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At least 973 records · Page 54

Quantum Magnetic Properties in Perovskite with Anderson Localized Artificial Spin‐1/2

Abstract Quantum magnetic properties in a geometrically frustrated lattice of spin‐1/2 magnet, such as quantum spin liquid or solid and the associated spin fractionalization, are considered key in developing a new phase of matter. The feasibility of observing the quantum magnetic properties, usually found in geometrically frustrated lattice of spin‐1/2 magnet, in a perovskite material with controlled disorder is demonstrated. It is found that the controlled chemical disorder, due to the chemical substitution of Ru ions by Co‐ions, in a simple perovskite CaRuO 3 creates a random prototype configuration of artificial spin‐1/2 that forms dimer pairs between the nearest and further away ions. The localization of the Co impurity in the Ru matrix is analyzed using the Anderson localization formulation. The dimers of artificial spin‐1/2, due to the localization of Co impurities, exhibit singlet‐to‐triplet excitation at low temperature without any ordered spin correlation. The localized gapped excitation evolves into a gapless quasi‐continuum as dimer pairs break and create freely fluctuating fractionalized spins at high temperature. Together, these properties hint at a new quantum magnetic state with strong resemblance to the resonance valence bond system.

74 ATOMIC AND MOLECULAR PHYSICS↗

A greedy algorithm for computing eigenvalues of a symmetric matrix with localized eigenvectors

Here, we present a greedy algorithm for computing selected eigenpairs of a large sparse matrix $H$ that can exploit localization features of the eigenvector. When the eigenvector to be computed is localized, meaning only a small number of its components have large magnitudes, the proposed algorithm identifies the location of these components in a greedy manner, and obtains approximations to the desired eigenpairs of $H$ by computing eigenpairs of a submatrix extracted from the corresponding rows and columns of $H$. Even when the eigenvector is not completely localized, the approximate eigenvectors obtained by the greedy algorithm can be used as good starting guesses to accelerate the convergence of an iterative eigensolver applied to $H$. We discuss a few possibilities for selecting important rows and columns of $H$ and techniques for constructing good initial guesses for an iterative eigensolver using the approximate eigenvectors returned from the greedy algorithm. We demonstrate the effectiveness of this approach with examples from nuclear quantum many-body calculations and many-body localization studies of quantum spin chains.

97 MATHEMATICS AND COMPUTING↗

Finite element formulation with embedded weak discontinuities for strain localization under dynamic conditions

Here, we present an explicit finite element formulation designed for the treatment of strain localization under highly dynamic conditions. We also used a material stability analysis to detect the onset of localization behavior. Finite elements with embedded weak discontinuities are employed with the aim of representing subsequent localized deformation accurately. The formulation and its algorithmic implementation are described in detail. Numerical results are presented to illustrate the usefulness of this computational framework in the treatment of strain localization under highly dynamic conditions, and to examine its performance characteristics in the context of two-dimensional plane-strain problems.

36 MATERIALS SCIENCE↗

Heterogeneous solute segregation suppresses strain localization in nanocrystalline Ag-Ni alloys

Solute segregation to individual grain boundaries is used by design to produce strong and stable nanocrystalline metallic alloys. Grain-boundary segregation, however, is known to cause adverse embrittlement effects from a strain-localization failure mechanism that imposes significant material limitations for structural applications. Here, using atomistic simulations, it is discovered that heterogeneous Ni segregation in nanocrystalline Ni-mixed Ag alloys dramatically shuts down localized shear bands during plastic deformation, while simultaneously increasing the tensile strength. Nanocrystalline Cu-mixed Ag metals are predicted to exhibit standard homogeneous Cu segregation and a tensile strength that saturates above a solute concentration of 8 at.% due to glass-like shear localization induced by grain boundaries. By contrast, it is found that heterogeneous Ni segregation in nanocrystalline Ag-Ni alloys forms solute-rich clusters along interfaces leading to strain delocalization at high strain and continuous strengthening at high solute concentrations up to 15 at.%. As a result, this study reveals the importance of heterogeneous versus homogeneous segregation behaviors on strain localization and points to a fundamentally new strategy to design failure-resistant nanostructured materials through grain boundary segregation engineering.

36 MATERIALS SCIENCE↗

Mechanical properties and strain localization of WA-DED printed P91 steel

This paper discusses a P91 steel block that was additively manufactured by wire arc direct energy deposition (WA-DED) followed by two types of post-process heat treatment (PPHT). Vickers microhardness and digital image correlation tensile tests were performed along the building direction. The global mechanical properties (i.e., microhardness and tensile properties) and the local mechanical responses (i.e., hardness fluctuation and strain localization) were systematically investigated. Results showed that (1) all P91 specimens showed higher strengths than American Society of Mechanical Engineers standard requirements for wrought P91 steel, (2) the as-printed P91 exhibited much higher average hardness and fluctuations than that after PPHT, (3) PPHT reduced P91 strengths but improved the ductility significantly, and (4) strain localization presented in the as-printed specimen during uniform deformation in tensile tests. The hardness fluctuation and strain localization along the building direction of the AP P91 were caused by different thermal histories received during WA-DED. The study indicated that PPHT, ideally tempering-only heat treatment, is necessary for the WA-DED printed P91 steel.

Mechanical properties↗

A coupled equilibrium boundary layer model with stable water isotopes and its application to local water recycling

The contribution of evapotranspiration (ET) to regional precipitation, known as “local water recycling”, is a key process in the water cycle that can affect water management. However, the amount of planetary boundary layer (PBL) moisture that arises from ET is highly uncertain due to complex atmosphere and land surface conditions. In this study, an idealized two-layer equilibrium boundary layer model was coupled with a stable water isotope module including HDO and H 2 18 O to constrain PBL growing season water transport processes. The model was validated using turbulent heat fluxes and isotope ratios of water vapor (δ m ) and precipitation (δ P ) measured at a cropland site and a nearby tall tower in the Upper Midwest, United States. The results show that the PBL equilibrium features of δ m and δ P are well-constrained by thermal and moisture equilibrium in the PBL. For this study region, the summer values of rain evaporation fraction (f) and local water recycling ratio (LRR) are estimated to be 0.09 and 0.29 ± 0.12, respectively. The summer LRR values for the years 2006–2010 were 0.35, 0.36, 0.17, 0.29, and 0.29, respectively. The small value of LRR in 2008 corresponded to a drought condition with the lowest precipitation and second lowest ET among the five years. The summer magnitude of the amount effect is –2.8‰ (mm day –1 ) –1 and –0.8‰ (mm day –1 ) –1 for HDO and H 2 18 O, respectively. The local water recycling is identified as a significant factor influencing the continental isotope effect. Cropland has likely changed the regional LRR by –7.6 to 19.5% under different pre-agriculture land use scenarios. In conclusion, the feedback processes revealed here indicate that local water recycling is expected to be weakened under drought conditions, but it will be enhanced if irrigation is applied more intensely with more frequent drought events as the climate continues to warm.

54 ENVIRONMENTAL SCIENCES↗

A centralized-based method to determine the local voltage control strategies of distributed generator operation in active distribution networks

The increasing penetration of distributed generators (DGs) exacerbates the risk of voltage violations in active distribution networks (ADNs). The var capacity provided by DG inverters is a potential solution for voltage regulation. The conventional centralized control strategies limited by computation and communication burdens are difficult to meet the requirement of rapid voltage control. However, the local control strategies based on real-time measurements have a fast response to the frequent fluctuations of DG outputs. The performance of these local controllers depends on the tuning of the control parameters. This paper proposes a centralized-based method to determine the local voltage control strategies for DGs. A centralized parameter tuning model of control curves is built, in which and curves of DG inverters are mathematically formulated based on piecewise linearization. The original mixed-integer nonlinear programming (MINLP) model is converted into an effectively solved mixed-integer second-order cone programming (MISOCP) model using convex relaxation. The potential benefits of DG inverters are explored to regulate both reactive and curtailed active power, based on local voltage measurements. Case studies on a modified PG&E 69-node distribution system are carried out to verify the effectiveness of the proposed method. Results show that power losses of ADNs are significantly reduced and voltage profiles are also improved.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Exploring the impact of hydro-mechanical coupling on compaction localization

In deep subsurface environments, where porous rocks are saturated with fluids, hydromechanical coupling plays a critical role in the formation and propagation of localized deformation zones, such as compaction bands. In this study, we numerically investigate the influence of fluid-rock interactions on the development of compaction localization in fluid-saturated rocks. For this purpose, it uses a numerical framework that adapts the heat equation to model the diffusion of pore pressure caused by deformation. This is achieved with specialized subroutines for material behavior and heat transfer formulated within the ABAQUS platform and by allowing changes in rock permeability during strain localization. The results highlight that hydromechanical coupling significantly alters the compaction behavior compared to dry conditions. Under high confining stress, excess pore pressure inhibits the progression of compaction fronts, while in time-dependent processes like rock creep, pore pressure transients accelerate deformation by creating feedback loops between mechanical forces and fluid flow. These findings underscore the importance of saturation in controlling the dynamics of compaction localization and provide insights into the interplay between pore pressure, deformation, and permeability. The implications of this study extend to applications in geological storage, resource extraction, and subsurface geomechanics, offering a deeper understanding of coupled hydromechanical processes in porous rocks.

58 GEOSCIENCES↗

Locality-aware and load-balanced static task scheduling for MapReduce

Task scheduling for MapReduce jobs has been an active area of research with the objective of decreasing the amount of data transferred during the shuffle phase via exploiting data locality. In the literature, generally only the scheduling of reduce tasks is considered with the assumption that scheduling of map tasks is already determined by the input data placement. However, in cloud or HPC deployments of MapReduce, the input data is located in a remote storage and scheduling map tasks gains importance. Here, we propose models for simultaneous scheduling of map and reduce tasks in order to improve data locality and balance the processors’ loads in both map and reduce phases. Our approach is based on graph and hypergraph models which correctly encode the interactions between map and reduce tasks. Partitions produced by these models are decoded to schedule map and reduce tasks. A two-constraint formulation utilized in these models enables balancing processors’ loads in both map and reduce phases. The partitioning objective in the hypergraph models correctly encapsulates the minimization of data transfer when a local combine step is performed prior to shuffle, whereas the partitioning objective in the graph models achieve the same feat when a local combine is not performed. Here, we show the validity of our scheduling on the MapReduce parallelizations of two important kernel operations – sparse matrix–vector multiplication (SpMV) and generalized sparse matrix–matrix multiplication (SpGEMM) – that are widely encountered in big data analytics and scientific computations. Compared to random scheduling, our models lead to tremendous savings in data transfer by reducing data traffic from several hundreds of megabytes to just a few megabytes in the shuffle phase and consequently leading up to 2.6x and 4.2x speedup for SpMV and SpGEMM, respectively.

97 MATHEMATICS AND COMPUTING↗

Kink band and shear band localization in anisotropic perfectly plastic solids

Shear-driven strain localization has been observed in a wide variety of materials and may take the form of shear bands or kink bands. Based on observations of kink bands in plastically anisotropic metallic nanolaminates and single crystal metals, here we posit that, for the specific case of isochoric deformation, the kinematics of kink band formation are indistinguishable from those of plane strain shear band formation. The only distinction between shear bands and kink bands in these systems would then be that kink bands ‘lock up’ at a particular value of material rotation while shear bands may progress to arbitrarily high strains. In order to investigate whether strong material anisotropy is sufficient to arrest shear localization at a geometry that matches the classic kink band geometry, we model the development of a band of simple shear within an anisotropic perfectly plastic material. The resulting analytical model provides the stress state needed to maintain the kinematics of simple shear as a function of material anisotropy, deformation band orientation, and shear strain (or equivalently, material rotation). It is found that plastic anisotropy can promote either kink band or shear band formation depending on the loading orientation. When the deviatoric stress is positive parallel to the plane of anisotropy, shear localization may progress without bound and a shear band is produced. When the deviatoric stress is negative parallel to the plane of anisotropy, shear localization is arrested after a certain material rotation, resulting in a kink band. Examination of the requisite applied stress state during kink band formation provides an explanation for the experimentally-observed ‘lock up’ geometry. Solutions for the band boundary inclination angle are obtained and used to provide bounds on permissible band angles for both shear bands and kink bands.

36 MATERIALS SCIENCE↗

Influence of local lattice distortions on electrical transport of refractory high entropy alloys

In this report we employ first-principles alloy theories to assess the influence of local lattice distortions on the electronic transport of six body-centered cubic high-entropy alloys. We find weak disorder smearing of bands in the ideal lattice due to the similar number of valence electrons among alloying elements. Allowing relaxation, we demonstrate that local distortions in NbMoTaW and VNbMoTaW are small while they are anomalously large in HfNbTiZr, HfNbTaTiZr, VCrZrNb and CrNbTiVZr. The Fermi surfaces of the latter are strongly smeared by local distortions, leading to nearly-saturated resistivities. These findings address the important local relaxation effect on the electronic structure of high-entropy alloys.

36 MATERIALS SCIENCE↗

A transfer learning approach for acoustic emission zonal localization on steel plate-like structure using numerical simulation and unsupervised domain adaptation

The detection and localization of damage in metallic structures using acoustic emission (AE) monitoring and artificial intelligence technology such as deep learning has been widely studied. However, a current challenge of this approach is the difficulty of obtaining sufficient labeled historical AE signals for the training process of deep learning models. This problem can be approached through the implementation of transfer learning. The innovation of this paper lies in the development of a transfer learning approach for AE source localization on a stainless-steel structure when no historical labeled AE signals are available for training. A finite element model is developed to generate numerical AE signals for the training. Unsupervised domain adaptation (UDA) technology is utilized to reduce the distribution difference between the numerical and the realistic AE signals and to derive the localization results of the unlabeled realistic AE signals. Finally, the results suggest that the proposed approach is capable of localizing AE signals with high accuracy in the absence of labeled training data.

42 ENGINEERING↗

Local Chemical Strain in PtFe Alloy Nanoparticles

Precise deciphering of the atomic-insight chemical strain and distribution in nanosolids, especially in nanoalloys with disordered structure, is significant to correlate the structure and chemical properties. In this report, we found an abnormally enhanced negative thermal expansion (NTE) along the c axis in a 3.5 nm PtFe magnetic L1 0 alloy, which was usually weakened by the reduced contribution of invar behavior in a nanosized magnetic material. 57 Fe Mössbauer spectra and extended X-ray absorption fine structure studies indicated the local disordered state of chemical coordination of the L1 0 phase. Pair distribution function and reverse Monte Carlo simulation revealed a surface A1-phase coating and atomic-level stretching chemical strain on the heteroatomic pair along the c axis. Local tensile chemical strain and increasing magnetic moments of Fe atoms on the surface of the L1 0 core made a dominant contribution to the enhanced NTE behavior. Furthermore, the present work brings an atomic reveal for the local chemical strain in bimetallic nanomaterials and provides an innovative perspective to tailoring the functional properties according to the local chemical environment.

36 MATERIALS SCIENCE↗

Core/Shell-Like Localized Emission at Atomically Thin Semiconductor–Au Interface

Localized emission in atomically thin semiconductors has sparked significant interest as single-photon sources. Despite comprehensive studies into the correlation between localized strain and exciton emission, the impacts of charge transfer on nanobubble emission remains elusive. Here, in this paper, we report the observation of core/shell-like localized emission from monolayer WSe 2 nanobubbles at room temperature through near-field studies. By altering the electronic junction between monolayer WSe 2 and the Au substrate, one can effectively adjust the semiconductor to metal junction from a Schottky to an Ohmic junction. Through concurrent analysis of topography, potential, tip-enhanced photoluminescence, and a piezo response force microscope, we attribute the core/shell-like emissions to strong piezoelectric potential aided by induced polarity at the WSe 2 –Au Schottky interface which results in spatial confinement of the excitons. Our findings present a new approach for manipulating charge confinement and engineering localized emission within atomically thin semiconductor nanobubbles. These insights hold implications for advancing the nano and quantum photonics with low-dimensional semiconductors.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Stability-driven nonnegative matrix factorization to interpret spatial gene expression and build local gene networks

Spatial gene expression patterns enable the detection of local covariability and are extremely useful for identifying local gene interactions during normal development. The abundance of spatial expression data in recent years has led to the modeling and analysis of regulatory networks. The inherent complexity of such data makes it a challenge to extract biological information. We developed staNMF, a method that combines a scalable implementation of nonnegative matrix factorization (NMF) with a new stability-driven model selection criterion. When applied to a set of Drosophila early embryonic spatial gene expression images, one of the largest datasets of its kind, staNMF identified 21 principal patterns (PP). Providing a compact yet biologically interpretable representation of Drosophila expression patterns, PP are comparable to a fate map generated experimentally by laser ablation and show exceptional promise as a data-driven alternative to manual annotations. Our analysis mapped genes to cell-fate programs and assigned putative biological roles to uncharacterized genes. Finally, we used the PP to generate local transcription factor regulatory networks. Spatially local correlation networks were constructed for six PP that span along the embryonic anterior-posterior axis. Using a two-tail 5% cutoff on correlation, we reproduced 10 of the 11 links in the well-studied gap gene network. In conclusion, the performance of PP with the Drosophila data suggests that staNMF provides informative decompositions and constitutes a useful computational lens through which to extract biological insight from complex and often noisy gene expression data.

59 BASIC BIOLOGICAL SCIENCES↗

Localization dynamics in a centrally coupled system

In systems in which interactions couple a central degree of freedom and a bath, one would expect signatures of the bath's phase to be reflected in the dynamics of the central degree of freedom. This has been recently explored in connection with many-body localized baths coupled with a central qubit or a single-cavity mode - systems with growing experimental relevance in various platforms. Such models also have an interesting connection with Floquet many-body localization via quantizing the external drive, although this has been relatively unexplored. Here we adapt the multilayer multiconfigurational time-dependent Hartree (ML-MCTDH) method, a well-known tree tensor network algorithm, to numerically simulate the dynamics of a central degree of freedom, represented by a d-level system (qudit), coupled to a disordered interacting one-dimensional spin bath. ML-MCTDH allows us to reach ≈10 2 lattice sites, a far larger system size than what is feasible with exact diagonalization or kernel polynomial methods. From the intermediate time dynamics, we find a well-defined thermodynamic limit for the qudit dynamics upon appropriate rescaling of the system-bath coupling. The spin system shows similar scaling collapse in the Edward-Anderson spin-glass order parameter or entanglement entropy at relatively short times. At longer timescales, we see slow growth of the entanglement, which may arise from dephasing mechanisms in the localized system or long-range interactions mediated by the central degree of freedom. Similar signs of localization are shown to appear as well with unscaled system-bath coupling.

1-dimensional spin chains↗

Absence of many-body localization in a single Landau level

The localization properties of the highly excited states of a system projected into a single Landau level are analyzed. An analysis of level spacing ratios for finite size systems shows a clear crossover from extended (GUE) to localized (Poisson) statistics, indicating a many-body localization transition. However, the location of this transition depends very strongly on system size, and appears to scale to infinite disorder in the thermodynamic limit. This result does not depend on the properties of the ground state (such as whether the ground state exhibits topological order), as expected for a transition of highly excited eigenstates. We therefore conclude that many-body localization does not exist in these systems. Our results demonstrate that a subthermodynamic number of single particle effectively extended states is sufficient to cause all many-body states to become extended.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Interpretable machine learning study of the many-body localization transition in disordered quantum Ising spin chains

We apply support vector machine (SVM) to study the phase transition between many-body localized and thermal phases in a disordered quantum Ising chain in a transverse external field. The many-body eigenstate energy E is bounded by a bandwidth W = E max – E min . The transition takes place on a phase diagram spanned by the energy density ε = 2(E – E min )/W and the disorder strength δJ of the spin interaction uniformly distributed within [ – δJ, δJ], formally parallel to the mobility edge in Anderson localization. In our paper, we use the labeled probability density of eigenstate wave functions belonging to the deeply localized and thermal regimes at two different energy densities (ε's) as the training set, i.e., providing labeled data at four corners of the phase diagram. Then we employ the trained SVM to predict the whole phase diagram. The obtained phase boundary qualitatively agrees with previous work using entanglement entropy to characterize these two phases. We further analyze the decision function of the SVM to interpret its physical meaning and find that it is analogous to the inverse participation ratio in configuration space. Our findings demonstrate the ability of the SVM to capture potential quantities that may characterize the many-body localization phase transition.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗