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At least 163 records · Page 9

d -Electron Heavy Fermion Behavior in a Near-Room-Temperature Polar Metallic Ferrimagnet: A Case of Mn 5 SiC

Polycrystalline Mn 5 SiC was synthesized by using a high-temperature solid-state method. Mn 5 SiC adopts a polar space group (Cmc2 1 ) with six crystallographic Mn sites confirmed by X-ray and neutron diffraction, transmission electron microscopy, and second harmonic generation experiments. The complex crystal structure features edge-sharing trigonal prisms and icosahedra, as well as face/edge-sharing pentagonal prisms. Magnetic measurements indicate ferrimagnetic ordering with a transition temperature of 284 K. The ferrimagnetic structure (magnetic space group Cm’c’2 1 ) was further identified by powder neutron diffraction, where collinear Mn spins align along the crystallographic c-axis. The refined magnetic moment for each crystallographic Mn site at 4 K is 1.8(2), −2.42(9), −1.72(8), 0.51(6), 0.50(4), and 1.7(2) μ B . Density functional theory calculations confirm both the metallic behavior and the ferrimagnetic structure observed experimentally and further provide insight into the observed Mn moment dependence across crystallographic sites. The resistivity and specific heat measurements and density functional theory calculations reveal a substantially large Kadowaki–Woods ratio of 5 × 10 –5 μΩ·cm/(mJ/mol) 2 and a many-body renormalization factor of 5.5, indicating the unusual heavy Fermion behavior in such an itinerant magnetic metal.

Messegee, Zachary T. [George Mason University, Fai↗

Single pair of Weyl nodes in the spin-canted structure of EuCd 2 As 2

We report time reversal symmetry breaking Weyl semimetals are unique among Weyl materials in allowing the minimal number of Weyl points, thus offering the clearest signatures of the associated physics. Here we present neutron diffraction, density-functional theory, and transport measurement results which indicate that EuCd 2 As 2 , under ambient field, strain, and pressure, is such a material with a single pair of Weyl points. Our work reveals a magnetic structure (magnetic space group C2'/m') with Eu moments pointing along the [210] direction in plane and canted ~ 30° out of plane. Density functional theory calculations using this structure show that the observed canting drastically alters the relevant electronic bands, relative to the in-plane order, leading to a single set of well-defined Weyl points. Furthermore, we find the canting angle can tune the distance of the Weyl points above the Fermi level, with the smallest distance at low canting angles. Finally, transport measurements of the anomalous Hall effect and longitudinal magnetoresistance exhibit properties indicative of a chiral anomaly, thus supporting the neutron scattering and DFT results suggesting EuCd 2 As 2 is close to the ideal situation of the Weyl hydrogen atom.

36 MATERIALS SCIENCE↗

Synthesis, Structural Characterization and Chemical Bonding of Sr 7 Li 6 Sn 12 and its Quaternary Derivatives with Eu and Alkaline Earth Metal (Mg, Ca, Ba) Substitutions. A Tale of Seven Li‐Containing Stannides and Two Complex Crystal Structures

In this paper, we discuss the synthesis and the structural characterization of the new ternary compound Sr 7 Li 6 Sn 12 and its six quaternary derivatives, where alkaline earth metals (Ca, Mg, Ba) and the rare earth metal Eu are substituted, yielding crystalline phases of monoclinic or orthorhombic symmetry. The title compounds were synthesized via high‐temperature solid‐state reactions of the corresponding elements. The crystal structures were determined by single‐crystal X‐ray diffraction methods. The (Sr,Ca) 7 Li 6 Sn 12 and Eu 7 (Mg,Li) 6 Sn 12 phases represent a new structure type (space group P 2/ m , No. 10) while Sr 7 Li 6 Sn 12 and the rest of the title phases crystallize in the orthorhombic base‐centered space group Cmmm (No. 65) which is similar to the Eu 7 Li 8– x Sn 10+ x ( x ≈ 2.0) phase with the Ce 7 Li 8 Ge 10 structure type (Pearson code oC 50). Careful examination of the resulting structures shows intricate disordering between Li and Sn atoms, which is governed by the total number of valence electrons. The discussion of experimental results is also supported by DFT electronic structure calculations.

Osman, Hussien H.↗

Visualization and efficient generation of constrained high-dimensional theoretical parameter spaces

We describe a set of novel methods for efficiently sampling high-dimensional parameter spaces of physical theories defined at high energies, but constrained by experimental measurements made at lower energies. Often, theoretical models such as supersymmetry are defined by many parameters, $\mathcal{O}$(10 – 100), expressed at high energies, while relevant experimental constraints are often defined at much lower energies, preventing them from directly ruling out portions of the space. Instead, the low-energy constraints define a complex, potentially non-contiguous subspace of the theory parameters. Naive scanning of the theory space for points which satisfy the low-energy constraints is hopelessly inefficient due to the high dimensionality, and the inverse problem is considered intractable. As a result, many theoretical spaces remain under-explored. We introduce a class of modified generative autoencoders, which attack this problem by mapping the high-dimensional parameter space to a structured low-dimensional latent space, allowing for easy visualization and efficient generation of theory points which satisfy experimental constraints. An extension without dimensional compression, which focuses on limiting potential information loss, is also introduced.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Optical neural engine for solving scientific partial differential equations

Abstract Solving partial differential equations (PDEs) is the cornerstone of scientific research and development. Data-driven machine learning (ML) approaches are emerging to accelerate time-consuming and computation-intensive numerical simulations of PDEs. Although optical systems offer high-throughput and energy-efficient ML hardware, their demonstration for solving PDEs is limited. Here, we present an optical neural engine (ONE) architecture combining diffractive optical neural networks for Fourier space processing and optical crossbar structures for real space processing to solve time-dependent and time-independent PDEs in diverse disciplines, including Darcy flow equation, the magnetostatic Poisson’s equation in demagnetization, the Navier-Stokes equation in incompressible fluid, Maxwell’s equations in nanophotonic metasurfaces, and coupled PDEs in a multiphysics system. We numerically and experimentally demonstrate the capability of the ONE architecture, which not only leverages the advantages of high-performance dual-space processing for outperforming traditional PDE solvers and being comparable with state-of-the-art ML models but also can be implemented using optical computing hardware with unique features of low-energy and highly parallel constant-time processing irrespective of model scales and real-time reconfigurability for tackling multiple tasks with the same architecture. The demonstrated architecture offers a versatile and powerful platform for large-scale scientific and engineering computations.

Tang, Yingheng (ORCID:0009000153622546)↗

Neuroevolutionary Learning of Particles and Protocols for Self-Assembly

Within simulations of molecules deposited on a surface we show that neuroevolutionary learning can design particles and time-dependent protocols to promote self-assembly, without input from physical concepts such as thermal equilibrium or mechanical stability and without prior knowledge of candidate or competing structures. Furthermore, the learning algorithm is capable of both directed and exploratory design: it can assemble a material with a user-defined property, or search for novelty in the space of specified order parameters. In the latter mode it explores the space of what can be made, rather than the space of structures that are low in energy but not necessarily kinetically accessible.

74 ATOMIC AND MOLECULAR PHYSICS↗

CEGANN: CRYSTAL EDGE GRAPH ATTENTION NEURAL NETWORK

SF-22-156 Machine learning (ML) models and applications in materials design and discovery typically involve the use of feature representations or descriptors followed by a learning algorithm that maps them to user desired properties of interest. Most popular mathematical formulation-based descriptors are not unique across atomic environments and suffer from transferability issues across different application domains and/or material classes. The CEGANN code provides a unified interface to facilitate material characterization across materials across multiple scales (from atomic to mesoscale) and diverse classes of materials ranging from metals oxides, non-metals, and even hierarchical materials such as zeolites and semi ordered materials such as mesophases. CEGANN implements a Graph Attention Network (GAT) type convolution architecture. The details of network architecture can be found in the paper https://doi.org/10.48550/arXiv.2207.10168. The software comes with pretrained examples and dataset for the classification of the following representative systems: (1) Structure-level representation such as space group (2) Structural dimensionality (e.g., bulk, 2D, clusters etc.) (3) Grain boundary identification (4) Nucleation and growth of a zeolite polymorph (5) Characterization of binary mesophases and their phase transitions (6) Growth of ice. The code is written in python programming language.

CHAN, HENRYT↗

Diffuse scattering from correlated electron systems

The role of inhomegeneity in determining the properties of correlated electron systems is poorly understood because of the dearth of structural probes of disorder at the nanoscale. Advances in both neutron and x-ray scattering instrumentation now allow comprehensive measurements of diffuse scattering in single crystals over large volumes of reciprocal space, enabling structural correlations to be characterized over a range of length scales from 5 to 200 angstroms or more. When combined with new analysis tools, such as three-dimensional difference pair-distribution functions, these advanced capabilities have produced fresh insights into the interplay of structural fluctuations and electronic properties in a broad range of correlated electron materials. This review describes recent investigations that have demonstrated the importance of understanding structural inhomogeneity pertaining to phenomena as diverse as superconductivity, charge density wave modulations, metal-insulator transitions, and multipolar interactions.

36 MATERIALS SCIENCE↗

Nowcasting Earthquakes in Southern California With Machine Learning: Bursts, Swarms, and Aftershocks May Be Related to Levels of Regional Tectonic Stress

Abstract Seismic bursts in Southern California are sequences of small earthquakes strongly clustered in space and time and include seismic swarms and aftershock sequences. A readily observable property of these events, the radius of gyration ( R G ), allows us to connect the bursts to the temporal occurrence of the largest M ≥ 7 earthquakes in California since 1984. In the Southern California earthquake catalog, we identify hundreds of these potentially coherent space‐time structures in a region defined by a circle of radius 600 km around Los Angeles. We compute R G for each cluster then filter them to identify those bursts with large numbers of events closely clustered in space, which we call “compact” bursts. Our basic assumption is that these compact bursts reflect the dynamics associated with large earthquakes. Once we have filtered the burst catalog, we apply an exponential moving average to construct a time series for the Southern California region. We observe that the R G of these bursts systematically decreases prior to large earthquakes, in a process that we might term “radial localization.” The R G then rapidly increases during an aftershock sequence, and a new cycle of “radial localization” then begins. These time series display cycles of recharge and discharge reminiscent of seismic stress accumulation and release in the elastic rebound process. The complex burst dynamics we observe are evidently a property of the region as a whole, rather than being associated with individual faults. This new method allows us to improve earthquake nowcasting, which is a technique to evaluate the current state of hazard in a seismically active region.

58 GEOSCIENCES↗

Atomic‐Scale Surface Imaging of Bulk Epitaxial CsPbBr 3 Perovskite Single Crystals on Mica Using Light Assisted Scanning Tunneling Microscopy at Low‐Temperature (80 K)

Epitaxial single-crystalline CsPbBr 3 perovskite films on mica, prepared ex situ, are explored using a low-temperature scanning tunneling microscope (STM) by probing the unoccupied electronic states of their surface in ultra-high vacuum (UHV) at 80 K. Light-assisted STM measurements under a broadband illumination with visible light were employed to enhance and stabilize surface conductivity. STM imaging across the surface of macroscopic bulk CsPbBr 3 films reveals large flat terraces characterized by a specific type of surface reconstruction, consisting of parallel rows of U-shaped atomic nanostructures. These structures are spaced by 12 Å and exhibit an internal feature size of 5.1 Å. Density functional theory (DFT) calculations reproduce the experimental observations and reveal a competition between different orthorhombic CsPbBr 3 (110) surface reconstructions: a Cs-rich structure, identified as the most energetically stable, and three alternative Pb–Br-rich reconstructions, which are slightly higher in energy yet remain consistent with the STM data. Additional analyses that explicitly account for the mica substrate exclude the cubic CsPbBr 3 phase and other orthorhombic surface orientations, while showing that variations in the mica surface termination do not alter the preferred CsPbBr 3 (110) reconstruction. In conclusion, this combined approach thereby confirms our assignment and resolves previous STM interpretations of CsPbBr 3 .

36 MATERIALS SCIENCE↗

Synthesis and Transport Properties of the Family of Zintl Phases Ca 3 RESb 3 (RE = La–Nd, Sm, Gd–Tm, Lu): Exploring the Roles of Crystallographic Disorder and Core 4f Electrons for Enhancing Thermoelectric Performance

Zintl phases with complex crystal structures have been studied as promising candidate-materials for thermoelectric (TE) applications. Here, we report the syntheses of the family of rare-earth metal Zintl phases with the general formula Ca 4–x RE x Sb 3 (x ≈ 1; RE = La–Nd, Sm, Gd–Tm, Lu). The structural elucidation is based on refinements of single-crystal X-ray diffraction data for 12 unique chemical compositions. The cubic structure is confirmed as belonging to the anti-Th 3 P 4 structure type (space group I4¯3d, no. 220, Z = 4), where the Ca and RE atoms share the same atomic site with ca. 75% and 25% occupancies, respectively. Such crystallographic disordering of divalent Ca and trivalent RE atoms in the structure provides a pathway to intricate bonding. The latter, together with the presence of heavy elements such as Sb and the lanthanides, are expected to enhance the scattering probability of phonons, thereby leading to as low thermal conductivity κ as that of the ordered RE 4 Sb 3 . The drive of the hypothetical parent compound Ca 4 Sb 3 to be stabilized by alloying with rare-earth metals can be understood following the Zintl-Klemm concept, as the resultant formula may be rationalized as (Ca 2+ ) 3 RE 3+ (Sb 3– ) 3 , indicating the realization of closed-shell electronic configurations for all elements. This notion is confirmed by electronic structure calculations, which reveal narrow bandgaps E g = 0.77 and 0.53 eV for Ca 3 LaSb 3 and Ca 3 LuSb 3 , respectively. Additionally, the incorporation of RE atoms into the structure drives the phase into a state of a degenerate semiconductor with dominant hole charge carriers.

36 MATERIALS SCIENCE↗

Robust antiferromagnetism in Y 2 Co 3

We report on a solution-growth based method to synthesise single crystals of Y 2 Co 3 and on its structural and magnetic properties. We find that Y 2 Co 3 crystallizes in the La 2 Ni 3 -type orthorhombic structure with space group Cmce (No. 64), with Co forming distorted kagome lattices. Y 2 Co 3 orders antiferromagnetically below TN=252 K. Magnetization measurements reveal that the moments are primarily aligned along the b axis with evidence for some canting. Band-structure calculations indicate that ferromagnetic and antiferromagnetic orders are nearly degenerate, at odds with experimental results. Magnetization measurements under pressure up to 1 GPa reveal that the Néel temperature decreases with the slope of -1.69 K/GPa. We observe a field-induced spin-flop transition in the magnetization measurements at 1.5 K and 21 T with magnetic field along the b direction. The magnetization is not saturated up to 35 T, indicating that the antiferromagnetic ordering in Y 2 Co 3 is quite robust, which is surprising for such a Co-rich intermetallic.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Magnetic phase transitions in Eu(Co 1-x Nix) 2-y As 2 single crystals

The effects of Ni doping in Eu(Co 1-x Ni x ) 2-y As 2 single crystals with x = 0 to 1 grown out of self flux are investigated via crystallographic, electronic transport, magnetic, and thermal measurements. All compositions adopt the body-centered-tetragonal ThCr 2 Si 2 structure with space group I 4= mmm . Here, we also find 3-4% of randomly-distributed vacancies on the Co/Ni site. Anisotropic magnetic susceptibility $\chi$α (α = ab; c) data versus temperature T show clear signatures of an antiferromagnetic (AFM) c-axis helix structure associated with the Eu +2 spins-7/2 for x = 0 and x = 1 as previously reported. The $\chi$α (T) data for x = 0.03 and 0.10 suggest an anomalous 2 q magnetic structure containing two helix axes along the c axis and in the ab plane, respectively, whereas for x = 0.75, 0.82, and 1 a c-axis helix is inferred as previously found for x = 1. At intermediate compositions x = 0:2, 0.32, 0.42, 0.54, and 0.65 a magnetic structure with a large ferromagnetic (FM) c-axis component is found from magnetization versus fi eld isotherms, suggested to be an incommensurate FM cone structure associated with the Eu spins, which consists of both AFM and FM components. In addition, the $\chi$ (T) and heat capacity C p (T) data for x = 0.2-0.65 indicate the occurrence of itinerant FM order associated with the Co/Ni atoms with Curie temperatures from 60 K to 25 K, respectively. Electrical resistivity ρ(T) measurements indicate metallic character for all compositions with abrupt increases in slope on cooling below the Eu AFM transition temperatures. In addition to this panoply of magnetic transitions, 151 Eu Mössbauer measurements indicate that ordering of the Eu moments proceeds via an incommensurate sine amplitude-modulated structure with additional transition temperatures associated with this effect.

36 MATERIALS SCIENCE↗

Structure and lattice excitations of the copper substituted lead oxyapatite Pb 9.06⁢(7)⁢ Cu 0.94⁢(6)⁢ (PO 3.92⁢(4) ) 6 ⁢O 0.96⁢(3)

The copper substituted lead oxyapatite, Pb 10-x⁢ Cu x (PO 3.92⁢(4) ) 6 ⁢O 0.96⁢(3) [x = 0.94(6)] was studied using neutron and x-ray diffraction and neutron spectroscopy techniques. The crystal structure of the main phase of our sample, which has come to be colloquially known as LK-99, is verified to possess a hexagonal structure with space group P6 3 /m, alongside the presence of impurity phases Cu and Cu 2 ⁢S. We determine the primary substitution location of the Cu as the Pb1 (6⁢ℎ) site, with a small substitution at the Pb2 (4⁢f) site. Consequently, no clear Cu-doping-induced structural distortion was observed in the investigated temperature region between 10 K and 300 K. Specially, we did not observe a reduction of coordinate number at the Pb2 site or a clear tilting of PO 4 tetrahedron. Magnetic characterization reveals a diamagnetic signal in the specimen, accompanied by a very weak ferromagnetic component at 2 K. No long-range magnetic order down to 10 K was detected by the neutron diffraction. Inelastic neutron scattering measurements did not show magnetic excitations for energies up to 350 meV. There is no sign of a superconducting resonance in the excitation spectrum of this material. The measured phonon density of states compares well with density functional theory calculations performed for the main LK-99 phase and its impurity phases. Our study may shed some insight into the role of the favored substitution site of copper in the absence of structural distortion and superconductivity in LK-99.

36 MATERIALS SCIENCE↗

Combining artificial intelligence and physics-based modeling to directly assess atomic site stabilities: from sub-nanometer clusters to extended surfaces

The performance of functional materials is dictated by chemical and structural properties of individual atomic sites. In catalysts, for instance, the thermodynamic stability of constituting atomic sites is a key descriptor from which more complex properties, such as molecular adsorption energies and reaction rates, can be derived. In this study, we present a widely applicable machine learning (ML) approach to instantaneously compute the stability of individual atomic sites in structurally and electronically complex nano-materials. Conventionally, we determine such site stabilities using computationally intensive first-principles calculations. With our approach, we predict the stability of atomic sites in sub-nanometer metal clusters of 3–55 atoms with mean absolute errors in the range of 0.11–0.14 eV. To extract physical insights from the ML model, we introduce a genetic algorithm (GA) for feature selection. This algorithm distills the key structural and chemical properties governing the stability of atomic sites in size-selected nanoparticles, allowing for physical interpretability of the models and revealing structure–property relationships. The results of the GA are generally model and materials specific. In the limit of large nanoparticles, the GA identifies features consistent with physics-based models for metal–metal interactions. By combining the ML model with the physics-based model, we predict atomic site stabilities in real time for structures ranging from sub-nanometer metal clusters (3–55 atom) to larger nanoparticles (147 to 309 atoms) to extended surfaces using a physically interpretable framework. Finally, we present a proof of principle showcasing how our approach can determine stable and active nanocatalysts across a generic materials space of structure and composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Search for quantum gravity using astrophysical neutrino flavour with IceCube

Along their long propagation from production to detection, neutrinos undergo flavour conversions that convert their types or flavours. High-energy astrophysical neutrinos propagate unperturbed over a billion light years in vacuum and are sensitive to small effects caused by new physics. Effects of quantum gravity are expected to appear at the Planck energy scale. Such a high-energy universe would have existed only immediately after the Big Bang and is inaccessible by human technologies. On the other hand, quantum gravity effects may exist in our low-energy vacuum, but are suppressed by inverse powers of the Planck energy. Measuring the coupling of particles to such small effects is difficult via kinematic observables, but could be observable through flavour conversions. Furthermore, we report a search with the IceCube Neutrino Observatory, using astrophysical neutrino flavours to search for new space–time structure. We did not find any evidence of anomalous flavour conversion in the IceCube astrophysical neutrino flavour data. We apply the most stringent limits of any known technologies, down to 10 –42 GeV –2 with Bayes factor greater than 10 on the dimension-six operators that parameterize the space–time defects. We thus unambiguously reach the parameter space of quantum-gravity-motivated physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

On the Crystal Structure of Colloidally Prepared Metastable Ag2Se Nanocrystals

Structural polymorphism is known for many bulk materials; however, on the nanoscale metastable polymorphs tend to form more readily than in the bulk, and with more structural variety. One such metastable polymorph observed for colloidal Ag2Se nanocrystals has traditionally been referred to as the “tetragonal” phase of Ag2Se. While there are reports on the chemistry and properties of this metastable polymorph, its crystal structure, and therefore electronic structure, has yet to be determined. We report that an anti-PbCl2-like structure type (space group P21/n) accurately describes the powder X-ray diffraction and X-ray total scattering patterns of colloidal Ag2Se nanocrystals prepared by several different methods. Density functional theory (DFT) calculations indicate that the anti-PbCl2-like Ag2Se polymorph is a dynamically stable, narrow-band gap semiconductor. DFT results reveal a dense theoretical Ag2Se phase space with many low-energy polymorphs, which helps explain the large number of polymorphs reported in the literature. Analysis and calculation data are stored in the zip archive. The `ag2se-calcs.aiida.` contains the provenance of the calculations and can be imported into an AiiDA database instance. The antiPbCl2like_Ag2Se_laboratory.cif file is the Reitveld refined Ag2Se structure starting from the PbCl2 structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Decoding structure-spectrum relationships with physically organized latent spaces

Here, a semisupervised machine learning method for the discovery of structure-spectrum relationships is developed and then demonstrated using the specific example of interpreting x-ray absorption near-edge structure (XANES) spectra. This method constructs a one-to-one mapping between individual structure descriptors and spectral trends. Specifically, an adversarial autoencoder is augmented with a rank constraint (RankAAE). The RankAAE methodology produces a continuous and interpretable latent space, where each dimension can track an individual structure descriptor. As a part of this process, the model provides a robust and quantitative measure of the structure-spectrum relationship by decoupling intertwined spectral contributions from multiple structural characteristics. This makes it ideal for spectral interpretation and the discovery of descriptors. The capability of this procedure is showcased by considering five local structure descriptors and a database of >50 000 simulated XANES spectra across eight first-row transition metal oxide families. The resulting structure-spectrum relationships not only reproduce known trends in the literature but also reveal unintuitive ones that are visually indiscernible in large datasets. The results suggest that the RankAAE methodology has great potential to assist researchers in interpreting complex scientific data, testing physical hypotheses, and revealing patterns that extend scientific insight.

36 MATERIALS SCIENCE↗