy (SFM), here we present for the first time simultaneous atomically resolved SFM and Kelvin probe force microscopy (KPFM) images of a silicon vicinal surface. We find that the local contact potential difference is not homogeneous over all silicon atoms, contrary to the common understanding of the work function. For the interpretation of the data we performed density functional theory (DFT) calculations. We explain the atomic-scale electronic features by differences in the surface dipole distribution caused by a Smoluchowski-type effect. E.g., at step edges the partial negative charge is larger at the lower-lying atoms closer to the bulk than at the atoms more protruding towards the vacuum. This is the first manifestation of such type of effect on a semiconductor surface. The DFT images accurately reproduce the experiments even without including the tip in the calculations. This underlines that the high-resolution KPFM images indeed show the intrinsic properties of the surface and not only tip-surface interactions.

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 phase separation at grain boundaries, we derive a density-based phase-field model. In this model, we describe the grain boundary free energy based on available bulk thermodynamic data while an atomic grain boundary density is obtained using atomistic simulations. To benchmark the performance of the model, we study Mn grain boundary segregation in the Fe--Mn system. 3D simulation results are compared against atom probe tomography measurements. We show that a continuous increase in the alloy composition results in a discontinuous jump in the Mn grain boundary segregation. This jump corresponds to an interfacial spinodal phase separation. For alloy compositions above the interfacial spinodal, we found a transient spinodal phase separation phenomenon which 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 separation at grain boundaries.

This work presents the new template matching capabilities implemented in Pyxem, an open source Python library for analyzing four-dimensional scanning transmission electron microscopy (4D-STEM) data. Template matching is a brute force approach for deriving local crystal orientations. It works by comparing a library of simulated diffraction patterns to experimental patterns collected with nano-beam and precession electron diffraction (NBED and PED). This is a computationally demanding task, therefore the implementation combines efficiency and scalability by utilizing multiple CPU cores or a graphical processing unit (GPU). The code is built on top of the scientific python ecosystem, and is designed to support custom and reproducible workflows that combine the image processing, template library generation, indexation and visualisation all in one environment. The tools are agnostic to file size and format, which is significant in light of the increased adoption of pixelated detectors from different manufacturers. This paper details the implementation, validation, and benchmarking results of the method. The method is illustrated by calculating orientation maps of nanocrystalline materials and precipitates embedded in a crystalline matrix. The combination of speed and flexibility opens the door for automated parameter studies and real-time on-line orientation mapping inside the TEM.

Atom probe tomography (APT) helps elucidate the link between the nanoscale chemical variations and physical properties, but it has limited structural resolution. Field ion microscopy (FIM), a predecessor technique to APT, is capable of attaining atomic resolution along certain sets of crystallographic planes albeit at the expense of elemental identification. We demonstrate how two commercially-available atom probe instruments, one with a straight flight path and one fitted with a reflectron-lens, can be used to acquire time-of-flight mass spectrometry data concomitant with a FIM experiment. We outline various experimental protocols making use of temporal and spatial correlations to best discriminate field evaporated signals from the large field ionised background signal, demonstrating an unsophisticated yet efficient data mining strategy to provide this discrimination. We discuss the remaining experimental challenges that need be addressed, notably concerned with accurate detection and identification of individual field evaporated ions contained within the high field ionised flux that contributes to a FIM image. Our hybrid experimental approach can, in principle, exhibit true atomic resolution with elemental discrimination capabilities, neither of which atom probe nor field ion microscopy can individually fully deliver - thereby making this new approach, here broadly termed analytical field ion microscope (aFIM), unique.

Frictional contacts lead to the formation of a surface layer called the third body, consisting of wear particles and structures resulting from their agglomerates. Its behavior and properties at the nanoscale control the macroscopic tribological performance. It is known that wear particles and surface topography evolve with time and mutually influence one another. However, the formation of the mature third body is largely uncharted territory and the properties of its early stages are unknown. Here we show how a third body initially consisting of particles acting as roller bearings transitions into a shear-band-like state by forming adhesive bridges between the particles. Using large-scale atomistic simulations on a brittle model material, we find that this transition is controlled by the growth and increasing disorganization of the particles with increasing sliding distance. Sliding resistance and wear rate are at first controlled by the surface roughness, but upon agglomeration wear stagnates and friction becomes solely dependent on the real contact area in accordance with the plasticity theory of contact by Bowden and Tabor.

Bimetallic nanoparticles are often superior candidates for a wide range of technological and biomedical applications, thanks to their enhanced catalytic, optical, and magnetic properties, which are often better than their monometallic counterparts. Most of their properties strongly depend on their chemical composition, crystallographic structure, and phase distribution. However, little is known of how their crystal structure, on the nanoscale, transforms over time at elevated temperatures, even though this knowledge is highly relevant in case nanoparticles are used in, e.g., high-temperature catalysis. Au-Fe is a promising bimetallic system where the low-cost and magnetic Fe is combined with catalytically active and plasmonic Au. Here, we report on the in situ temporal evolution of the crystalline ordering in Au-Fe nanoparticles, obtained from a modern laser ablation in liquids synthesis. Our in-depth analysis, complemented by dedicated atomistic simulations, includes a detailed structural characterization by X-ray diffraction and transmission electron microscopy as well as atom probe tomography to reveal elemental distributions down to a single atom resolution. We show that the Au-Fe nanoparticles initially exhibit highly complex internal nested nanostructures with a wide range of compositions, phase distributions, and size-depended microstrains. The elevated temperature induces a diffusion-controlled recrystallization and phase merging, resulting in the formation of a single face-centered-cubic ultrastructure in contact with a body-centered cubic phase, which demonstrates the metastability of these structures. Uncovering these unique nanostructures with nested features could be highly attractive from a fundamental viewpoint as they could give further insights into the nanoparticle formation mechanism under non-equilibrium conditions.

The eutectic Ga-In (EGaIn) alloy has low vapor pressure, low toxicity, high thermal and electrical conductivities, and thus has shown a great potential for smart material applications. For such applications, EGaIn is maintained above its melting point, below which it undergoes solidification and phase separation. A scientific understanding of the structural and compositional evolution during thermal cycling could help further assess the application range of low-melting-point fusible alloys. Here, we use an integrated suite of cryogenically-enabled advanced microscopy & microanalysis to better understand phase separation and (re)mixing processes in EGaIn. We reveal an overlooked thermal-stimulus-response behaviour for frozen mesoscale EGaIn at cryogenic temperatures, with a sudden volume expansion observed during in-situ heat-cycling, associated with the immiscibility between Ga and In during cooling and the formation of metastable Ga phases. These results emphasize the importance of the kinetics of rejuvenation, and open new paths for EGaIn as a self-healing material.

Fossil-free ironmaking is indispensable for reducing massive anthropogenic CO2 emissions in the steel industry. Hydrogen-based direct reduction (HyDR) is among the most attractive solutions for green ironmaking, with high technology readiness. The underlying mechanisms governing this process are characterized by a complex interaction of several chemical (phase transformations), physical (transport), and mechanical (stresses) phenomena. Their interplay leads to rich microstructures, characterized by a hierarchy of defects ranging across several orders of magnitude in length, including vacancies, dislocations, internal interfaces, and free surfaces in the form of cracks and pores. These defects can all act as reaction, nucleation, and diffusion sites, shaping the overall reduction kinetics. A clear understanding of the roles and interactions of these dynamically-evolving nano-/microstructure features is missing. Gaining better insights in these effects could enable improved access to the microstructure-based design of more efficient HyDR methods, with potentially high impact on the urgently needed decarbonization in the steel industry.

Tailoring the physical properties of complex materials for targeted applications requires optimizing the microstructure and crystalline defects that influence electrical and thermal transport, and mechanical properties. Laser surface remelting can be used to modify the sub-surface microstructure of bulk materials and hence manipulate their properties locally. Here, we introduce an approach to perform remelting in a reactive nitrogen atmosphere, in order to form nitrides and induce segregation of nitrogen to structural defects. These defects arise from the fast solidification of the full-Heusler Fe2VAl compound that is a promising thermoelectric material. Advanced scanning electron microscopy, including electron channelling contrast imaging and three-dimensional electron backscatter diffraction, is complemented by atom probe tomography to study the distribution of crystalline defects and their local chemical composition. We reveal a high density of dislocations, which are stable due to their character as geometrically necessary dislocations. At these dislocations and low-angle grain boundaries, we observe segregation of nitrogen and vanadium, which can be enhanced by repeated remelting in nitrogen atmosphere. We propose that this approach can be generalized to other additive manufacturing processes to promote local segregation and precipitation states, thereby manipulating physical properties.

Crack growth in stress corrosion cracking (SCC) in 7xxx Al alloys is an intermittent process, which generates successive crack arrest markings (CAMs) visible on the fracture surface. It is conjectured that H is generated at the crack tip during crack arrest, which then facilitates crack advancement through hydrogen embrittlement. Here, nanoscale imaging by 4D-scanning-transmission electron microscopy and atom probe tomography show that CAMs are produced by oxidation at the arrested crack tip, matrix precipitates dissolve and solute diffuse towards the growing CAM. Substantial homogenous residual strain remains underneath the fracture surface, indicative of non-localized plastic activity. Our study suggests that H induces crack propagation through decohesion.