Giant Uniaxial Magnetocrystalline Anisotropy in SmCrGe 3
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Xu, Mingyu↗
Engineering topics
Li, Mingda
Publications and source records attributed to Li, Mingda.
Virtual node graph neural network for full phonon prediction
Understanding the structure-property relationship is crucial for designing materials with desired properties. The past few years have witnessed remarkable progress in machine-learning methods for this connection. However, substantial challenges remain, including the generalizability of models and prediction of properties with materials-dependent output dimensions. Here we present the virtual node graph neural network to address the challenges. By developing three virtual node approaches, we achieve Γ-phonon spectra and full phonon dispersion prediction from atomic coordinates. We show that, compared with the machine-learning interatomic potentials, our approach achieves orders-of-magnitude-higher efficiency with comparable to better accuracy. This allows us to generate databases for Γ-phonon containing over 146,000 materials and phonon band structures of zeolites. Additionally, our work provides an avenue for rapid and high-quality prediction of phonon band structures enabling materials design with desired phonon properties. The virtual node method also provides a generic method for machine-learning design with a high level of flexibility. In this study, the authors present a virtual node graph neural network to enable the prediction of material properties with variable output dimensions. This method offers fast and accurate predictions of phonon band structures in complex solids.
36 MATERIALS SCIENCE↗
INSPIRED: Inelastic neutron scattering prediction for instantaneous results and experimental design
Inelastic neutron scattering (INS) has unique advantages in probing how atoms vibrate and how the vibrations propagate and interact. Such dynamic information is crucial in understanding various material properties, from heat capacity, thermal conductivity, phase transitions, and chemical reactions to more exotic quantum behavior. The analysis and interpretation of the INS spectra often start from a model structure of the sample, followed by a series of calculations to obtain the simulated spectra to compare with experiments. The conventional way to perform such calculations usually requires significant time, computing resources, and specialized expertise. Here, we present a new program named INSPIRED (Inelastic Neutron Scattering Prediction for Instantaneous Results and Experimental Design), which enables users to perform rapid INS simulations in several different ways on their personal computers in just a few clicks, with the crystal structure as the only input file. Specifically, the users can choose a pre-trained symmetry-aware neural network (coupled with an autoencoder) to predict the phonon density of states (DOS), 1D S(E) and 2D S(|Q|,E) spectra for any given structure. One can also choose an existing density functional theory (DFT) calculation from a database (containing over 12,000 crystals), and quickly obtain the simulated INS spectra for single crystals and powders. It is also possible to use pre-trained universal machine learning force fields to relax a given crystal structure, calculate the phonon dispersion and DOS, and, subsequently, the INS spectra. All these functions are implemented with a PyQt graphic user interface. Finally, we expect these new tools will benefit broad user communities and significantly improve the efficiency of experiment design, execution, and data analysis for INS.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Triangular Lattice of Ho 3+ with S eff = 1/2 in Antiferromagnetic KHoSe 2
Not Available
36 MATERIALS SCIENCE↗
Field-free deterministic switching of all–van der Waals spin-orbit torque system above room temperature
Two-dimensional van der Waals (vdW) magnetic materials hold promise for the development of high-density, energy-efficient spintronic devices for memory and computation. Recent breakthroughs in material discoveries and spin-orbit torque control of vdW ferromagnets have opened a path for integration of vdW magnets in commercial spintronic devices. However, a solution for field-free electric control of perpendicular magnetic anisotropy (PMA) vdW magnets at room temperatures, essential for building compact and thermally stable spintronic devices, is still missing. Here, we report a solution for the field-free, deterministic, and nonvolatile switching of a PMA vdW ferromagnet, Fe 3 GaTe 2 , above room temperature (up to 320 K). We use the unconventional out-of-plane anti-damping torque from an adjacent WTe 2 layer to enable such switching with a low current density of 2.23 × 10 6 A cm –2 . This study exemplifies the efficacy of low-symmetry vdW materials for spin-orbit torque control of vdW ferromagnets and provides an all-vdW solution for the next generation of scalable and energy-efficient spintronic devices.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Three-dimensional flat bands in pyrochlore metal CaNi 2
Electronic flat-band materials host quantum states characterized by a quenched kinetic energy. These flat bands are often conducive to enhanced electron correlation effects and emergent quantum phases of matter. Long studied in theoretical models, these systems have received renewed interest after their experimental realization in van der Waals heterostructures and quasi-two-dimensional (2D) crystalline materials. An outstanding experimental question is if such flat bands can be realized in three-dimensional (3D) networks, potentially enabling new materials platforms and phenomena. Here we investigate the C15 Laves phase metal CaNi 2 , which contains a nickel pyrochlore lattice predicted at a model network level to host a doubly-degenerate, topological flat band arising from 3D destructive interference of electronic hopping. Using angle-resolved photoemission spectroscopy, we observe a band with vanishing dispersion across the full 3D Brillouin zone that we identify with the pyrochlore flat band as well as two additional flat bands that we show arise from multi-orbital interference of Ni d -electrons. Furthermore, we demonstrate chemical tuning of the flat-band manifold to the Fermi level that coincides with enhanced electronic correlations and the appearance of superconductivity. Extending the notion of intrinsic band flatness from 2D to 3D, this provides a potential pathway to correlated behaviour predicted for higher-dimensional flat-band systems ranging from tunable topological to fractionalized phases.
36 MATERIALS SCIENCE↗
Topological Superconductors from a Materials Perspective
Not Available
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
The Effect of Embedded Nanoparticles on the Phonon Spectrum of Ice: An Inelastic X-ray Scattering Study
As a contribution to the ongoing effort toward high-frequency sound manipulation in composite materials, we use Inelastic X-ray Scattering to probe the phonon spectrum of ice, either in a pure form or with a sparse amount of nanoparticles embedded in it. The study aims at elucidating the ability of nanocolloids to condition the collective atomic vibrations of the surrounding environment. We observe that a nanoparticle concentration of about 1 % in volume is sufficient to visibly affect the phonon spectrum of the icy substrate, mainly canceling its optical modes and adding nanoparticle phonon excitations to it. We highlight this phenomenon thanks to the lineshape modeling based on a Bayesian inference, which enables us to capture the finest detail of the scattering signal. The results of this study can empower new routes toward the shaping of sound propagation in materials through the control of their structural heterogeneity.
77 NANOSCIENCE AND NANOTECHNOLOGY↗
One dimensional wormhole corrosion in metals
Corrosion is a ubiquitous failure mode of materials. Often, the progression of localized corrosion is accompanied by the evolution of porosity in materials previously reported to be either three-dimensional or two-dimensional. However, using new tools and analysis techniques, we have realized that a more localized form of corrosion, which we call 1D wormhole corrosion, has previously been miscategorized in some situations. Using electron tomography, we show multiple examples of this 1D and percolating morphology. To understand the origin of this mechanism in a Ni-Cr alloy corroded by molten salt, we combined energy-filtered four-dimensional scanning transmission electron microscopy and ab initio density functional theory calculations to develop a vacancy mapping method with nanometer-resolution, identifying a remarkably high vacancy concentration in the diffusion-induced grain boundary migration zone, up to 100 times the equilibrium value at the melting point. Deciphering the origins of 1D corrosion is an important step towards designing structural materials with enhanced corrosion resistance.
36 MATERIALS SCIENCE↗
Materials Informatics for the Development and Discovery of Future Magnetic Materials
Not provided.
Engineering↗
Panoramic Mapping of Phonon Transport from Ultrafast Electron Diffraction and Scientific Machine Learning
Abstract One central challenge in understanding phonon thermal transport is a lack of experimental tools to investigate frequency‐resolved phonon transport. Although recent advances in computation lead to frequency‐resolved information, it is hindered by unknown defects in bulk regions and at interfaces. Here, a framework that can uncover microscopic phonon transport information in heterostructures is presented, integrating state‐of‐the‐art ultrafast electron diffraction (UED) with advanced scientific machine learning (SciML). Taking advantage of the dual temporal and reciprocal‐space resolution in UED, and the ability of SciML to solve inverse problems involving coupled Boltzmann transport equations, the frequency‐dependent interfacial transmittance and frequency‐dependent relaxation times of the heterostructure from the diffraction patterns are reliably recovered. The framework is applied to experimental Au/Si UED data, and a transport pattern beyond the diffuse mismatch model is revealed, which further enables a direct reconstruction of real‐space, real‐time, frequency‐resolved phonon dynamics across the interface. The work provides a new pathway to probe interfacial phonon transport mechanisms with unprecedented details.
36 MATERIALS SCIENCE↗
Phase-transition-induced thermal hysteresis in Type-II weyl semimetals M o T e 2 and M o 1 − x W x T e 2
The resistivity versus temperature measurement is commonly used for identifying temperature-induced phase-change and the resulting hysteresis loop. However, while the resistance is influenced by both the density of states and the carrier lifetimes, the Seebeck coefficient is influenced predominantly by the density of states, and hence is a better probe of the phase of the material. Here, 1T'-T d temperature-induced phase transition in MoTe 2 is studied using temperature-dependent X-ray diffraction, resistivity, and Seebeck coefficient measurements. A more distinct hysteresis is observed when measuring the Seebeck coefficient which is consistent with direct measurements of the crystallographic angle using the temperature-dependent X-ray diffraction. The Seebeck and electrical resistivity measurements indicate a competing contribution of the electrons and holes. The contribution of electron pockets becomes more dominant when molybdenum atoms are replaced by tungsten. In MoTe 2 , a topologically induced enhancement of the Nernst coefficient is observed at low temperatures and a relatively large phase-transition induced Thomson coefficient of 111 μV∙K -1 is measured at 254 K.
36 MATERIALS SCIENCE↗
Machine‐Learning Spectral Indicators of Topology
Abstract Topological materials discovery has emerged as an important frontier in condensed matter physics. While theoretical classification frameworks have been used to identify thousands of candidate topological materials, experimental determination of materials’ topology often poses significant technical challenges. X‐ray absorption spectroscopy (XAS) is a widely used materials characterization technique sensitive to atoms’ local symmetry and chemical bonding, which are intimately linked to band topology by the theory of topological quantum chemistry (TQC). Moreover, as a local structural probe, XAS is known to have high quantitative agreement between experiment and calculation, suggesting that insights from computational spectra can effectively inform experiments. In this work, computed X‐ray absorption near‐edge structure (XANES) spectra of more than 10 000 inorganic materials to train a neural network (NN) classifier that predicts topological class directly from XANES signatures, achieving F 1 scores of 89% and 93% for topological and trivial classes, respectively is leveraged. Given the simplicity of the XAS setup and its compatibility with multimodal sample environments, the proposed machine‐learning‐augmented XAS topological indicator has the potential to discover broader categories of topological materials, such as non‐cleavable compounds and amorphous materials, and may further inform field‐driven phenomena in situ, such as magnetic field‐driven topological phase transitions.
36 MATERIALS SCIENCE↗
M-STAR: Magnetism second target advanced reflectometer at the Spallation Neutron Source
M-STAR is a next generation polarized neutron reflectometer with advanced capabilities. A new focusing guide concept is optimized for samples with dimensions down to a millimeter range. A proposed hybrid pulse-skipping chopper will enable experiments at constant geometry at one incident angle in a broad range of wavevector transfer Q up to 0.3 A –1 for specular, off-specular, and GISANS measurements. M-STAR will empower nanoscience and spintronics studies routinely on small samples (~2 × 2 mm 2 ) and of atomic-scale thickness using versatile experimental conditions of magnetic and/or electric fields, light, and temperature applied in situ to novel complex device-like nanosystems with multiple buried interfaces. M-STAR will enable improved grazing incidence diffraction measurements, as a surface-sensitive depth-resolved probe of, e.g., the out-of-plane component of atomic magnetic moments in ferromagnetic, antiferromagnetic, and more complex structures as well as in-plane atomic-scale structures inaccessible with contemporary diffractometry and reflectometry. New horizons will be opened by the development of an option to probe near-surface dynamics with inelastic grazing incidence scattering in the time-of-flight mode. These novel options in combination with ideally matched parameters of the second target station will place M-STAR in the world’s leading position for high resolution polarized reflectometry.
47 OTHER INSTRUMENTATION↗
Machine learning magnetism classifiers from atomic coordinates
The determination of magnetic structure poses a long-standing challenge in condensed matter physics and materials science. Experimental techniques such as neutron diffraction are resource-limited and require complex structure refinement protocols, while computational approaches such as first-principles density functional theory (DFT) need additional semi-empirical correction, and reliable prediction is still largely limited to collinear magnetism. Here, we present a machine learning model that aims to classify the magnetic structure by inputting atomic coordinates containing transition metal and rare earth elements. By building a Euclidean equivariant neural network that preserves the crystallographic symmetry, the magnetic structure (ferromagnetic, antiferromagnetic, and nonmagnetic) and magnetic propagation vector (zero or non-zero) can be predicted with an average accuracy of 77.8% and 73.6%. In particular, a 91% accuracy is reached when predicting no magnetic ordering even if the structure contains magneticelement(s). Ourworkrepresents onestepforwardtosolvingthegrand challenge of full magnetic structure determination.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Acid-in-Clay Electrolyte for Wide-Temperature-Range and Long-Cycle Proton Batteries
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Wang, Shitong↗
Electronic properties of correlated kagomé metals AV 3 Sb 5 (A = K, Rb, and Cs): A perspective
Following the discovery of a new family of kagomé prototypical materials with structure AV 3 Sb 5 (A=K, Rb, and Cs), there has been a heightened interest in studying the correlation-driven electronic phenomena in these kagomé lattice systems. The study of these materials has gone beyond magneto-transport measurements to reveal exciting features such as Dirac bands, anomalous Hall effect, bulk superconductivity with T c ~0.9–2.5K, and the observation of charge density wave instabilities, suggesting an intertwining of topological physics and new quantum orders. Moreover, very recent works on numerous types of experiments have appeared further examining the unconventional superconductivity and the exotic electronic states found within these kagomé materials. Theories on the strong interactions that play a role in these systems have been proposed to shed light on the nature of these topological charge density waves. In this brief review, we summarize these recent experimental findings and theoretical proposals and envision the materials as new platforms to study the interplay between topological physics and strongly correlated electronic systems.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Restriction-In-Motion of Surface Ligands Enhances Photoluminescence of Quantum Dots - Experiment and Theory
Here the relationship between emission and ligand restriction of a series of ZnSe/ZnS quantum dots (QDs) encapsulated in nanoparticles is investigated systematically via experiments and quantum theory. The QDs have a ZnSe core and a ZnS shell, capped with hydrophobic ligands (triotylphosphine oxide/hexadecylamine), allowing them to be entrapped in a model biomembrane, bicelle, made of zwitterionic dipalmitoyl and dihexanoyl phosphatidylcholines and charged dipalmitoyl phosphatidylglycerol. Enhanced photoluminescence is observed upon encapsulation, depending on the QD-to-lipid ratio. Transmission electron microscopy and small-angle X-ray scattering confirm that QDs are preferably situated at the rim of bicellar discs. A simplified quantum dissipation heat-bath theory is proposed to correlate the enhancement with slower nonradiative processes caused by the restriction-in-motion (RIM) of the surface ligands. However, Fõrster resonance energy transfer due to QD aggregation counteracts the effect.
36 MATERIALS SCIENCE↗