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At least 109 records · Page 6

Insights into Defect-Mediated Nucleation of the Equilibrium B2 Phase in Face-Centered Cubic High-Entropy Alloys

A fine scale second phase distribution is important for strengthening metallic materials. High precipitate density is often difficult to achieve due to sluggish precipitation kinetics and limited nucleation sites. Based on the CALPHAD predictions, transition element-based complex concentrated alloys (CCAs)/ High Entropy Alloys (HEAs), have a highly stable face-centered cubic (FCC) phase and intermetallic B2 phase. The precipitation of the strengthening B2 phase is often limited to low fractions in these alloys due to a high nucleation barrier in the FCC matrix. Here, by illustrating in three different alloys, we present a defect mediated nucleation of a high fraction equilibrium B2 phase. The degree of cold work is used to manipulate the phase fraction, morphology, and distribution of B2 precipitates. Our approach synergistically improves the strength and ductility of these alloys and is widely applicable to many other complex alloys.

Sharma, Abhishek↗

Interactive Exploration of High-Dimensional Phase Diagrams

High-dimensional thermodynamic phase stability databases are becoming increasingly common due to the convergence of three recent trends: (i) the widespread interest in so-called “high-entropy” alloys, (ii) the availability of high-throughput computational assessments of phase stability in broad composition spaces and (iii) the ongoing development of ever-increasingly broad, multicomponent, multiphase CALPHAD databases. Although automated computational tools can readily process such high-dimensional data, scientists are often unable to visualize the relevant phase relations, an ability that is crucial to gaining an intuitive understanding of the stability constraints governing materials design. The present work addresses this need by providing algorithms that enable the interactive exploration of phase equilibria in high-dimensional spaces. These algorithms concentrate the complex nonlinear nonsmooth optimization needed into a preprocessing step that generates a large number of high-dimensional yet elementary graphical primitives. Furthermore, these primitives can then be cross-sectioned to yield 3-dimensional views in a computationally efficient manner that enables an interactive exploration of high-dimensional spaces. All of these operations are highly parallelizable, thus facilitating scaling of this method to large data sets.

36 MATERIALS SCIENCE↗

Evaluating the grain-scale deformation behavior of a single-phase FCC high entropy alloy using synchrotron high energy diffraction microscopy

We report although the deformation behavior of high-entropy alloys (HEAs) has been extensively studied at the macroscale, many important properties have yet to be explored for these alloys at the microscale, thus hampering accurate prediction of damage and failure processes. Synchrotron high-energy diffraction microscopy (HEDM) and fast-Fourier transform-based crystal plasticity modeling was conducted to investigate the three-dimensional (3D) grain-resolved micromechanical response for approximately 1,900 constituent grains within a single-phase FCC HEA up to 1% applied strain. The evolution of grain-resolved elastic strains, lattice reorientations, and maximum resolved shear stresses (mRSS) were evaluated to quantify elastic, yield, and fully plastic behavior. Overall, the initial critical resolved shear stress (CRSS), determined via in situ HEDM and companion modeling, was found to be > 20% higher than estimated using the classical polycrystalline Taylor factor (M = 3.06). However, a descriptive parameter based on the average grain-resolved Taylor factor ($\overline{M}$) was found to show excellent agreement with plastic yielding behavior observed within HEDM datasets. Noticeable deviations in HEDM lattice reorientations compared to both EVP-FFT simulations and classical predictions for FCC polycrystals were discovered, highlighting the complexity in correlating local lattice reorientations, Taylor, and Schmid factors with plastic response for this material at the grain-scale. Therefore, it is anticipated that the overall trends and parameter identification of 3D grain-resolved properties in this study can serve as an important foundation for continued mesoscale investigation on both well-established and newly developed Cantor-like HEAs.

36 MATERIALS SCIENCE↗

Vacancy diffusion barrier spectrum and diffusion correlation in multicomponent alloys

Vacancy diffusion serves a crucial role in many important kinetic behaviors and properties of multicomponent alloys. Essential questions, however, persist regarding how chemical complexity affects diffusion and what unique characteristics, if any, set these alloys apart from traditional metals. Using neural network kinetics model, we study vacancy diffusion in NbMoTa alloy across a broad temperature range (2600 to 800 K). Unlike pure metals, the two key diffusion parameters—diffusion correlation factor f and activation energy ΔG m —are not constant in alloys, but instead substantially decrease with decreasing temperature. This temperature dependence arises from a reduced number of active vacancy jump pathways at lower temperatures, leading to more correlated diffusion. Upon examining vacancy diffusion throughout the entire compositional space of the Nb-Mo-Ta system, we discover that the slowest vacancy diffusion surprisingly occurs in the non-equimolar region, rather than the equimolar concentration where the configurational entropy is highest. The diffusion barrier spectrum, characterizing the diffusion energy landscape, is an intrinsic material characteristic, which controls both f and ΔG m and, thereby, the diffusivity. Lastly, we find that the vacancy diffusion rate drops noticeably in the presence of local chemical order in the NbMoTa system, particularly for MoTa alloys with long-range B2 order.

Defects↗

Defect and satellite characteristics of additive manufacturing metal powders

Metal additive manufacturing (AM) requires high-quality metal powders to three-dimensionally (3D) print metallic components with complex and customizable geometries. The lack of quantification of AM metal powders creates quality control challenges for 3D printed components, increases the uncertainty of printing reliability and net cost of inspected and certified printed components, and reduces the recyclability of used powders. However, critical characteristics of AM metal powders that are decisive factors for the 3D printing process, such as internal porosity, contamination, and satellite feature, remain ambiguous. In this work, we developed a novel approach to 3D quantify key characteristics of AM metal powders down to individual particles by using high-resolution synchrotron x-ray computed tomography. Empowered by the penetrative capability of high-energy x-ray, internal porosity and contamination within as-atomized metal powders from high-entropy alloys to nickel-based superalloys were evaluated. Additionally, the newly-developed dispersion method enables the homogeneous separation of individual particles, and consequently, results in the implementation of 3D particle shape analysis. To resolve a major challenge of identification and quantification of satellite-feature particles in as-atomized AM metal powders, the satellite features were quantitated by modeling and analyzing the shape parameter of local thickness variance. Furthermore, the 3D analytical methods of particle assessment in this study can be applied to other materials systems like rock, food, and pharmaceutical particles, and provide insights for process optimization across powder metallurgy, concrete, food and pharmaceutical manufacturing, and AM industries.

36 MATERIALS SCIENCE↗

Neural-network model for force prediction in multi-principal-element alloys

Atomistic simulations can provide useful insights into the physical properties of multi-principal-element alloys. However, classical potentials mostly fail to capture key quantum (electronic-structure) effects. Here we present a deep 3D convolutional neural network (3D CNN) based framework combined with a voxelization technique to design interatomic potentials for chemically complex alloys. We highlight the performance of the 3D CNN model and its efficacy in computing potentials using the medium-entropy alloy TaNbMo. In order to provide insights into the effect of voxel resolution, we implemented two approaches based on the inner and outer bounding boxes. An efficient 3D CNN model, which is as accurate as the density-functional theory (DFT) approach, for calculating potentials will provide a promising schema for accurate atomistic simulations of structure and dynamics of general multi-principle element alloys.

36 MATERIALS SCIENCE↗

Friction surface layer deposition of triple-phase Al 10 Cr 12 Fe 35 Mn 23 Ni 20 high entropy alloy: Process optimization and microstructural evolution

A high-strength Co-free triple-phase Al 10 Cr 12 Fe 35 Mn 23 Ni 20 high-entropy alloy (HEA) was successfully fabricated using Friction Surface Layer Deposition (FSLD), a bulk manufacturing method. Multiple single-layer deposits were produced by varying forging force (F) and traverse speeds (T r ) to optimize the process parameters. The optimized conditions (F = 40 kN & T r = 200 mm/min) were then applied to manufacture a scaled-up multi-layer specimen. The initial microstructure of the HEA consisted of coarse grains of the soft FCC-phase, long columnar dendrites of the hard BCC-phase, and small precipitates of the harder B2-phase within the BCC-dendrites. During FSLD, the FCC-matrix underwent continuous dynamic recrystallization due to high-temperature severe plastic deformation, forming finer equiaxed grains. Simultaneously, the BCC-dendrites fractured into smaller fragments, some of which experienced partial growth and coarsening under applied stress, resulting in an hourglass morphology. In contrast, the small B2-precipitates within the BCC-fragments dissolved during the elevated temperatures of FSLD and reprecipitated as substantially finer precipitates during continuous cooling post-FSLD. Additionally, the orientation relationships between the FCC and BCC/B2 phases were completely destroyed by the severe thermoplastic deformation inherent to FSLD. The microstructural refinements led to a substantial improvement in hardness from 177 HV to 283 HV, driven by Hall-Petch strengthening. The increased number of interfaces, including coherent BCC-B2 interfaces, potentially enhances the sink strength and radiation tolerance of the HEA, making it a promising candidate for nuclear applications. In conclusion, this study also highlights FSLD as a versatile technique for achieving tunable properties in HEAs, with detailed schematics illustrating the complex mechanisms of phase transformations during processing.

Additive Manufacturing↗

The microstructure and He + ion irradiation behavior of novel low-activation W-Ta-Cr-V refractory high entropy alloy for nuclear applications

Microstructure and nanohardness of a nearly equimolar W-Ta-Cr-V high entropy alloy (HEA), as well as its irradiation response under He + irradiation, were investigated. The single-phase body-centered cubic nanostructured alloy with a 1 µm thick layer was fabricated on a silicon substrate using a magnetron sputtering method. The HEA film has a complex microstructure consisting of micrometric domains that exhibit internal nanostructure controlled by their crystal orientation. The measured nanohardness of the W-Ta-Cr-V alloy is 13 ± 2 GPa, which significantly exceeds the hardness of nanocrystalline tungsten as a result of the high solid-solution strengthening effect. In order to evaluate the irradiation resistance of the HEA film, the material was irradiated with 200 keV He + ions at room temperature, with two different ion fluences: 1 × 10 16 and 5 × 10 16 ions/cm 2 . Using transmission electron microscopy, a high density of extremely fine He bubbles is observed that were uniformly distributed in the matrix. The increase of He + ion fluence increased the density of bubbles, whereas their size remained at a similar level, which indicates that the damage proceeds by the nucleation of additional He bubbles, not by their growth.

36 MATERIALS SCIENCE↗

Entropy-Driven Structural Evolution in Ceramic Oxides

High-entropy ceramics, with five or more elements randomly occupying the same cation crystallographic sites, offer vast compositional diversity and unique properties for material design and applications. However, for many dissimilar elements, entropic stabilization cannot overcome the enthalpic barrier to cation substitution. As a result, most high-entropy ceramics incorporate only a few similar elements, limiting the in-depth exploration of the effect of entropy on ceramic properties. Here, we first use density functional theory to model fluorite crystal structures composed of 1-10 elements and then experimentally present practical fluorite oxide nanostructures containing 1, 3, 8, and 15 metals, as well as a record-breaking 25-element high-entropy ceramic incorporating a diverse palette of rare-earth, transition, alkaline, p-block, and noble metals. As entropy increases, structural and configurational disorder in the solid solution rises, altering structural features such as lattice distortion, crystallinity, homogeneity, defect density, and thermal stability. This research provides new insights and understanding of the role of entropy in stabilizing compositionally complex ceramics.

Liu, Shuo↗

Long-range magnetic order with disordered spin orientations in a high-entropy antiferromagnet

Disorder in magnetic systems typically suppresses long-range order, promoting short-range states such as spin glasses and magnetic clusters. This is particularly prominent in high-entropy materials, characterized by the random distributions of local magnetic entities and exchange interactions. However, in rare exceptions, long-range magnetic order can persist in high-entropy systems, while the microscopic characters and underlying mechanisms remain elusive, especially the magnetic behaviors of individual elements. Here, combining neutron diffraction and resonant soft x-ray scattering, we have conducted an element-specific investigation into the magnetic order of a high-entropy honeycomb-lattice van der Waals material (Mn 1/4 Fe 1/4 Co 1/4 Ni 1/4 )PS 3 . Despite significant atomic disorder, long-range zigzag antiferromagnetic order is observed below 72 K, with all four transition-metal elements participating in a unified phase transition. However, the spin orientations of various elements are distinct, attributed to the competition between single-ion anisotropies and exchange interactions. Our findings showcase a novel form of long-range magnetic order with disordered spin orientations, which is synergically stabilized by distinct magnetic elements in a high entropy magnet, offering a new paradigm for understanding complex magnetic systems.

Shen, Yao [Chinese Academy of Sciences (CAS), Beij↗

Deep Gaussian process-based cost-aware batch Bayesian optimization for complex materials design campaigns

The accelerating pace and expanding scope of materials discovery demand optimization frameworks that efficiently navigate vast design spaces with complex response surfaces while judiciously allocating limited evaluation resources. We present a cost-aware, batch Bayesian optimization scheme powered by deep Gaussian process (DGP) surrogates and a heterotopic querying strategy. Our DGP surrogate, formed by stacking GP layers, models complex hierarchical relationships among high-dimensional compositional features and captures correlations across multiple target properties, propagating uncertainty through successive layers. We integrate evaluation cost into an upper-confidence-bound acquisition extension, which, together with heterotopic querying, proposes small batches of candidates in parallel, balancing exploration of under-characterized regions with exploitation of high-mean, low-variance predictions across correlated properties. Applied to refractory high-entropy alloys for high-temperature applications, our framework converges to optimal formulations in fewer iterations with cost-aware queries than conventional GP-based BO, highlighting the value of deep, uncertainty-aware, cost-sensitive strategies in materials campaigns.

36 MATERIALS SCIENCE↗

High-entropy halide perovskite single crystals stabilized by mild chemistry

High entropy materials are excellent candidates for a range of functional materials but traditionally require high-temperature synthetic procedures over 1000°C and complex processing techniques such as hot rolling to form. One route to address the extreme synthetic requirements for high entropy materials should involve designing crystal structures with ionic bonding networks and low cohesive energies. Here, we develop room-temperature (20°C) and low temperature (80°C) solution synthesis procedures for a new class of metal-halide perovskite high entropy semiconductor (HES) single crystals. Due to the soft, ionic lattice nature of the class of metal-halide perovskites, these HES single crystals are designed on the cubic Cs 2 MCl 6 (M = Zr 4+ , Sn 4+ , Te 4+ , Hf 4+ , Re 4+ , Os 4+ , Ir 4+ , or Pt 4+ ) vacancy-ordered double perovskite structure from the self-assembly of stabilized complexes in multielement inks, namely free Cs + cations and five or six different isolated [MCl6] 2- anionic octahedral molecules well-mixed in strong hydrochloric acid. The resulting single-phase single crystals span two HES families of five- and six-elements occupying the M-site as a random alloy in near-equimolar ratios, with the overall Cs 2 MCl 6 crystal structure and stoichiometry maintained. In conclusion, the incorporation of various [MCl 6 ] 2- octahedral molecular orbitals disordered across the high entropy five- and six-element Cs 2 MCl 6 single crystals produces complex vibrational and electronic structures with energy transfer interactions between the confined exciton states of the five or six different isolated octahedral molecules.

36 MATERIALS SCIENCE↗

Denary oxide nanoparticles as highly stable catalysts for methane combustion

Oxide nanoparticles with elemental and structural diversity are widely studied for catalysis and energy applications. While compositional control holds great promise for materials discovery, current oxide nanoparticles are typically limited to a few cations due to the intrinsic complexity in nanoscale multi-element mixing. Here we report the rational design and synthesis of single-phase multi-element oxide nanoparticles with tunable composition, size and structure. We have identified temperature-, oxidation- and entropy-driven synthesis strategies to mix a range of elements with largely dissimilar oxidation potentials (including palladium), thus greatly expanding the compositional space. Through rapid synthesis and screening, we obtained a denary multi-element oxide catalyst showing high performance and superior stability for catalytic methane combustion over 100 hours due to the high-entropy design and stabilization. Finally, our work therefore provides a viable synthesis route with clear guidelines for multi-element oxide nanoparticles and enables materials design in the multi-element space towards highly stable catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Unlocking superplasticity in medium and high-entropy alloys

Superplasticity, the capacity of materials to sustain extraordinary tensile elongations at elevated temperatures, underpins a range of advanced metal-forming technologies. Conventionally, it is achieved in fine-grained alloys where deformation is dominated by grain-boundary sliding, accommodated by diffusion and dislocation activity. The advent of medium- and high-entropy alloys (M/HEAs), with their high chemical complexity and unconventional phase stability, offers new pathways to superplastic behavior beyond traditional alloy systems. Although investigated only recently, several M/HEAs already exhibit elongations that rival or exceed those of classical superplastic materials, particularly when ultrafine or metastable microstructures are engineered. Here, we review progress in understanding superplastic deformation in M/HEAs, emphasizing the interplay among composition, initial microstructure, thermomechanical processing, and microstructural evolution during high-temperature deformation. We discuss approaches to generating the fine-grained structures necessary for grain-boundary sliding, including severe plastic deformation and tailored heat treatments. We further highlight dynamic phenomena such as phase transformations, evolving grain-boundary chemistry, and deformation-induced grain refinement that can enhance plasticity in these systems. These mechanisms often shift the balance of deformation processes, enabling large elongations even outside classical criteria. Finally, we outline key challenges for application, including cost, scalability, recyclability, and microstructural stability.

klenam, Desmond [University of the Witwatersrand, ↗

Synthesis of monodisperse high entropy alloy nanocatalysts from core@shell nanoparticles

We report that high-entropy alloy (HEA) nanoparticles (NPs) hold great promise in electrocatalysis because of their nearly unlimited compositions, tailorable active sites, and high durability. However, the synthesis of these compositionally complex structures as monodisperse NPs remains a challenge by colloidal routes because the different rates of metal precursor reduction lead to phase separation. Here, we report the conversion of core@shell NPs into HEA NPs through annealing, with conservation of sample monodispersity. This potentially general route for high-quality HEA NPs was demonstrated by preparing PdCu@PtNiCo NPs via seed-mediated co-reduction, wherein Pt, Ni, and Co were co-deposited on PdCu seeds in solution. These multimetallic NPs were then converted to single-crystalline and single-phase PdCuPtNiCo NPs through annealing. On account of their small particle size, highly dispersed Pt/Pd content, and low elemental diffusivity, these HEA NPs were found to be a highly efficient and durable catalyst for the oxygen reduction reaction. They were also highly selective for the four-electron transfer pathway. We expect that this new synthetic strategy will facilitate the synthesis of new HEA NPs for catalysis and other applications.

36 MATERIALS SCIENCE↗

Local chemical fluctuation mediated ultra-sluggish martensitic transformation in high-entropy intermetallics

Superelasticity associated with martensitic transformation has found a broad range of engineering applications, such as in low-temperature devices in the aerospace industry. Nevertheless, the narrow working temperature range and strong temperature sensitivity of the first-order phase transformation significantly hinder the usage of smart metallic components in many critical areas. Here, we scrutinized the phase transformation behavior and mechanical properties of multicomponent B2-structured intermetallic compounds. Strikingly, the (TiZrHfCuNi) 83.3 Co 16.7 high-entropy intermetallics (HEIs) show superelasticity with high critical stress over 500 MPa, high fracture strength of over 2700 MPa, and small temperature sensitivity in a wide range of temperatures over 220 K. The complex sublattice occupation in these HEIs facilitates formation of nano-scaled local chemical fluctuation and then elastic confinement, which leads to an ultra-sluggish martensitic transformation. The thermal activation of the martensitic transformation was fully suppressed while the stress activation is severely retarded with an enhanced threshold stress over a wide temperature range. Moreover, the high configurational entropy also results in a small entropy change during phase transformation, consequently giving rise to the low temperature sensitivity of the superelasticity stress. Furthermore, our findings may provide a new paradigm for the development of advanced superelastic alloys, and shed new insights into understanding of martensitic transformation in general.

36 MATERIALS SCIENCE↗

Advanced thermal/environmental barrier coatings of high-entropy rare earth disilicates tuned by strong anharmonicity of Eu 2 Si 2 O 7

Advancing thermal/environmental barrier coating (TEBC) materials with integrated thermal-mechanical functions is paramount for safeguarding SiC-based ceramic matrix composites (CMCs) in high-efficiency gas turbines. Herein, we employ a synergistic approach, combining density functional theory (DFT) methods and combinatorial chemistry techniques, to design high-performance and low-cost RE 2 Si 2 O 7 (RE = rare earth elements) TEBC materials tailored for enhanced compatibility with SiC-based CMCs. Expanding on phase stability of alloying pure RE 2 Si 2 O 7 , the investigation extends to the mechanical and thermal properties of solid solution systems, including Er 1/2 Y 3/4 Yb 3/4 Si 2 O 7 , Gd 1/4 Er 1/4 Y 3/4 Yb 3/4 Si 2 O 7 , and Eu 1/4 Er 1/4 Y 3/4 Yb 3/4 Si 2 O 7 . The solid solution systems exhibit a major reduction in lattice thermal conductivity relative to their pure counterparts, achieving ultralow values of 0.25 to 0.39 W m −1 K −1 at 1500 K. Furthermore, the coefficients of thermal expansion (CTE) of these solid solutions are precisely tuned within the desired range for SiC (4.4 to 5.5 × 10 −6 K −1 ), while maintaining good mechanical properties. Here, in particular, the addition of Eu 2 Si 2 O 7 demonstrates to be an important variable to the tuning of CTE and lattice thermal conductivity by leveraging its strong anharmonicity, presenting a pioneering avenue for fine-tuning material properties. In summary, this research not only identifies promising TEBC materials with superior thermal properties, but also introduces a valuable computational material design methodology for the rapid discovery of complex materials for harsh environments.

36 MATERIALS SCIENCE↗

Local cation ordering in compositionally complex Ruddlesden–Popper n = 1 oxides

The Ruddlesden–Popper (RP) layered perovskite structure is of great interest due to its inherent tunability, and the emergence and growth of the compositionally complex oxide (CCO) concept endows the RP family with further possibilities. Here, a comprehensive assessment of thermodynamic stabilization, local order/disorder, and lattice distortion was performed in the first two reported examples of lanthanum-deficient La n+1 B n O 3n+1 (n = 1, B = Mg, Co, Ni, Cu, Zn) obtained via various processing conditions. Chemical short-range order (CSRO) at the B-site and the controllable excess interstitial oxygen (δ) in RP-CCOs are uncovered by neutron pair distribution function analysis. Reverse Monte Carlo analysis of the data, Metropolis Monte Carlo simulations, and extended x-ray absorption fine structure analysis implies a modest degree of magnetic element segregation on the local scale. Further, ab initio molecular dynamics simulations results obtained from special quasirandom structure disagree with experimentally observed CSRO but confirm Jahn–Teller distortion of CuO 6 octahedra. These findings highlight potential opportunities to control local order/disorder and excess interstitial oxygen in layered RP-CCOs and demonstrate a high degree of freedom for tailoring application-specific properties. They also suggest a need for expansion of theoretical and data modeling approaches in order to meet the innate challenges of CCO and related high-entropy phases.

36 MATERIALS SCIENCE↗