Phase nucleation through confined spinodal fluctuations at crystal defects evidenced in Fe-Mn alloys

Structurally complex phase engineering enables hydrogen-tolerant Al alloys

Hydrogen embrittlement (HE) impairs the durability of aluminium (Al) alloys and hinders their use in a hydrogen economy1-3. Intermetallic compound particles in Al alloys can trap hydrogen and mitigate HE4, but these particles usually form in a low number density compared with conventional strengthening nanoprecipitates. Here we report a size-sieved complex precipitation in Sc-added Al-Mg alloys to achieve a high-density dispersion of both fine Al3Sc nanoprecipitates and in situ formed core-shell Al3(Mg, Sc)2/Al3Sc nanophases with high hydrogen-trapping ability. The two-step heat treatment induces heterogeneous nucleation of the Samson-phase Al3(Mg, Sc)2 on the surface of Al3Sc nanoprecipitates that are only above 10 nm in size. The size dependence is associated with Al3Sc nanoprecipitate incoherency, which leads to local segregation of magnesium and triggers the formation of Al3(Mg, Sc)2. The tailored distribution of dual nanoprecipitates in our Al-Mg-Sc alloy provides about a 40% increase in strength and nearly five times improved HE resistance compared with the Sc-free alloy, reaching a record tensile uniform elongation in Al alloys charged with H up to 7 ppmw. We apply this strategy to other Al-Mg-based alloys, such as Al-Mg-Ti-Zr, Al-Mg-Cu-Sc and Al-Mg-Zn-Sc alloys. Our work showcases a possible route to increase hydrogen resistance in high-strength Al alloys and could be readily adapted to large-scale industrial production.

Real-space visualization of a defect-mediated charge density wave transition

We study the coupled charge density wave (CDW) and insulator-to-metal transitions in the 2D quantum material 1T-TaS2. By applying in situ cryogenic 4D scanning transmission electron microscopy with in situ electrical resistance measurements, we directly visualize the CDW transition and establish that the transition is mediated by basal dislocations (stacking solitons). We find that dislocations can both nucleate and pin the transition and locally alter the transition temperature Tc by nearly ~75 K. This finding was enabled by the application of unsupervised machine learning to cluster five-dimensional, terabyte scale datasets, which demonstrate a one-to-one correlation between resistance-a global property-and local CDW domain-dislocation dynamics, thereby linking the material microstructure to device properties. This work represents a major step toward defect-engineering of quantum materials, which will become increasingly important as we aim to utilize such materials in real devices.

Stabilizing Supersaturation with Extreme Grain Refinement in Spinodal Aluminum Alloys

Supersaturated solid solutions can be formed in alloys from various non-equilibrium processes, but stabilizing the metastable phases against decomposition is challenging, particularly the spinodal decomposition that occurs via chemical fluctuations without energy barriers to nucleation. In this work, it is found that spinodal decomposition in supersaturated Al(Zn) solid solutions can be inhibited with straining-induced extreme grain refinement. For the refined supersaturated grains at the nanoscale, their spinodal decomposition is obviously resisted by the relaxed grain boundaries and reduced lattice defects. As grains are refined below 10 nm the decomposition is completely inhibited, in which atomic diffusion is blocked by the stable Schwarz crystal structure with vacancy-free grains. Extreme grain refinement offers a general approach to stabilize supersaturated phases with broadened compositional windows for property modulation of alloys.

Two-dimensional demixing within multilayered nanoemulsion films

Benefiting from the demixing of substances in the two-phase region, a smart polymer laminate film system that exhibits direction-controlled phase separation behavior was developed in this study. Here, nanoemulsion films (NEFs) in which liquid nanodrops were uniformly confined in a polymer laminate film through the layer-by-layer deposition of oppositely charged emulsion nanodrops and polyelectrolytes were fabricated. Upon reaching a critical temperature, the NEFs exhibited a micropore-guided demixing phenomenon. A simulation study based on coarse-grained molecular dynamics revealed that the perpendicular diffusion of oil droplets through the micropores generated in the polyelectrolyte layer is crucial for determining the coarsening kinetics and phase separation level, which is consistent with the experimental results. Considering the substantial advantages of this unique and tunable two-dimensional demixing behavior, the viability of using the as-proposed NEF system for providing an efficient route for the development of smart drug delivery patches was demonstrated.

Molecular organization of the early stages of nucleosome phase separation visualized by cryo-electron tomography

It has been proposed that the intrinsic property of nucleosome arrays to undergo liquid-liquid phase separation (LLPS) in vitro is responsible for chromatin domain organization in vivo. However, understanding nucleosomal LLPS has been hindered by the challenge to characterize the structure of the resulting heterogeneous condensates. We used cryo-electron tomography and deep-learning-based 3D reconstruction/segmentation to determine the molecular organization of condensates at various stages of LLPS. We show that nucleosomal LLPS involves a two-step process: a spinodal decomposition process yielding irregular condensates, followed by their unfavorable conversion into more compact, spherical nuclei that grow into larger spherical aggregates through accretion of spinodal materials or by fusion with other spherical condensates. Histone H1 catalyzes more than 10-fold the spinodal-to-spherical conversion. We propose that this transition involves exposure of nucleosome hydrophobic surfaces causing modified inter-nucleosome interactions. These results suggest a physical mechanism by which chromatin may transition from interphase to metaphase structures.

A sustainable ultra-high strength Fe18Mn3Ti maraging steel through controlled solute segregation and α-Mn nanoprecipitation

The enormous magnitude of 2 billion tons of alloys produced per year demands a change in design philosophy to make materials environmentally, economically, and socially more sustainable. This disqualifies the use of critical elements that are rare or have questionable origin. Amongst the major alloy strengthening mechanisms, a high-dispersion of second-phase precipitates with sizes in the nanometre range is particularly effective for achieving ultra-high strength. Here, we propose an alternative segregation-based strategy for sustainable steels, free of critical elements, which are rendered ultrastrong by second-phase nano-precipitation. We increase the Mn-content in a supersaturated, metastable Fe-Mn solid solution to trigger compositional fluctuations and nano-segregation in the bulk. These fluctuations act as precursors for the nucleation of an unexpected α-Mn phase, which impedes dislocation motion, thus enabling precipitation strengthening. Our steel outperforms most common commercial alloys, yet it is free of critical elements, making it a new platform for sustainable alloy design.

Recent demands to design alloys in a more sustainable way have discouraged the use of critical elements that are rare. Here the authors demonstrate a segregation-based strategy to produce a sustainable steel, Fe18Mn3Ti, without critical elements while achieving ultrahigh-strength.

Electric Fields Enhance Ice Formation from Water Vapor by Decreasing the Nucleation Energy Barrier

Video images of ice formation from moist air under temperature and electric potential gradients reveal that ambient electricity enhances ice production rates while changing the habit of ice particles formed under low supersaturation. The crystals formed under an electric field are needles and dendrites instead of the isometric ice particles obtained within a Faraday cage. Both a non-classical mechanism and classical nucleation theory independently explain the observed mutual feedback between ice formation and its electrification. The elongated shapes result from electrostatic repulsion at the crystal surfaces, opposing the attractive intermolecular forces and thus lowering the ice-air interfacial tension. The video images allow for the estimation of ice particle dimensions, weight, and speed within the electric field. Feeding this data on standard equations from electrostatics shows that the ice surface charge density attains 0.62–1.25 × 10−6 C·m−2, corresponding to 73–147 kV·m−1 potential gradients, reaching the range measured within thunderstorms. The present findings contribute to a better understanding of natural and industrial processes involving water phase change by acknowledging the presence and effects of the pervasive electric fields in the ambient environment.

The Influence of Metastable Cellular Structure on Deformation Behavior in Laser Additively Manufactured 316L Stainless Steel

Metastable cellular structures (MCSs) play a crucial role for the mechanical performance in concentrated alloys during non-equilibrium solidification process. In this paper, typifying the heterogeneous 316L stainless steel by laser additive manufacturing (LAM) process, we examine the microstructures in cellular interiors and cellular boundaries in detail, and reveal the interactions of dislocations and twins with cellular boundaries. Highly ordered coherent precipitates present along the cellular boundary, resulting from spinodal decomposition by local chemical fluctuation. The co-existences of precipitates and high density of tangled dislocations at cellular boundaries serve as walls for extra hardening. Furthermore, local chemical fluctuation in MCSs inducing variation in stacking fault energy is another important factor for ductility enhancement. These findings shed light on possible routines to further alter nanostructures, including precipitates and dislocation structures, by tailoring local chemistry in MCSs during LAM.

Ultrahigh specific strength in a magnesium alloy strengthened by spinodal decomposition

Strengthening of magnesium (Mg) is known to occur through dislocation accumulation, grain refinement, deformation twinning, and texture control or dislocation pinning by solute atoms or nano-sized precipitates. These modes generate yield strengths comparable to other engineering alloys such as certain grades of aluminum but below that of high-strength aluminum and titanium alloys and steels. Here, we report a spinodal strengthened ultralightweight Mg alloy with specific yield strengths surpassing almost every other engineering alloy. We provide compelling morphological, chemical, structural, and thermodynamic evidence for the spinodal decomposition and show that the lattice mismatch at the diffuse transition region between the spinodal zones and matrix is the dominating factor for enhancing yield strength in this class of alloy.

Phase-Field Modeling of Chemoelastic Binodal/Spinodal Relations and Solute Segregation to Defects in Binary Alloys

Microscopic phase-field chemomechanics (MPFCM) is employed in the current work to model solute segregation, dislocation-solute interaction, spinodal decomposition, and precipitate formation, at straight dislocations and configurations of these in a model binary solid alloy. In particular, (i) a single static edge dipole, (ii) arrays of static dipoles forming low-angle tilt (edge) and twist (screw) grain boundaries, as well as at (iii) a moving (gliding) edge dipole, are considered. In the first part of the work, MPFCM is formulated for such an alloy. Central here is the MPFCM model for the alloy free energy, which includes chemical, dislocation, and lattice (elastic), contributions. The solute concentration-dependence of the latter due to solute lattice misfit results in a strong elastic influence on the binodal (i.e., coexistence) and spinodal behavior of the alloy. In addition, MPFCM-based modeling of energy storage couples the thermodynamic forces driving (Cottrell and Suzuki) solute segregation, precipitate formation and dislocation glide. As implied by the simulation results for edge dislocation dipoles and their configurations, there is a competition between (i) Cottrell segregation to dislocations resulting in a uniform solute distribution along the line, and (ii) destabilization of this distribution due to low-dimensional spinodal decomposition when the segregated solute content at the line exceeds the spinodal value locally, i.e., at and along the dislocation line. Due to the completely different stress field of the screw dislocation configuration in the twist boundary, the segregated solute distribution is immediately unstable and decomposes into precipitates from the start.

Microstructure and Thermal Analysis of Metastable Intermetallic Phases in High-Entropy Alloy CoCrFeMo0.85Ni

CoCrFeMoNi high entropy alloys (HEAs) exhibit several promising characteristics for potential applications of high temperature coating. In this study, metastable intermetallic phases and their thermal stability of high-entropy alloy CoCrFeMo_0.85Ni were investigated via thermal and microstructural analyses. Solidus and liquidus temperatures of CoCrFeMo_0.85Ni were determined by differential thermal analysis as 1323 °C and 1331 °C, respectively. Phase transitions also occur at 800 °C and 1212 °C during heating. Microstructure of alloy exhibits a single-phase face-centred cubic (FCC) matrix embedded with the mixture of (Co, Cr, Fe)-rich tetragonal phase and Mo-rich rhombohedron-like phase. The morphologies of two intermetallics show matrix-based tetragonal phases bordered by Mo-rich rhombohedral precipitates around their perimeter. The experimental results presented in our paper provide key information on the microstructure and thermal stability of our alloy, which will assist in the development of similar thermal spray HEA coatings.

Machine-learning-enhanced time-of-flight mass spectrometry analysis

Mass spectrometry is a widespread approach used to work out what the constituents of a material are. Atoms and molecules are removed from the material and collected, and subsequently, a critical step is to infer their correct identities based on patterns formed in their mass-to-charge ratios and relative isotopic abundances. However, this identification step still mainly relies on individual users' expertise, making its standardization challenging, and hindering efficient data processing. Here, we introduce an approach that leverages modern machine learning technique to identify peak patterns in time-of-flight mass spectra within microseconds, outperforming human users without loss of accuracy. Our approach is cross-validated on mass spectra generated from different time-of-flight mass spectrometry (ToF-MS) techniques, offering the ToF-MS community an open-source, intelligent mass spectra analysis.

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A machine-learning method provides reliable atomic/molecular labels for ToF-MS

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No human labeling or prior information required

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The training dataset is artificially generated based on isotopic abundances

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Method validated on a variety of materials and two ToF-MS-based techniques

Time-of-flight mass spectrometry (ToF-MS) is a mainstream analytical technique widely used in biology, chemistry, and materials science. ToF-MS provides quantitative compositional analysis with high sensitivity across a wide dynamic range of mass-to-charge ratios. A critical step in ToF-MS is to infer the identity of the detected ions. Here, we introduce a machine-learning-enhanced algorithm to provide a user-independent approach to performing this identification using patterns from the natural isotopic abundances of individual atomic and molecular ions, without human labeling or prior knowledge of composition. Results from several materials and techniques are compared with those obtained by field experts. Our open-source, easy-to-implement, reliable analytic method accelerates this identification process. A wide range of ToF-MS-based applications can benefit from our approach, e.g., hunting for patterns of biomarkers or for contamination on solid surfaces in high-throughput data.

Atom probe tomography

Atom probe tomography (APT) provides three-dimensional compositional mapping with sub-nanometre resolution. The sensitivity of APT is in the range of parts per million for all elements, including light elements such as hydrogen, carbon or lithium, enabling unique insights into the composition of performance-enhancing or lifetime-limiting microstructural features and making APT ideally suited to complement electron-based or X-ray-based microscopies and spectroscopies. Here, we provide an introductory overview of APT ranging from its inception as an evolution of field ion microscopy to the most recent developments in specimen preparation, including for nanomaterials. We touch on data reconstruction, analysis and various applications, including in the geosciences and the burgeoning biological sciences. We review the underpinnings of APT performance and discuss both strengths and limitations of APT, including how the community can improve on current shortcomings. Finally, we look forwards to true atomic-scale tomography with the ability to measure the isotopic identity and spatial coordinates of every atom in an ever wider range of materials through new specimen preparation routes, novel laser pulsing and detector technologies, and full interoperability with complementary microscopy techniques.

A model for grain boundary thermodynamics

Systematic microstructure design requires reliable thermodynamic descriptions of each and all microstructure elements. While such descriptions are well established for most bulk phases, thermodynamic assessment of microstructure defects is challenging because of their individualistic nature. In this paper, a model is devised for assessing grain boundary thermodynamics based on available bulk thermodynamic data. We propose a continuous relative atomic density field and its spatial gradients to describe the grain boundary region with reference to the homogeneous bulk and derive the grain boundary Gibbs free energy functional. The grain boundary segregation isotherm and phase diagram are computed for a regular binary solid solution, and qualitatively benchmarked for the Pt-Au system. The relationships between the grain boundary's atomic density, excess free volume, and misorientation angle are discussed. Combining the current density-based model with available bulk thermodynamic databases enables constructing databases, phase diagrams, and segregation isotherms for grain boundaries, opening possibilities for studying and designing heterogeneous microstructures.

New approach for FIB-preparation of atom probe specimens for aluminum alloys

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.

Reflections on the Analysis of Interfaces and Grain Boundaries by Atom Probe Tomography

Interfaces play critical roles in materials and are usually both structurally and compositionally complex microstructural features. The precise characterization of their nature in three-dimensions at the atomic scale is one of the grand challenges for microscopy and microanalysis, as this information is crucial to establish structure-property relationships. Atom probe tomography is well suited to analyzing the chemistry of interfaces at the nanoscale. However, optimizing such microanalysis of interfaces requires great care in the implementation across all aspects of the technique from specimen preparation to data analysis and ultimately the interpretation of this information. This article provides critical perspectives on key aspects pertaining to spatial resolution limits and the issues with the compositional analysis that can limit the quantification of interface measurements. Here, we use the example of grain boundaries in steels; however, the results are applicable for the characterization of grain boundaries and transformation interfaces in a very wide range of industrially relevant engineering materials.

Transformation of siderite to goethite by humic acid in the natural environment

Humic acid (HA) is particularly important in iron-bearing mineral transformations and erosion at the water-mineral boundary zone of the Earth. In this study, three stages of the possible pathway by which HA causes mineral transformation from siderite to goethite are identified. Firstly, a Fe(II)-HA complex is formed by chelation, which accelerates the dissolution and oxidation of Fe(II) from the surface of siderite. As the Fe(II)-HA complex retains Fe atoms in close proximity of each other, ferrihydrite is formed by the agglomeration and crystallization. Finally, the ferrihydrite structurally rearranges upon attachment to the surface of goethite crystals and merges with its structure. The influence of low concentrations of HA (0-2 mg/L) on phosphate adsorption is found to be beneficial by the inducing of new mineral phases. We believe that these results provide a greater understanding of the impact of HA in the biogeochemical cycle of phosphate, mineral transformation.

Interplay of Chemistry and Faceting at Grain Boundaries in a Model Al Alloy

The boundary between two crystal grains can decompose into arrays of facets with distinct crystallographic character. Faceting occurs to minimize the system's free energy, i.e., when the total interfacial energy of all facets is below that of the topologically shortest interface plane. In a model Al-Zn-Mg-Cu alloy, we show that faceting occurs at investigated grain boundaries and that the local chemistry is strongly correlated with the facet character. The self-consistent coevolution of facet structure and chemistry leads to the formation of periodic segregation patterns of 5-10 nm, or to preferential precipitation. This study shows that segregation-faceting interplay is not limited to bicrystals but exists in bulk engineering Al alloys and hence affects their performance.

3D nanostructural characterisation of grain boundaries in atom probe data utilising machine learning methods

Boosting is a family of supervised learning algorithm that convert a set of weak learners into a single strong one. It is popular in the field of object tracking, where its main purpose is to extract the position, motion, and trajectory from various features of interest within a sequence of video frames. A scientific application explored in this study is to combine the boosting tracker and the Hough transformation, followed by principal component analysis, to extract the location and trace of grain boundaries within atom probe data. Before the implementation of this method, these information could only be extracted manually, which is time-consuming and error-prone. The effectiveness of this method is demonstrated on an experimental dataset obtained from a pure aluminum bi-crystal and validated on simulated data. The information gained from this method can be combined with crystallographic information directly contained within the data, to fully define the grain boundary character to its 5 degrees of freedom at near-atomic resolution in three dimensions. It also enables local atomic compositional and geometric information, i.e. curvature, to be extracted directly at the interface.

An Automated Computational Approach for Complete In-Plane Compositional Interface Analysis by Atom Probe Tomography

We introduce an efficient, automated computational approach for analyzing interfaces within atom probe tomography datasets, enabling quantitative mapping of their thickness, composition, as well as the Gibbsian interfacial excess of each solute. Detailed evaluation of an experimental dataset indicates that compared with the composition map, the interfacial excess map is more robust and exhibits a relatively higher resolution to reveal compositional variations. By field evaporation simulations with a predefined emitter mimicking the experimental dataset, the impact of trajectory aberrations on the measurement of the thickness, composition, and interfacial excess of the decorated interface are systematically analyzed and discussed.

Linear Complexions: Metastable Phase Formation and Coexistence at Dislocations

The unique three-phase coexistence of metastable B2-FeNi with stable L1_{0}-FeNi and L1_{2}-FeNi_{3} is discovered near edge dislocations in body-centered cubic Fe-Ni alloys using atomistic simulations. Stable nanoscale precipitate arrays, formed along the compression side of dislocation lines and defined as linear complexions, were observed for a wide range of compositions and temperatures. By analyzing the thermodynamics associated with these phase transitions, we are able to explain the metastable phase formation and coexistence, in the process defining new research avenues for theoretical and experimental investigations.

Strain-Induced Asymmetric Line Segregation at Faceted Si Grain Boundaries

The unique combination of atomic-scale composition measurements, employing atom probe tomography, atomic structure determination with picometer resolution by aberration-corrected scanning transmission electron microscopy, and atomistic simulations reveals site-specific linear segregation features at grain boundary facet junctions. More specific, an asymmetric line segregation along one particular type of facet junction core, instead of a homogeneous decoration of the facet planes, is observed. Molecular-statics calculations show that this segregation pattern is a consequence of the interplay between the asymmetric core structure and its corresponding local strain state. Our results contrast with the classical view of a homogeneous decoration of the facet planes and evidence a complex segregation patterning.