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At least 73 records · Page 4

A map of single-phase high-entropy alloys

High-entropy alloys have exhibited unusual materials properties. The stability of equimolar single-phase solid solution of five or more elements is supposedly rare and identifying the existence of such alloys has been challenging because of the vast chemical space of possible combinations. Herein, based on high-throughput density-functional theory calculations, we construct a chemical map of single-phase equimolar high-entropy alloys by investigating over 658,000 equimolar quinary alloys through a binary regular solid-solution model. We identify 30,201 potential single-phase equimolar alloys (5% of the possible combinations) forming mainly in body-centered cubic structures. We unveil the chemistries that are likely to form high-entropy alloys, and identify the complex interplay among mixing enthalpy, intermetallics formation, and melting point that drives the formation of these solid solutions. We demonstrate the power of our method by predicting the existence of two new high-entropy alloys, i.e. the body-centered cubic AlCoMnNiV and the face-centered cubic CoFeMnNiZn, which are successfully synthesized.

36 MATERIALS SCIENCE↗

Mapping of Texture and Phase Fractions in Heterogeneous Stress States during Multiaxial Loading of Biomedical Superelastic NiTi

Thermoelastic deformation mechanisms in polycrystalline biomedical-grade superelastic NiTi are spatially mapped using in situ neutron diffraction during multiaxial loading and heating. The trigonal R-phase is formed from the cubic phase during cooling to room temperature and subsequently deforms in compression, tension, and torsion. The resulting R-phase variant microstructure from the variant reorientation and detwinning processes are equivalent for the corresponding strain in tension and compression, and the variant microstructure is reversible by isothermal loading. The R-phase variant microstructure is consistent between uniaxial and torsional loading when the principal stress directions of the stress state are considered (for the crystallographic directions observed here). The variant microstructure evolution is tracked and the similarity in general behavior between uniaxial and torsional loading, in spite of the implicit heterogeneous stress state associated with torsional loading, pointed to the ability of the reversible thermoelastic transformation in NiTi to accommodate stress and strain mismatch with deformation. This ability of the R-phase, despite its limited variants, to accommodate stress and strain and satisfy strain incompatibility in addition to the existing internal stresses has significance for reducing irrecoverable deformation mechanisms during loading and cycling through the phase transformation.

36 MATERIALS SCIENCE↗

Relation between sampling, sensitivity and precision in strain mapping using the Geometric Phase Analysis method in Scanning Transmission Electron Microscopy

The sensitivity and the precision of the Geometric Phase Analysis (GPA) method for strain characterization is a topic widely discussed in the literature and is usually difficult to quantify. Indeed, the GPA precision is intricately linked to the resolution of the strain maps defined when masking the periodic reflections in Fourier space. In this study an additional parameter, sampling, is proposed to be analyzed regarding the precision of GPA by developing the concept of a phase noise in the GPA equations. Both experimentally and theoretically, the following article demonstrates how the precision, and the sensitivity of the GPA method is improved when using a larger pixel spacing to record an electron micrograph in Scanning Transmission Electron Microscopy (STEM). In conclusion, the counterintuitive concept of increasing the field of view to improve the GPA precision results in an extension of the application of strain characterization methods in STEM towards low deformation levels.

47 OTHER INSTRUMENTATION↗

Precise magnetic field mapping of the EMPHATIC Phase 1 magnet with COMSOL

A compact Halbach array magnet is used to measure the momentum of the secondary particles in EMPHATIC(Experiment to Measure the Production ofHadrons At a Test beam InChicagoland). Hall probe data was taken for the central cylindrical bore of the magnet and a field map was constructed. COMSOL Multiphysics® Software is used for modeling the magnet and constructing the corresponding magnetic field map. Here, we present a fitting approach where the hall probe data is used to determine a 1mm-spacing map of the entire volume of the magnet using COMSOL. The new map will allow for linear interpolation within the volume, and expand the map to outside the measurement volume, thus increasing the acceptance and precision of EMPHATIC's tracking system.

47 OTHER INSTRUMENTATION↗

Heterogeneous microstructure of yttrium hydride and its relation to mechanical properties

Here, the goal of this study is to investigate the properties of yttrium hydride materials in relation to the microstructure, especially its homogeneity. High-throughput nanoindentation mapping was used to evaluate hardness distribution. Raman spectral imaging demonstrated its sensitivity to the presence of YH2 and impurities. Raman peak position maps were correlated with residual stress in the specimens. Electron backscatter diffraction mapping provided phase distributions with correlation to high-energy X-ray diffraction analysis. The experimental mapping data were combined and analyzed using unsupervised machine learning cluster procedures. The machine learning analysis revealed that yttrium hydride specimens contained a major δ-YH2 – x phase component and minor α-Y and δ-YH2 – x components with significant residual stress. The minor phase fraction decreased with increasing nominal H/Y ratio, which affected the nanoindentation and Vickers hardness. The multimodal mapping procedures described herein affect developing important microstructure–property relationships, as well as correlations in heterogeneity and mechanical properties.

36 MATERIALS SCIENCE↗

Titanium doped kagome superconductor CsV 3–x Ti x Sb 5 and two distinct phases

The vanadium-based kagome superconductor CsV 3 Sb 5 has attracted tremendous attention due to its unexcepted anomalous Hall effect (AHE), charge density waves (CDWs), nematicity, and a pseudogap pair density wave (PDW) coexisting with unconventional strong-coupling superconductivity. The origins of CDWs, unconventional superconductivity, and their correlation with different electronic states in this kagome system are of great significance, but so far, are still under debate. Chemical doping in the kagome layer provides one of the most direct ways to reveal the intrinsic physics, but remains unexplored. Here, we report, for the first time, the synthesis of Ti-substituted CsV 3 Sb 5 single crystals and its rich phase diagram mapping the evolution of intertwining electronic states. The Ti atoms directly substitute for V in the kagome layers. CsV 3–x Ti x Sb 5 shows two distinct superconductivity phases upon substitution. The Ti slightly-substituted phase displays an unconventional V-shaped superconductivity gap, coexisting with weakening CDW, PDW, AHE, and nematicity. The Ti highly-substituted phase has a U-shaped superconductivity gap concomitant with a short-range rotation symmetry breaking CDW, while long-range CDW, twofold symmetry of in-plane resistivity, AHE, and PDW are absent. Furthermore, we also demonstrate the chemical substitution of V atoms with other elements such as Cr and Nb, showing a different modulation on the superconductivity phases and CDWs. These findings open up a way to synthesise a new family of doped CsV 3 Sb 5 materials, and further represent a new platform for tuning the different correlated electronic states and superconducting pairing in kagome superconductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Nonlocal subpicosecond delay metrology using spectral quantum interference

Precise knowledge of position and timing information is critical to support elementary protocols such as entanglement swapping on quantum networks. While approaches have been devised to use quantum light for such metrology, they largely rely on time-of-flight (ToF) measurements with single-photon detectors and, therefore, are limited to picosecond-scale resolution owing to detector jitter. In this work, we demonstrate an approach to distributed sensing that leverages phase modulation to map changes in the spectral phase to coincidence probability, thereby overcoming the limits imposed by single-photon detection. By extracting information about the joint biphoton phase, we measure a generalized delay—the difference in signal–idler arrival, relative to local radio frequency (RF) phase modulation. For nonlocal ranging measurements, we achieve (2$σ$) precision of ±0.04 ps and for measurements of the relative RF phase, (2$σ$) precision of ±0.7°. We complement this fine timing information with ToF data from single-photon time-tagging to demonstrate absolute measurement of time delay. By relying on off-the-shelf telecommunications equipment and standard quantum resources, this approach has the potential to reduce overhead in practical quantum networks.

42 ENGINEERING↗

Phase Boundaries, Isotope Effect and Superconductivity of Lithium Under Hydrostatic Conditions

We present theoretical and experimental studies of superconductivity and low temperature structural phase boundaries in lithium. We mapped the structural phase diagram of 6Li and 7Li under hydrostatic conditions between 5 – 55 GPa and within the temperature range of 15 – 75 K, observing the FCC → hR1 → cI16 phase transitions. 6Li and 7Li show some differences at the structural boundaries, with a potential shift of the phase boundaries of 6Li to lower pressures. Density functional theory calculations and topological analysis of the electron density elucidates the superconducting properties and interatomic interactions within these phases of lithium.

Deemyad, Shanti↗

Goal-oriented real-time Bayesian inference for linear autonomous dynamical systems with application to digital twins for tsunami early warning

We present a goal-oriented framework for constructing digital twins with the following properties: (1) they employ discretizations of high-fidelity partial differential equation (PDE) models governed by autonomous dynamical systems, leading to large-scale forward problems; (2) they solve a linear inverse problem to assimilate observational data to infer uncertain model components followed by a forward prediction of the evolving dynamics; and (3) the entire end-to-end, data-to-inference-to-prediction computation is carried out without approximation and in real time through a Bayesian framework that rigorously accounts for uncertainties. Several challenges must be overcome to realize this framework, including the large scale of the forward problem, the high dimensionality of the parameter space, and for a class of problems including those we target, the slow decay of the singular values of the parameter-to-observable map. Here we introduce a methodology to overcome these challenges by exploiting the autonomous structure of the forward model to decompose the solution of the inverse problem into a one-time-only offline phase in which the PDE model is solved a limited number of times (equal to the number of sensors), and an online phase that maps well onto GPUs and computes the parameter inference and prediction of quantities of interest in real time, given observational data. Our ultimate goal is to apply this framework to construct digital twins for subduction zones, including Cascadia, to provide early warning for tsunamis generated by megathrust earthquakes. To this end, we demonstrate how our methodology can be used to employ seafloor pressure observations, along with the coupled acoustic–gravity wave equations, to infer the earthquake-induced spatiotemporal seafloor motion (discretized with $\mathscr{O}$ (10 9 ) parameters) and forward predict the tsunami propagation. We present results of an end-to-end inference, prediction, and uncertainty quantification for a representative test problem with $\mathscr{O}$ (10 8 ) inversion parameters for which goal-oriented Bayesian inference is accomplished exactly and in real time, that is, in a matter of seconds.

97 MATHEMATICS AND COMPUTING↗

Computational Design of Interlayers for Thermally Stable Compositionally Graded Coatings on Nickel Alloys

To extend the service life of Ni-based superalloys, refractory metal coatings are often used. However, direct bonding between metals with dissimilar crystal structure promotes brittle intermetallic phase formation. This work presents a computational thermodynamic framework for high throughput design of functionally graded interlayers to suppress deleterious phases that may form at the interlayer. The Thermo-Calc software package was used to screen candidate metallic interlayer elements based on stability of solid-solution phases. Vanadium was identified as a promising interlayer due to its consistent suppression of intermetallic phases. Temperature-dependent phase diagram mapping between 600 and 1000 °C guided selection of a compositional pathway that significantly reduced intermetallic formation compared to directly joining the Ni-based and Nb refractory alloys. Time–temperature–transformation analysis was performed to assess whether equilibrium-predicted phases are kinetically accessible along regions of the graded path where non-solid-solution phases are not fully suppressed. The methodology was further applied to additional Ni-based alloy and coating systems, illustrating its transferability as an approach for rapid computational design of graded interlayers in dissimilar high-temperature materials.

36 MATERIALS SCIENCE↗

Holographic View of Mixed-State Symmetry-Protected Topological Phases in Open Quantum Systems

We establish a holographic duality between d -dimensional mixed-state symmetry-protected topological (mSPT) phases and ( d + 1 ) -dimensional subsystem symmetry-protected topological (SSPT) states. Specifically, we show that the reduced density matrix of the boundary layer of a ( d + 1 ) -dimensional SSPT state with subsystem symmetry S and global symmetry G corresponds to a d -dimensional mSPT phase with strong S and weak G symmetries. Conversely, we demonstrate that the wave function of an SSPT state can be constructed by replicating the density matrix of the corresponding lower-dimensional mSPT phase. This mapping links the density matrix in lower dimensions to the entanglement properties of higher-dimensional wave functions, providing an approach for analyzing nonlinear quantities and quantum information metrics in mixed-state systems. Our duality offers a new perspective for studying intrinsic mSPT phases that are unique to open quantum systems, without pure-state analogues. We show that strange correlators and twisted Rényi- N correlators can diagnose these nontrivial phases and we explore their connection to strange correlators in pure-state SSPT phases. Furthermore, we discuss several implications of this holographic duality, including a method for preparing intrinsic mSPT phases through the duality. Published by the American Physical Society 2025

Sun, Shijun (ORCID:0000000168880030)↗

Data–Driven Velocity Model Evaluation Using K–Means Clustering

In this work, we develop a data-driven clustering method to evaluate a velocity model using surface wave velocity dispersion. This is done by first computing theoretical dispersion curves for 1-D velocity profiles of all the grid locations and then splitting the resulting dispersion curves into a certain number of groups via the K-means clustering. The observed dispersion curves are also clustered following the same procedure and the velocity model is assessed by comparing the spatial patterns obtained for the observed and synthetic data sets. The method is applied to evaluate two community velocity models in southern California, CVM-S4.26 and CVM-H15.1, using phase velocity maps derived for 3–16 s Rayleigh waves. We found a good correlation in the spatial distribution of clusters between the result of CVM-S4.26 and that of the observed data, suggesting that the CVM-S4.26 fits the observed dispersion maps better than the CVM-H15.1 in terms of features extracted from the clustering analysis.

58 GEOSCIENCES↗

Rapid Identification of Synthetic Routes to Functional Metastable Phases Using X-ray Probed Laser Anneal Mapping (XPLAM) Time-Temperature Quench Maps

Many material systems have known or predicted functional phases that are metastable at standard temperature and pressure. While substantial advances have been made in the high-throughput and combinatorial synthesis of materials with a range of stoichiometries, investigation of thermal processing remains largely the domain of iterative uniform anneals or static gradients. Here we develop X-ray probed laser anneal mapping (XPLAM), a high throughput technique coupling spatially resolved X-ray diffraction with microsecond to millisecond laser gradient anneals to produce temperature–dwell–transformation (TDT) diagrams of the phase as a function of quench time and temperature. In addition to showing regimes where specific metastable phases form preferentially, TDT diagrams provide insight into the submillisecond kinetics of solid–solid phase transitions. This is a unique tool for mapping reaction pathways for metastable phases. As a first demonstration of XPLAM, we study Bi2O3, which has a rich set of polytypes, including the d-phase with an exceptionally high oxygen ion conductivity. We demonstrate the first annealing-driven synthesis of room temperature d-Bi2O3. We expect XPLAM to prove a powerful technique for rapid identification of synthetic routes to metastable phases and to generate the exhaustive data sets required for machine learning-guided exploration of materials processing.

36 MATERIALS SCIENCE↗

Accelerating Thermochemical Equilibrium Calculations for Nuclear Reactor Applications

Thermochemical properties play a key role in modeling and simulation of several key phenomena in nuclear reactors. There has been an increasing interest in incorporating CALPHAD-based formulations in multiphysics simulations including for Molten Salt Reactors where knowledge of phase evolution of the salt and the chemical potentials of various elements are of utmost importance in source term analyses and redox control. However, the size of such simulations is often limited by the high computational cost of full thermodynamic equilibrium calculations. This work discusses the current efforts aimed at accelerating thermochemical equilibrium calculations for multiphysics simulations performed using the open-source finite element / finite volume code Multiphysics Object Oriented Simulation Environment (MOOSE) [1]. While several methods have been proposed for accelerating phase equilibrium calculations [2], most focus on relatively small systems and often rely on a- priori knowledge of the state-space of the system. Nuclear materials, however, are often multi-component systems owing to the evolution of composition under irradiation and an approach based on a-priori mapping of phase diagram is often not enough. This work is aimed at demonstrating an on-the-fly surrogate modeling framework that uses active learning to reduce the number of full equilibrium calculations that must be performed. By combining with efficient coupling approaches, the surrogate framework helps in reducing the computational cost of thermodynamic equilibrium informed multiphysics simulations of nuclear materials. The performance is benchmarked against full coupling with the thermochemistry library Thermochimica [3]. This work uses a machine learning based approach for constructing surrogate models to predict the stable phases in a multicomponent system. The surrogates were constructed using neural networks and Gaussian process classification. In this work, we compare the relative performance of the two methods. We also demonstrate the use of caching previous calculations by interpolating the values from nearest neighbors. References [1] Lindsay, A.D., et al. "2.0 – MOOSE: Enabling massively parallel multiphysics simulation", SoftwareX, 20 (2022): 101202. [2] Roos, W.A. and Zietsman J.H. "Accelerating complex chemical equilibrium calculations – A Review", Calphad, 77 (2022): 102380. [3] Piro, M.H.A., et al. "The thermochemistry library Thermochimica", Computational Materials Science, 67 (2013): 266-272.

36 MATERIALS SCIENCE↗

Structural Manipulation of Phase Transitions by Self‐Induced Strain in Geometrically Confined Thin Films

Strain engineering is a well-known method often used to tune material properties in thin films. The most studied sources of strain are lattice mismatch and differential thermal contraction between the substrate and film. However, in materials which undergo a structural phase transition (SPT), a third and often overlooked source of strain may play a very significant role. If the substrate confines the area of the film, the SPT may induce stress which changes the evolution of the transition. This is a 2D analog of the isochoric phase transition between water and ice, where the freezing point drops below 0 °C. To illustrate this, the prototypical Mott insulator V 2 O 3 which has an SPT coupled to a metal–insulator transition is used to show how self-induced strain can drastically alter structural and electronic properties. This effect provides an elegant approach for mapping the phase diagram of the SPT and the transitions coupled to it. Moreover, the magnitude of self-straining is tunable by modifying the substrate morphology. Furthermore, this effect may be important for numerous materials which exhibit an SPT and are subjected to geometrical constraints.

Kalcheim, Yoav↗

Thin-Film Stabilization and Magnetism of η -Carbide-Type Iron Nitrides

Transition-metal nitrides in ..eta..-carbide-type structures exhibit unusual bonding motifs and proximity to magnetic instabilities. Yet they remain unexplored in thin-film form due to the difficulty of stabilizing nitrogen-poor ternaries among competing phases. Here, we report the thin-film synthesis and phase-stability mapping of the ..eta..-nitride systems Fe-W-N and Fe-Mo-N. Amorphous Fe-M-N (M = W, Mo) combinatorial libraries deposited by reactive cosputtering crystallize upon rapid thermal annealing, enabling systematic identification of synthesis windows as a function of composition and annealing temperature. Using laboratory powder X-ray diffraction and synchrotron grazing incidence wide-angle X-ray scattering, we establish that Fe 3 Mo 3 N-based ..eta..-carbide phases form over a substantially broader compositional and thermal range than W-based compositions, where ..eta.. structures are stabilized only when the films are Fe-rich. These trends are rationalized using mixed chemical-potential vs composition phase diagrams that capture the narrow nitrogen chemical-potential stability of ..eta..-nitrides. Magnetic measurements reveal that ferromagnetism is induced in Fe-rich Fe 3.54 Mo 2.46 N with a small exchange-bias-like response that is absent in Fe 3 W 3 N-based compositions, highlighting the sensitivity of magnetic behavior to modest deviations from stoichiometry. This work establishes practical thin-film synthesis routes for ..eta..-nitride materials and demonstrates how composition can be tuned to access emergent magnetic phenomena in these complex nitrides.

36 MATERIALS SCIENCE↗

An approach for fast and accurate simulation of phase change material based thermal energy storage in buildings

Latent heat thermal energy storage (LHTES) has significant potential for mitigating peak electricity demand and enabling load shifting in buildings. Phase Change Material embedded heat exchangers (PCM-HX) can significantly improve energy demand management due to high storage capacity. However, PCM-HX evaluation typically depends on computationally expensive fully transient simulations, posing significant challenges for scalable system- and building-level energy assessments across different climates and system architectures. This paper presents a generalized, accurate, and computationally efficient methodology for simulating building energy systems integrated with LHTES. The PCM-HX transient performance is represented by performance maps generated using a Generalized Resistance-Capacitance Model (GRCM) that enables accurate predictions of arbitrary PCM-HXs at low computational cost. The feasibility of the proposed approach was verified using a case study considering a dual-mode heat pump-thermal energy storage (HP-TES) system simulated in Modelica with Spawn of EnergyPlus™ for a DOE prototype small office building in two locations: Tampa, FL, and International Falls, MN. The PCM-HX performance maps provided accurate predictions of PCM-HX transient behavior, with mean absolute percentage deviations within 2–4% compared to GRCM while also achieving at least 1800× reduction in computational time. Moreover, the HP-TES system achieved energy savings of up to 17.4% in Tampa, FL, and 62.2% in International Falls, MN, demonstrating the broader applicability of the proposed methodology across different climate zones. This work highlights the importance of robust PCM-HX models in enabling accurate and computationally efficient building-level simulations and enabling future research opportunities for investigating optimized HP-TES designs and advanced control strategies for grid-interactive buildings.

Modelica↗