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At least 919 records · Page 51

Effects of magnetic and structural phase transitions on the normal and anomalous Hall effects in Ni-Mn-In-B Heusler alloys

In this work, magnetization, electrical resistivity, magnetoresistance, and Hall resistivity of Ni 50 Mn 35 In 14.25 B 0.75 and Ni 50 Mn 35 In 14.5 B 0.5 Heusler alloys were studied in a temperature range $\textit{T}$ = 80–400 K in magnetic fields up to 20 kOe. Both alloys exhibit a martensitic transformation from a high-temperature ferromagnetic austenite phase to a low-temperature, low-magnetization martensitic phase. The electrical resistivity nearly doubles as a result of the martensitic transformation, reaching 180 and 100 µΩ cm in the martensitic states of Ni 50 Mn 35 In 14.25 B 0.75 and Ni 50 Mn 35 In 14.5 B 0.5 , respectively. The temperature dependence of the electrical resistivity does not corresponded with the Mooij correlation. The magnetoresistance is negative with a narrow negative peak at the martensitic transition. Normal and anomalous Hall effect coefficients were determined by fitting the field dependences of the Hall resistivity using magnetization data. The coefficients of the normal Hall effect for both compositions were found to decrease with temperature from positive values in the austenite to negative values in the martensite phase. None of the known correlations between the anomalous Hall effect coefficient and resistivity were satisfied. Significant changes in the values of the anomalous Hall coefficients during the martensitic transformation are explained by the difference in spin-up and spin-down state occupations in the martensite and austenite phases. First-principles calculations of the electronic structures confirm this explanation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Using machine-learning to understand complex microstructural effects on the mechanical behavior of Ti-6Al-4V alloys

Structural materials properties are highly dependent on their microstructure. Their microstructure is in turn affected by multiple fabrication and thermo-mechanical treatment parameters, all of which conform a highly-dimensional parametric space with often hidden correlations that are difficult to extract by experimentation alone. This is particularly true for alloys of the dual-phase Ti-6Al-4V family, with their greatly complex and rich microstructures, which combine several intrinsic length scales associated with multiple grain and subgrain structures, grains with different crystal lattices (α and β phases), and complex chemistry. In this paper we use a comprehensive set of machine learning techniques to develop predictive tools relating the yield strength and hardening rate of these alloys to a set of input parameters covering extensive ranges. The data generator is a finite-element crystal plasticity model for polycrystal deformation that takes into account slip anisotropy and employs standard dislocation evolution models for the α and β phases of Ti-based alloys. Our dataset includes over two thousand independent simulations and is used to train the machine learning models, which are then used to establish correlations between microstructural parameters and the alloys’ mechanical response. Our results point to the most influential parameters affecting yield strength and hardening rate, information that can then be used to guide experimental synthesis and characterization efforts to save time and resources.

36 MATERIALS SCIENCE↗

Hidden orders and phase transitions for the fully packed quantum loop model on the triangular lattice

Abstract Quantum loop and dimer models are prototypical correlated systems with local constraints, which are not only intimately connected to lattice gauge theories and topological orders but are also widely applicable to the broad research areas of quantum materials and quantum simulation. Employing our sweeping cluster quantum Monte Carlo algorithm, we reveal the complete phase diagram of the triangular-lattice fully packed quantum loop model. Apart from the known lattice nematic (LN) solid and the even$${{\mathbb{Z}}}_{2}$$ Z 2 quantum spin liquid (QSL) phases, we discover a hidden vison plaquette (VP) phase, which had been overlooked and misinterpreted as a QSL for more than a decade. Moreover, the VP-to-QSL continuous transition belongs to the (2 + 1)D cubic * universality class, which offers a lattice realization of the (fractionalized) cubic fixed point that had long been considered as irrelevant towards the O(3) symmetry until corrected recently by conformal bootstrap calculations. Our results are therefore of relevance to recent developments in both experiments and theory, and facilitate further investigations of hidden phases and transitions.

Physics↗

Electronic properties of the bulk and surface states of Fe 1+y Te 1-x Se x

The idea of employing non-Abelian statistics for error-free quantum computing ignited interest in reports of topological surface superconductivity and Majorana zero modes (MZMs) in FeTe 0.55 Se 0.45 . However, the topological features and superconducting properties are not observed uniformly across the sample surface. The understanding and practical control of these electronic inhomogeneities present a prominent challenge for potential applications. Here, we combine neutron scattering, scanning angle-resolved photoemission spectroscopy, and microprobe composition and resistivity measurements to characterize the electronic state of Fe 1+y Te 1-x Se x . Furthermore, we establish a phase diagram in which the superconductivity is observed only at sufficiently low Fe concentration, in association with distinct antiferromagnetic correlations, whereas the coexisting topological surface state occurs only at sufficiently high Te concentration. We find that FeTe 0.55 Se 0.45 is located very close to both phase boundaries, which explains the inhomogeneity of superconducting and topological states. Our results demonstrate the compositional control required for use of topological MZMs in practical applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Molecular beam epitaxy synthesis and electrical transport properties of the correlated kagome metal Ni⁢ 3 In

Ni 3 ⁢In is a paramagnetic intermetallic consisting of 𝐴⁢𝐵-stacked Ni-kagome networks. Correlated electron behaviors deviating from the Fermi-liquid form have recently been observed in Ni 3 ⁢In bulk single crystals, attributed to stabilization of a partially flat electronic band near the Fermi level. Synthesis of this system in thin-film form offers unique opportunities for tuning of materials that could aid in identifying the microscopic origin of the non-Fermi-liquid response and exploring the suspected quantum criticality therein. Here, we report the realization of (001)-oriented epitaxial thin films of Ni 3 ⁢In on single-crystal SrTiO 3 (111) substrates by molecular beam epitaxy. Via control of growth conditions, we fabricate high-quality films with quantum fluctuations strongly influencing the physical properties of the system. Analysis of the electrical transport response reveals that intrinsic spin fluctuations in Ni 3 ⁢In may account for the observed non-Fermi-liquid behavior. Such structures may facilitate driving Ni 3 ⁢In across a potential quantum critical phase transition and uncover the role of unusual flat bands in triggering correlated phenomena.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Phase diagrams and polarization reversal in nanosized Hf x Zr 1–x O 2–y

To describe the polar properties of nanosized Hf x Zr 1–x O 2–y , we evolve the “effective” Landau–Ginzburg–Devonshire (LGD) model based on the parametrization of the Landau expansion coefficients for polar and antipolar orderings. We have shown that the effective LGD model can predict the influence of screening conditions and size effects on phase diagrams, polarization reversal, and structural properties of nanosized Hf x Zr 1–x O 2–y of various shapes and sizes. To verify the model, we use the available experimental results for Hf x Zr 1–x O 2 thin films and oxygen-deficient HfO2–y nanoparticles prepared under different annealing conditions. X-ray diffraction, which was used to determine the phase composition of the HfO 2–y nanoparticles, revealed the formation of a ferroelectric orthorhombic phase in them. Micro-Raman spectroscopy was used to explore the correlation of lattice dynamics and structural changes that depend on the oxygen vacancy concentration in the HfO 2–y nanoparticles. Since our approach allows us to determine the conditions (shape, sizes, Zr content, and/or oxygen vacancy amount) for which nanosized Hf x Zr 1–x O 2–y are ferroelectric or antiferroelectric, we hope that the obtained results are useful for creation of next generation Si-compatible ferroelectric gate oxide nanomaterials.

36 MATERIALS SCIENCE↗

Empirical investigation of nuclear correlation function distributions in lattice QCD

Two-point correlation functions of systems with baryon number 𝐵 ∈ {1,2,3,4} are investigated using lattice quantum chromodynamics (QCD). In particular, the empirical distributions of importance-sampling Monte-Carlo samples of these correlation functions are examined as a function of the spacetime separation between the two points and the baryon number. While the exact forms of these distributions are not known for QCD, recent work has determined asymptotic expressions for analogous correlation function distributions in simpler theories such as scalar field theory and the disordered phase of the 𝑂⁡(𝑁) model. The theoretical 𝑂⁡(𝑁) model distributions are found to provide an accurate description of the empirical QCD distributions at zero momentum over a wide range of temporal separations for each baryon number when assessed with a range of different statistical tests. In particular, the behavior of the baryon number 𝐵 QCD correlation function at large temporal separation is well reproduced by the 𝑂⁡(𝑁 ∼ 2/𝐵) model distribution.

Lattice field theory↗

Attractive Effect of a Strong Electronic Repulsion: The Physics of Vertex Divergences

While the breakdown of the perturbation expansion for the many-electron problem has several formal consequences, here we unveil its physical effect: flipping the sign of the effective electronic interaction in specific scattering channels. By decomposing local and uniform susceptibilities of the Hubbard model via their spectral representations, we prove how entering the nonperturbative regime causes an enhancement of the charge response, ultimately responsible for the phase-separation instabilities close to the Mott metal-insulator transition. Furthermore, our analysis opens a new route for understanding phase transitions in the nonperturbative regime and clarifies why attractive effects emerging from a strong repulsion can induce phase separations but not s-wave pairing or charge-density wave instabilities.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Microscopic origin of criticality at macroscale in QCD chiral phase transition

We reveal that the criticality of the chiral phase transition in QCD at the macroscale arises from the microscopic energy levels of its fundamental constituents, the quarks. We establish a novel relation between cumulants of the chiral order parameter (i.e., chiral condensate) and correlations among the energy levels of quarks (i.e., eigenspectra of the massless Dirac operator), which naturally leads to a generalization of the Banks-Casher relation. Based on this novel relation and through (2+1)-flavor lattice QCD calculations using the HISQ action with varying light quark masses in the vicinity of the chiral phase transition, we demonstrate that the correlations among the infrared part of the Dirac eigenspectra exhibit same universal scaling behaviors as expected of the cumulants of the chiral condensate. We find that these universal scaling behaviors extend up to the physical values of the up and down quark masses.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Automated TEM Reveals Intercrystalline Correlations of Conjugated Polymers

Transmission electron microscopy (TEM) continues to transform polymer science by revealing key aspects of chain packing, phase separation and nanoscale structure. The development of instrumentation and data analyses tools is driving the field forward and enabling new experiments. Here, we use automated high-resolution TEM (HRTEM) and image processing to identify the structure of a conjugated polymer used in organic electronics. Analysis of more than 600 HRTEM images reveals lattice parameters and orientation correlations between crystals, including the preferred alignment of neighboring crystals along the same crystallographic direction that is likely the result of liquid crystalline order.

Fair, Ryan A. [Pennsylvania State University, Univ↗

State densities of heavy nuclei in the static-path plus random-phase approximation

We report that nuclear state densities are important inputs to statistical models of compound-nucleus reactions. State densities are often calculated with self-consistent mean-field approximations that do not include important correlations and must be augmented with empirical collective enhancement factors. Here, we benchmark the static-path plus random-phase approximation (SPA + RPA) to the state density in a chain of samarium isotopes 148–155 Sm against exact results (up to statistical errors) obtained with the shell-model Monte Carlo (SMMC) method. The SPA + RPA method incorporates all static fluctuations beyond the mean field together with small-amplitude quantal fluctuations around each static fluctuation. Using a pairing plus quadrupole interaction, we show that the SPA + RPA state densities agree well with the exact SMMC densities for both the even- and odd-mass isotopes. For the even-mass isotopes, we also compare our results with mean-field state densities calculated with the finite-temperature Hartree-Fock-Bogoliubov (HFB) approximation. We find that the SPA + RPA repairs the deficiencies of the mean-field approximation associated with broken rotational symmetry in deformed nuclei and with the violation of particle-number conservation in the pairing condensate. In particular, in deformed nuclei the SPA + RPA reproduces the rotational enhancement of the state density relative to the mean-field state density.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A fast multi-fidelity method with uncertainty quantification for complex data correlations: Application to vortex-induced vibrations of marine risers

Here we develop a fast multi-fidelity modeling method for very complex correlations between high- and low-fidelity data by working in modal space to extract the proper correlation function. We apply this method to infer the amplitude of motion of a flexible marine riser in cross-flow, subject to vortex-induced vibrations (VIV). VIV are driven by an absolute instability in the flow, which imposes a frequency (Strouhal) law that requires a matching with the impedance of the structure; this matching is easily achieved because of the rapid parametric variation of the added mass force. As a result, the wavenumber of the riser spatial response is within narrow bands of uncertainty. Hence, an error in wavenumber prediction can cause significant phase-related errors in the shape of the amplitude of response along the riser, rendering correlation between low- and high-fidelity data very complex. Working in modal space as outlined herein, dense data from low-fidelity data, provided by the semi-empirical computer code VIVA, can correlate in modal space with few high-fidelity data, obtained from experiments or fully-resolved CFD simulations, to correct both phase and amplitude and provide predictions that agree very well overall with the correct shape of the amplitude response. We also quantify the uncertainty in the prediction using Bayesian modeling and exploit this uncertainty to formulate an active learning strategy for the best possible location of the sensors providing the high fidelity measurements.

42 ENGINEERING↗

Isoplethal study of phase formation and morphology in uranium-304L steel via scanning electron microscopy

Understanding the formation of uranium alloys with steel is important to advance nuclear technologies involving U metal fuels and machining U metal, and for nuclear forensics applications. No known phase diagram for the quaternary U-(M = Fe, Ni, Cr) system exists. For this work, we synthesize samples of U-304 L steel (nominal composition 70.1:18.3:10.4 at% Fe:Cr:Ni) across the U composition range 4.45—63.35 at%U by arc melting under inert conditions. Using the binary UFe phase diagram as a reference, we identify four U-steel alloy phases. We find the known U-Fe analogue phases UM 2 and U 6 M, and two low-U composition phases with nominal compositions UM 10 and U 2 M 7 . We apply a correlation length analysis to backscatter scanning electron microscopy images of sectioned and polished cross sections to quantify the domain formation length scale. We demonstrate that these depend heavily on the initial composition and range from 30 nm to 1.5 µm. This result, in particular, could be applicable to theoretical predictions of transport properties. Furthering our understanding of U alloy phase formation with important structural elements such as steel primaries is foundational in developing future nuclear technology.

36 MATERIALS SCIENCE↗

Core electron temperature turbulence and transport during sawtooth oscillations in the DIII-D tokamak

Abstract Sawteeth are one of the concerning instabilities in ITER and future burning plasma experiments. Sawtooth dynamics and its interaction with broadband plasma turbulence has been a challenge for predictive simulations of core transport in future fusion devices. This study provides new observations of core turbulence behavior during sawtooth oscillations in DIII-D hydrogen L-mode neutral beam injection heated plasmas in an inner wall limited configuration. A strong correlation of electron temperature and density turbulence levels with the sawtooth oscillation phase has been observed at locations inside the T e inversion radius and/or safety factor q = 1 magnetic surface. The T e turbulence amplitude in the core during the sawtooth ramp exhibits a critical T e gradient behavior inside but not near the T e inversion radius/ q = 1 magnetic surface. The most unstable mode calculated from the trapped gyro-landau fluid turbulence simulations reveal a change from low- k ion-type to low-k electron-type modes from pre- to post- sawtooth crash time periods.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Anomalous Hall effect in the polar magnet Gd 3 ⁢Ni 8 ⁢Sn 4 : A candidate for hosting skyrmions

While recent theoretical studies have positioned noncollinear polar magnets with C nv symmetry as compelling candidates for realizing topological magnetic phases and substantial intrinsic anomalous Hall conductivity, experimental realizations of the same in strongly correlated systems remain rare. Here, we present a large intrinsic anomalous Hall effect and extended topological magnetic ordering in Gd 3 ⁢Ni 8 ⁢Sn 4 with hexagonal C 6v symmetry. Observation of topological Hall response, corroborated by metamagnetic anomalies in isothermal magnetization, peak/hump features in field-evolution of ac susceptibility and longitudinal resistivity suggest the signature of topological magnetic phases. The anomalous Hall effect is quantitatively accounted for by the intrinsic Berry curvature-mediated mechanism. Finally, our results underscore polar magnets as a promising platform to investigate a plethora of emergent electrodynamic responses rooted in the interplay between magnetism and topology.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

In Situ Probing Potassium-ion Intercalation-induced Amorphization in Crystalline Iron Phosphate Cathode Materials

Na-ion and K-ion batteries are promising alternatives for large-scale energy storage applications due to their abundance and low cost. Intercalation of these large ions could cause irreversible structural deformation and partial to complete amorphization in the crystalline electrodes. The designing of new amorphous electrodes is another route to develop electrodes to store these ions reversibly. Lack of understanding of dynamic changes in the amorphous nanostructures during battery operation is the bottleneck for further developments. Here, we report the utilization of in situ digital image correlation and in-operando X-ray diffraction (XRD) techniques to probe dynamic changes in the amorphous phase of iron phosphate during potassium intercalation. In-operando XRD demonstrates amorphization in the electrode’s nanostructure during the first charge/discharge cycle. Additionally, the ex-situ high-resolution transmission electron microscopy further confirms the amorphization after potassium insertion. In situ strain analysis detects the reversible deformation associated with redox reactions in the amorphous phases. Our approach offers new insights on the mechanisms of ion intercalation in the amorphous nanostructures which are highly potent for development of next-generation batteries.

Ozdogru, Bertan↗

Towards inverse microstructure-centered materials design using generative phase-field modeling and deep variational autoencoders

The field of Integrated Computational Materials Engineering (ICME) combines a broad range of methods to study materials’ responses over a spectrum of length scales. A relatively unexplored aspect of microstructure-sensitive materials design is uncertainty propagation and quantification (UP/UQ) of materials’ microstructure, as well as establishing process-structure–property (PSP) relationships for inverse material design. In this study, an efficient UP technique built on the idea of changing probability measures and a deep generative unsupervised representative machine learning method for microstructure-based design of thermal conductivity of materials is proposed. Probability measures are used to represent microstructure space, and Wasserstein metrics are used to test the efficiency of the UP method. By using deep Variational AutoEncoder (VAE), we identify the correlations between the material/process parameters and the thermal conductivity of heterogeneous dual-phase microstructures. Through high-throughput screening, UP, and the deep-generative VAE method, PSP relationships that are too complex can be revealed by exploiting the materials’ design space with an emphasis on microstructures. As a last point, we demonstrate generative machine learning serves as a useful tool for inverse microstructure-centered materials design, and we demonstrate this by examining the inverse design of thermal conductivity in nano-structured materials. Here, the results reveal the effects of morphology, volume fraction, characteristic length scale, and the individual thermal diffusivity of phases on the thermal conductivity of dual-phase alloys. Our findings emphasize the advantages of high-throughput phase-field modeling and generative deep learning for linking PSP and inverse microstructure-centered materials design.

36 MATERIALS SCIENCE↗

Order-Disorder Transitions in ( Ca x Sr 1 - x ) 3 Rh 4 Sn 13

The classification of structural phase transitions as displacive or order-disorder in character is usually based on spectroscopic data above the transition. Here, we use single crystal x-ray diffraction to investigate structural correlations in the quasiskutterudites, (Ca x Sr 1-x ) 3 Rh 4 Sn 13 , which have a quantum phase transition at x ~ 0.9. Three-dimensional pair distribution functions show that the amplitudes of local atomic displacements are temperature independent below the transition and persist to well above the transition, a signature of order-disorder behavior. The implications for the associated electronic transitions are discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗