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At least 649 records · Page 36

The Magnetic Genome of Two-Dimensional van der Waals Materials

Magnetism in two-dimensional (2D) van der Waals (vdW) materials has recently emerged as one of the most promising areas in condensed matter research, with many exciting emerging properties and significant potential for applications ranging from topological magnonics to low-power spintronics, quantum computing, and optical communications. In the brief time after their discovery, 2D magnets have blossomed into a rich area for investigation, where fundamental concepts in magnetism are challenged by the behavior of spins that can develop at the single layer limit. However, much effort is still needed in multiple fronts before 2D magnets can be routinely used for practical implementations. In this comprehensive review, prominent authors with expertise in complementary fields of 2D magnetism (i.e., synthesis, device engineering, magneto-optics, imaging, transport, mechanics, spin excitations, and theory and simulations) have joined together to provide a genome of current knowledge and a guideline for future developments in 2D magnetic materials research.

36 MATERIALS SCIENCE↗

3D oxygen vacancy distribution and defect-property relations in an oxide heterostructure

Oxide heterostructures exhibit a vast variety of unique physical properties. Examples are unconventional superconductivity in layered nickelates and topological polar order in (PbTiO 3 ) n /(SrTiO 3 ) n superlattices. Although it is clear that variations in oxygen content are crucial for the electronic correlation phenomena in oxides, it remains a major challenge to quantify their impact. Here, we measure the chemical composition in multiferroic (LuFeO 3 ) 9 /(LuFe 2 O 4 ) 1 superlattices, mapping correlations between the distribution of oxygen vacancies and the electric and magnetic properties. Using atom probe tomography, we observe oxygen vacancies arranging in a layered three-dimensional structure with a local density on the order of 10 14 cm -2 , congruent with the formula-unit-thick ferrimagnetic LuFe 2 O 4 layers. The vacancy order is promoted by the locally reduced formation energy and plays a key role in stabilizing the ferroelectric domains and ferrimagnetism in the LuFeO 3 and LuFe 2 O 4 layers, respectively. The results demonstrate pronounced interactions between oxygen vacancies and the multiferroic order in this system and establish an approach for quantifying the oxygen defects with atomic-scale precision in 3D, giving new opportunities for deterministic defect-enabled property control in oxide heterostructures.

36 MATERIALS SCIENCE↗

Local analysis of fast magnetic reconnection

Fast magnetic reconnection is defined by the topology of the magnetic field lines changing on a timescale that is approximately an order of magnitude longer than the topology-conserving ideal-evolution timescale. Fast reconnection is an intrinsic property of Faraday's law when the evolving magnetic field depends non-trivially on all three spatial coordinates and is commonly observed—even when the effects that allow topology breaking are arbitrarily small. The associated current density need only be enhanced by a factor of approximately ten and flows in thin but broad ribbons along the magnetic field. These results follow from the variation in the separation of neighboring pairs of magnetic field lines, which in an ideal evolution typically increases exponentially with time, and the existence of a spatial scale below which magnetic field lines freely change their identities due to non-ideal effects, such as resistivity. Traditional reconnection theory ignores exponentially large variations and relies on the current density reaching a magnitude that is exponentially larger than is actually required. Here, an analysis of the behavior of magnetic field lines in the neighborhood of an arbitrarily chosen line is used to obtain more precise and rigorous results on intrinsic reconnection. The maximum parallel kinetic energy of collisionless charged particles is shown to have an exponential increase in time during a generic magnetic evolution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Robust Kagome Electronic Structure in Topological Quantum Magnets XMn 6 Sn 6 (X = Dy, Tb, Gd, Y)

Crystal geometry can greatly influence the emergent properties of quantum materials. As an example, the kagome lattice is an ideal platform to study the rich interplay between topology, magnetism, and electronic correlation. In this work, combining high-resolution angle-resolved photoemission spectroscopy and ab initio calculation, we systematically investigate the electronic structure of XMn 6 Sn 6 (X=Dy,Tb,Gd,Y) family compounds. Here, we observe the Dirac fermion and the flat band arising from the magnetic kagome lattice of Mn atoms. Interestingly, the flat band locates in the same energy region in all compounds studied, regardless of their different magnetic ground states and 4f electronic configurations. These observations suggest a robust Mn magnetic kagome lattice across the XMn 6 Sn 6 family, thus providing an ideal platform for the search for, and investigation of, new emergent phenomena in magnetic topological materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Computational design of metamaterials with self contact

Inverse homogenization in combination with contact modeling, topology optimization and shape optimization is used to design metamaterials with optimized macroscopic response. The homogenization assumes length scale separation which allows the non-linear macroscopic behavior to be obtained by analyzing a single unit cell in a lattice structure. Self contact in the unit cell, which is modeled using a third medium contact method, is leveraged to obtain a complex homogenized response. The inverse homogenization problem is initially formulated as a topology optimization problem, where the macroscopic stress–strain behavior is tuned to our liking. However, it is well known that boundary phenomena are difficult to model in topology optimization and that interface modeling is crucial to accurately analyze contact. For that reason, the boundary representation of the topology optimized design is extracted and used as initial design in a subsequent shape optimization. The behaviors of our designs are verified by performing rigorous post-processing analyzes using conforming meshes and conventional contact formulations.

42 ENGINEERING↗

An asymptotic-preserving semi-Lagrangian algorithm for the anisotropic heat transport equation with arbitrary magnetic fields

Here, we extend the recently proposed semi-Lagrangian algorithm for the extremely anisotropic heat transport equation [Chacón et al., J. Comput. Phys ., 272 (2014)] to deal with arbitrary magnetic field topologies. The original scheme (which showed remarkable numerical properties) was valid for the so-called tokamak-ordering regime, in which the magnetic field magnitude was not allowed to vary much along field lines. The proposed extension maintains the attractive features of the original scheme (including the analytical Green's function, which is critical for tractability) with minor modifications, while allowing for completely general magnetic fields. The accuracy and generality of the approach are demonstrated by numerical experiment with an analytical manufactured solution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Tunable phononic bandgap materials designed via topology optimization

Topology optimization is used to design phononic bandgap materials that are tunable by mechanical deformation. A periodic media is considered, which due to the assumption of length scale separation, allows the dispersion relations to be obtained by analyzing a single unit cell subjected to Floquet–Bloch boundary conditions. A finite macroscopic deformation is applied to the unit cell to affect its geometry and hence dispersion. We tune the dispersion–deformation relation to our liking by solving a topology optimization problem using nonlinear programming. The adjoint method is employed to compute the sensitivities, and the non-differentiability of degenerate eigenvalues is avoided using symmetric polynomials. Several tunable phononic crystal designs are presented. Also, a verification analysis is performed, wherein the optimized design is interpreted and analyzed using a conforming finite element mesh.

42 ENGINEERING↗

Phase Discovery and Selected Synthesis of Subvalent Niobium Tellurides Using a Polytelluride Flux Strategy

Transition metal subchalcogenides involve electron-rich metals and can facilitate an in-depth understanding of the relationships among quantum properties such as superconductivity, charge density wave, and topological band structures. However, effective experimental routes toward synthesizing transition metal subchalcogenides are still lacking, hindering the development of new quantum materials. Herein, we propose a eutectic polytelluride flux strategy as an excellent solution to address phase discovery and crystal growth in transition metal subtelluride systems. We report new phases easily and selectively synthesized using a eutectic “K 3 Te 4 ” polytelluride flux upon adjusting the ratio of Nb metal to flux in the starting materials (K/Nb/Te = 3:x:4). Using a high Nb content in the solvent (x = 2 and 1), crystals of KNb 3 Te 3 O 0.38 and K 0.9 Nb 3 Te 4 are obtained. Both subtellurides exhibit diverse Nb clusters, including face-sharing and edge-sharing Nb 6 octahedral columns and zig-zag Nb chains. Reducing the Nb content to x = 0.33 leads to the formation of a layered compound, K 1.06 NbTe 2 . This compound comprises a NbTe 6 trigonal prism with K intercalated between the layers. Single crystals of known binary Nb tellurides can also be grown using another eutectic flux “KTe 3 . 2 ”, and the obtained NbTe 2 exhibits a new polymorphism with extra trimerization along the b-axis in the Nb–Nb bonded double zig-zag cluster. Finally, precise control over the structural dimensionality and oxidation state, combined with the facile crystal growth process, makes our synthetic strategy an efficient route to explore quantum materials in transition metal subchalcogenides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanochemical Solid Form Screening of Zeolitic Imidazolate Frameworks Using Structure-Directing Liquid Additives

We demonstrate a systematic application of the mechanochemical liquid-assisted grinding (LAG) methodology to screen for forms of zinc imidazolate (ZnIm 2 ), of fundamental importance as the simplest member of the zeolitic imidazolate framework materials family. The exploration of 45 different liquid additives, selected based on their molecular structure and physicochemical properties has resulted in eight different ZnIm 2 topological forms, appearing in 13 crystallographically distinct solid forms (including two previously unknown forms of the crb (BCT) topology), amorphous phases, and the interrupted moc-Zn 4 Im 8 HIm. All prepared topological forms were also explored computationally, using dispersion-corrected periodic density functional theory (DFT) calculations, enabling the rationalization of screening outcomes, and setting the stage for future prediction of additive-directed metal–organic framework (MOF) synthesis. This first systematic exploration of LAG in screening for three-dimensional MOFs demonstrates the potential of the liquid additive to not only accelerate materials synthesis, but also to direct it toward topologically different MOFs. The discovery of novel forms of a material that already exhibits at least 21 crystallographically and functionally different forms provides a strong testimony on the power of mechanochemistry in metal–organic materials discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chiral spin-liquid-like state in pyrochlore iridate thin films

The pyrochlore iridates have become ideal platforms to unravel fascinating correlated and topological phenomena that stem from the intricate interplay among strong spin-orbit coupling, electronic correlations, lattice with geometric frustration, and itinerancy of the 5d electrons. The all-in-all-out antiferromagnetic state, commonly considered as the magnetic ground state, can be dramatically altered in reduced dimensionality, leading to exotic or hidden quantum states inaccessible in bulk. Here, by means of magnetotransport, resonant elastic and inelastic x-ray scattering experiments, we discover an emergent quantum disordered state in (111) Y 2 Ir 2 O 7 thin films (thickness ≤30 nm) persisting down to 5 K, characterized by dispersionless magnetic excitations. The anomalous Hall effect observed below an onset temperature near 125 K corroborates the presence of chiral short-range spin configurations expressed in non-zero scalar spin chirality, breaking the macroscopic time-reversal symmetry. The origin of this chiral state is ascribed to the restoration of magnetic frustration on the pyrochlore lattice in lower dimensionality, where the competing exchange interactions together with enhanced quantum fluctuations suppress any long-range order and trigger spin-liquid-like behavior with degenerate ground-state manifold.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Machine learning-based multidomain processing for texture-based image segmentation and analysis

Atomic and molecular resolved atomic force microscopy (AFM) images offer unique insights into materials' properties such as local ordering, molecular orientation, and topological defects, which can be used to pinpoint physical and chemical interactions occurring at the surface. Utilizing machine learning for extracting underlying physical parameters increases the throughput of AFM data processing and eliminates inconsistencies intrinsic to manual image analysis, thus enabling the creation of reliable frameworks for qualitative and quantitative evaluation of experimental data. Here, we present a robust and scalable approach to the segmentation of AFM images based on flexible pre-selected classification criteria. The usage of supervised learning and feature extraction allows us to retain the consideration of specific problem-dependent features (such as types of periodical structures observed in the images and the associated numerical parameters: spacing, orientation, etc.). We highlight the applicability of this approach for the segmentation of molecular resolved AFM images based on the crystal orientation of the observed domains, automated selection of boundaries, and collection of relevant statistics. Finally, we outline a general strategy for machine learning-enabled analysis of nanoscale systems exhibiting periodic order that could be applied to any analytical imaging technique

36 MATERIALS SCIENCE↗

Defects in bent-core liquid crystals

The spatial organization of liquid crystals (LCs) is governed by molecular shapes and interactions and reveals itself at the macroscopic scale by anisotropic properties and various textures with an abundance of topological defects. LC defects, representing singular and non-singular distortions of the orientational order, carry signatures of the undistorted ground LC state and bear specific information that helps to identify phases in newly synthesized materials. The review describes defects in materials with bent-core shape of molecules.

36 MATERIALS SCIENCE↗

A Data Processing Pipeline for Socio-Technical Network Analysis [Slides]

With the rapid adoption of emerging technologies, there is a need to catalog and model sociotechnical interdependencies that have been historically used to influence the operation of Critical Infrastructure networks including the impacts of mergers and acquisitions, hostile takeovers, and foreign investment. Our research intends to address this need with two primary contributions. First, we have developed a data curation and processing pipeline to generate sociotechnical networks extracted from a variety of data sources including SEC filings and infrastructure asset databases. The pipeline, implemented in Apache Airflow, extracts and normalizes the representation of entities and relations, specified within ontologies. Second, networks produced by our pipeline enable the development of graph-theoretic metrics that consider the properties of network components in addition to its topology. Measures of network complexity, such as degree distribution, reachability analyses, temporal analysis, and community detection may be adapted to indicate adversarial organizational influence. Our intent is to provide an extensible, machine-actionable approach to quickly communicate such models, reproduce previous results, and adapt them to new, unanticipated situations.

97 MATHEMATICS AND COMPUTING↗

A Data Processing Pipeline for Adversarial Socio-Technical Network Analysis

With the rapid adoption of emerging technologies, there is a need to catalog and model sociotechnical interdependencies that have been historically used to influence the operation of Critical Infrastructure networks including the impacts of mergers and acquisitions, hostile takeovers, and foreign investment. Our research intends to address this need with two primary contributions. First, we have developed a data curation and processing pipeline to generate sociotechnical networks extracted from a variety of data sources including SEC filings and infrastructure asset databases. The pipeline, implemented in Apache Airflow, extracts and normalizes the representation of entities and relations, specified within ontologies. Our intent is to provide an extensible, machine-actionable approach to quickly communicate such models, reproduce previous results, and adapt them to new, unanticipated situations. Second, networks produced by our pipeline enable the development of graph-theoretic metrics that consider the properties of network components in addition to its topology. Metadata associated with network components---whether semantic, temporal, or geospatial---affects the alignment of generated networks with assumptions underlying complexity metrics. Validation of generated networks relative to component types defined by an ontology, may allow the research community to adapt metrics to the semantics of the domains being studied. Generated networks may be processed as knowledge, dynamic, or spatial graphs and enables a variety of analyses including automated reasoning and measures of network complexity. Automated reasoning views extracted entities and relations as a knowledge graph; this enables application of inference rules that represent historically-attested adversarial business methods and applies that behavior to a specific geographic context. Measures of network complexity, including degree distribution, reachability analyses, temporal analysis, and community detection can be adapted to indicate adversarial organizational influence.

97 MATHEMATICS AND COMPUTING↗

Measuring Topological Constraint Relaxation in Ring-Linear Polymer Blends

Polymers are an effective test bed for studying topological constraints in condensed matter due to a wide array of synthetically available chain topologies. When linear and ring polymers are blended together, emergent rheological properties are observed as the blend can be more viscous than either of the individual components. This emergent behavior arises since ring-linear blends can form long-lived topological constraints as the linear polymers thread the ring polymers. Here, in this work, we demonstrate how the Gauss linking integral can be used to efficiently evaluate the relaxation of topological constraints in ring-linear polymer blends. For majority-linear blends, the relaxation rate of topological constraints depends primarily on reptation of the linear polymers, resulting in the diffusive time τ d,R for rings of length N R blended with linear chains of length N l to scale as τ d,R ~ N$^2_R$N$^{3.4}_L$.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

"Hall" transport of liquid crystal solitons in Couette flow

Topology establishes a unifying framework for a diverse range of scientific areas including particle physics, cosmology, and condensed matter physics. One of the most fascinating manifestations of topology in the context of condensed matter is the topological Hall effect, and its relative: the Skyrmion Hall effect. Skyrmions are stable vortex-like spin configurations in certain chiral magnets, and when subject to external electric currents can drift in the transverse direction to the current. These quasi-particles are characterised by a conserved topological charge which in the Skyrmion Hall effect plays the role of electric charges in the ordinary Hall effect. Recently, it has been shown that liquid crystals endowed with chiral properties serve as an ideal testbed for the fundamental investigation of topological solitons, including their two- and three-dimensional realisations. Here, we show experimentally and numerically that three-dimensional solitons aka "torons" exhibit a Hall-like effect when driven by shear flows: the torons are deflected in the direction perpendicular to the shear plane. The experimental results are rationalised in terms of the dynamic Ericksen-Leslie equations, which predict the emergence of the transverse component of the net mass flow, the magnitude of which scales as the 3rd power of the shear rate. The perturbation analysis highlights an interplay of the viscous and chiral elastic torques as the mechanism for the emergence of net transverse currents. Numerical simulations demonstrate, however, that torons are not merely dragged by the flow but move with their own transverse speed, much larger than the average flow velocity in the transverse direction. Our findings may enable responsive microfluidic applications relying on soft topological solitons.

FOS: Physical sciences↗

Controlling structural phases of Sn through lattice engineering

Topology and superconductivity, two distinct phenomena, offer unique insight into quantum properties and their applications in quantum technologies, spintronics, and sustainable energy technologies. Tin (Sn) plays a pivotal role here as an element because of its two structural phases, α-Sn exhibiting topological characteristics and β-Sn showing superconductivity. Here, we demonstrate precise control of these phases in Sn thin films using molecular beam epitaxy with systematically varied lattice parameters of the buffer layer. The Sn films exhibit either β-Sn or α-Sn phases as the buffer layer's lattice constant varies from 6.10 Å to 6.48 Å, spanning the range from GaSb (like InAs) to InSb. Further, the crystal structures of α- and β-Sn films are characterized by x-ray diffraction and confirmed by Raman spectroscopy and scanning transmission electron microscopy. Atomic force microscopy validates the smooth, continuous surface morphology. Electrical transport measurements further verify the phases: resistance drop near 3.7 K for β-Sn superconductivity and Shubnikov-de Haas oscillations for α-Sn topological characteristics. Density functional theory shows that α-Sn is stable under tensile strain and β-Sn under compressive strain, aligning well with experimental findings. Hence, this study introduces a platform controlling Sn phases through lattice engineering, enabling innovative applications in quantum technologies and beyond.

36 MATERIALS SCIENCE↗

Gapless Dirac surface states in the antiferromagnetic topological insulator MnBi 2 Te 4

We used angle-resolved photoemission spectroscopy (ARPES) and density functional theory calculations to study the electronic properties of MnBi 2 Te 4 , a material that was predicted to be an intrinsic antiferromagnetic (AFM) topological insulator. In striking contrast to earlier literature showing a full gap opening between two surface band manifolds on the (0001) surface, we observed a gapless Dirac surface state with a Dirac point sitting at E B = -280 meV . Furthermore, our ARPES data revealed the existence of a second Dirac cone sitting closer to the Fermi level. Surprisingly, these surface states remain intact across the AFM transition. The presence of gapless Dirac states in this material may be caused by different ordering at the surface from the bulk or weaker magnetic coupling between the bulk and surface. Whereas the surface Dirac cones seem to be remarkably insensitive to the AFM ordering most likely due to weak coupling to magnetism, we did observe a splitting of the bulk band accompanying the AFM transition. Finally, with a moderately high ordering temperature and interesting gapless Dirac surface states, MnBi 2 Te 4 provides a unique platform for studying the interplay between magnetic ordering and topology.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗