arXiv subjects

Weihua Wang

Publications and source records attributed to Weihua Wang.

At least 37 records · Page 2Linked to original sources

arXiv2024

Distance-Adaptive Quaternion Knowledge Graph Embedding with Bidirectional Rotation

Quaternion contains one real part and three imaginary parts, which provided a more expressive hypercomplex space for learning knowledge graph. Existing quaternion embedding models measure the plausibility of a triplet either through semantic matching or geometric distance scoring functions. However, it appears that semantic matching diminishes the separability of entities, while the distance scoring function weakens the semantics of entities. To address this issue, we propose a novel quaternion knowledge graph embedding model. Our model combines semantic matching with entity's geometric distance to better measure the plausibility of triplets. Specifically, in the quaternion space, we perform a right rotation on head entity and a reverse rotation on tail entity to learn rich semantic features. Then, we utilize distance adaptive translations to learn geometric distance between entities. Furthermore, we provide mathematical proofs to demonstrate our model can handle complex logical relationships. Extensive experimental results and analyses show our model significantly outperforms previous models on well-known knowledge graph completion benchmark datasets. Our code is available at https://github.com/llqy123/DaBR.

cs.LG↗

arXiv2024

Unifying Dual-Space Embedding for Entity Alignment via Contrastive Learning

Entity alignment aims to match identical entities across different knowledge graphs (KGs). Graph neural network-based entity alignment methods have achieved promising results in Euclidean space. However, KGs often contain complex structures, including both local and hierarchical ones, which make it challenging to efficiently represent them within a single space. In this paper, we proposed a novel method UniEA, which unifies dual-space embedding to preserve the intrinsic structure of KGs. Specifically, we learn graph structure embedding in both Euclidean and hyperbolic spaces simultaneously to maximize the consistency between the embedding in both spaces. Moreover, we employ contrastive learning to mitigate the misalignment issues caused by similar entities, where embedding of similar neighboring entities within the KG become too close in distance. Extensive experiments on benchmark datasets demonstrate that our method achieves state-of-the-art performance in structure-based EA. Our code is available at https://github.com/wonderCS1213/UniEA.

cs.CL↗

arXiv2024

Fully Hyperbolic Rotation for Knowledge Graph Embedding

Hyperbolic rotation is commonly used to effectively model knowledge graphs and their inherent hierarchies. However, existing hyperbolic rotation models rely on logarithmic and exponential mappings for feature transformation. These models only project data features into hyperbolic space for rotation, limiting their ability to fully exploit the hyperbolic space. To address this problem, we propose a novel fully hyperbolic model designed for knowledge graph embedding. Instead of feature mappings, we define the model directly in hyperbolic space with the Lorentz model. Our model considers each relation in knowledge graphs as a Lorentz rotation from the head entity to the tail entity. We adopt the Lorentzian version distance as the scoring function for measuring the plausibility of triplets. Extensive results on standard knowledge graph completion benchmarks demonstrated that our model achieves competitive results with fewer parameters. In addition, our model get the state-of-the-art performance on datasets of CoDEx-s and CoDEx-m, which are more diverse and challenging than before. Our code is available at https://github.com/llqy123/FHRE.

cs.AI↗

arXiv2024

Stress-tunable abilities of glass forming and mechanical amorphization

Mechanical amorphization, a widely observed phenomenon, has been utilized to synthesize novel phases by inducing disorder through external loading, thereby expanding the realm of glass-forming systems. Empirically, it has been plausible that mechanical amorphization ability consistently correlates with glass-forming ability. However, through a comprehensive investigation in binary, ternary, and quaternary systems combining neutron diffraction, calorimetric experimental approaches and molecular dynamics simulation, we demonstrate that this impression is only partly true and we reveal that the mechanical amorphization ability can be inversely correlated with the glass forming ability in certain cases To provide insights into these intriguing findings, we present a stress-dependent nucleation theory that offers a coherent explanation for both experimental and simulation results. Our study identifies the intensity of mechanical work, contributed by external stress, as the key control parameter for mechanical amorphization, rendering the ability to tune this process. This discovery not only unravels the underlying correlation between mechanical amorphization and glass-forming ability but also provides a pathway for the design and discovery of new amorphous phases with tailored properties.

cond-mat.mtrl-sci↗

arXiv2024

L^2GC:Lorentzian Linear Graph Convolutional Networks for Node Classification

Linear Graph Convolutional Networks (GCNs) are used to classify the node in the graph data. However, we note that most existing linear GCN models perform neural network operations in Euclidean space, which do not explicitly capture the tree-like hierarchical structure exhibited in real-world datasets that modeled as graphs. In this paper, we attempt to introduce hyperbolic space into linear GCN and propose a novel framework for Lorentzian linear GCN. Specifically, we map the learned features of graph nodes into hyperbolic space, and then perform a Lorentzian linear feature transformation to capture the underlying tree-like structure of data. Experimental results on standard citation networks datasets with semi-supervised learning show that our approach yields new state-of-the-art results of accuracy 74.7$\%$ on Citeseer and 81.3$\%$ on PubMed datasets. Furthermore, we observe that our approach can be trained up to two orders of magnitude faster than other nonlinear GCN models on PubMed dataset. Our code is publicly available at https://github.com/llqy123/LLGC-master.

cs.LG↗

arXiv2024

Inelastic electron scattering at large angles: the phonon polariton contribution

We explore the inelastic electron scattering in SrTiO3, PbTiO3, and SiC in their phonon energy range, challenging the assumption that phonon polaritons are excluded at large angles in high-resolution transmission electron energy-loss spectroscopy. We demonstrate that through multiple scattering, the electron beam can excite both phonons and phonon polaritons, and the relative proportion of each varies depending on the structure factor and scattering angle. Integrating dielectric theory, density functional theory, and multi-slice simulations, we provide a comprehensive framework for understanding these interactions in materials with polar optical phonons.

cond-mat.mtrl-sci↗

arXiv2023

Selenium / Tellurium Two-Dimensional Structures: from Isovalent Se Dopants in Te to Atomically Thin Se Films

Two-dimensional (2D) elemental semiconductors have great potential for device applications, but their performance is limited by the lack of efficient doping methods. Here, combining molecular beam epitaxy, scanning tunneling microscopy/spectroscopy, X-ray photoelectron spectroscopy, and density functional theory calculations, we investigate the evolution of the structural and electronic properties of 2D selenium/tellurium films with increased Se dosages on graphene/6H-SiC(0001) substrates. We found that Se atoms form isovalent dopants by replacing surface Te atoms, which introduces efficient electron doping and lowers the work function of Te films. With the Se dosage increasing, two types of elemental 2D crystalline Se structures, trigonal Se and Se8 molecular assembly films, are obtained on ultrathin Te films, which are distinct from the amorphous Se acquired by depositing Se directly on graphene/6H-SiC(0001). Our results shed light on tuning the electronic properties of 2D elemental semiconductors by isovalent doping and constructing heterostructures of isovalent 2D elemental materials.

cond-mat.mtrl-sci↗

arXiv2023

Tuning the Magnetism in Ultrathin CrxTey Films by Lattice Dimensionality

Two-dimensional (2D) magnetic transition metal compounds with atomic thickness exhibit intriguing physics in fundamental research and great potential for device applications. Understanding the correlations between their macrosopic magnetic properties and the dimensionality of microscopic magnetic exchange interactions are valuable for the designing and applications of 2D magnetic crystals. Here, using spin-polarized scanning tunneling microscopy, magnetization and magneto-transport measurements, we identify the zigzag-antiferromagnetism in monolayer CrTe2, incipient ferromagnetism in bilayer CrTe2, and robust ferromagnetism in bilayer Cr3Te4 films. Our density functional theory calculations unravel that the magnetic ordering in ultrathin CrTe2 is sensitive to the lattice parameters, while robust ferromagnetism with large perpendicular magnetic anisotropy in Cr3Te4 is stabilized through its anisotropic 3D magnetic exchange interactions.

cond-mat.mtrl-sci↗

arXiv2023

Observation of the Breakdown of Optical Phonon Splitting in a Two-dimensional Polar Monolayer

Phonon splitting of the longitudinal optical and transverse optical modes (LO-TO splitting), a ubiquitous phenomenon in three-dimensional (3D) polar materials, is essential for the formation of the 3D phonon polaritons. Theories predict that the LO-TO splitting will break down in two-dimensional (2D) polar systems, but direct experimental verification is still missing. Here, using monolayer hexagonal boron nitride (h-BN) as a prototypical example, we report the direct observation of the breakdown of LO-TO splitting and the finite slope of the LO phonons at the center of the Brillouin zone in 2D polar materials by inelastic electron scattering spectroscopy. Interestingly, the slope of the LO phonon in our measurements is lower than the theoretically predicted value for a freestanding monolayer due to the screening of the Cu foil substrate. This enables the phonon polaritons (PhPs) in monolayer h-BN/Cu foil to exhibit ultra-slow group velocity (~ 5 x 10^-6 c, c is the speed of light) and ultra-high confinement (~ 4000 times smaller wavelength than that of light). Our work reveals the universal law of the LO phonons in 2D polar materials and lays a physical foundation for future research on 2D PhPs.

cond-mat.mtrl-sci↗

arXiv2023

Turing Pattern and Chemical Medium-Range Order of Metallic glasses

The formation of bulk metallic glass requires the constituent elements to have a negative heat of mixing but has no restrictions on its magnitude. An understanding of this issue is lacking due to the absence of a valid method for describing chemical ordering of metallic glasses. For example, the radial distribution function is ineffective in identifying the elemental preferences of packed atoms. Here, we show that using molecular-dynamics simulation, the chemical medium-range ordering of liquid alloys can be evaluated from persistent homology. This inherently arising chemical medium-range order in metallic glasses is exclusively regulated by the activation and inhibition of the constituent components, making the topology of metallic glasses a Turing pattern. The connecting schemes of atoms of the same species form three distinct regions, reflecting different correlations at the short and medium length scales, while the difference in the schemes corresponds to chemical ordering. By changing the elemental types, it is demonstrated that the chemical medium-range order strongly depends on the relative depth of the interatomic-potential wells. The study separates metallic glasses from crystals under the condition of negative heat of mixing by emphasizing their fundamental difference in interatomic potentials.

cond-mat.mtrl-sci↗

arXiv2023

Efficient and accurate simulation of vitrification in multi-component metallic liquids with neural-network potentials

Constructing accurate interatomic potential and overcoming the exponential growth of structural equilibration time are challenges to the atomistic investigations of the composition-dependent structure and dynamics during the vitrification process of deeply supercooled multi-component metallic liquids. In this work, we describe a state-of-the-art strategy to address these challenges simultaneously. In the case of the representative Zr-Cu-Al system, in combination with a general algorithm for generating the neural-network potentials (NNP) of multi-component metallic glasses effectively and accurately, we propose a highly efficient atom-swapping hybrid Monte Carlo (SHMC) algorithm for accelerating the thermodynamic equilibration of deeply supercooled liquids. Extensive calculations demonstrate that the newly developed NNP faithfully reproduces the phase stabilities and structural characteristics obtained from the ab initio calculations and experiments. In the combined NNP-SHMC algorithm, the structure equilibration time in the deeply supercooled temperatures is accelerated by at least five orders of magnitudes, and the quenched glassy samples exhibit comparable stability to those prepared in the laboratory. Our results pave the way for the next-generation studies of the vitrification process and, thereby the composition-dependent glass-forming ability and physical properties of multi-component metallic glasses.

cond-mat.mtrl-sci↗

arXiv2023

Quakes of Compact Stars

Glitches are commonly observed for pulsars, which are explained by various mechanisms. One hypothesis attributes the glitch effect to the instantaneous moment of inertia change of the whole star caused by a starquake, which is similar to earthquakes caused by fast dislocation occurring on planar faults for the static stress, though the quake-induced dynamics responsible for glitch (superfluid vortex vs. pure starquake) remains still unknown. However, a theoretical model to quantitatively explain the stress loading, types of starquakes, and co-seismic change of moment of inertia is rarely discussed. In this study, we incorporate elastic deformation theories of earthquakes into the starquake problems. We compute the field of stress loading associated with rotation deceleration and determine the optimal type of starquakes at various locations. Two types of pulsar structure models, i.e. neutron and strangeon star models, are included in the computation and their differences are notable. Our calculation shows that the observed glitch amplitude can be explained by the starquakes in the strangeon star model, though the required scaled starquake magnitude is much larger than that occurred on the Earth. We further discuss the possibility to compute the energy budget and other glitch phenomena using the starquake model in the elastic medium framework.

astro-ph.HE↗

arXiv2022

Influence of oscillatory shear on nucleation in metallic glasses: a molecular dynamics study

The process of crystal nucleation can be accelerated or retarded by ultrasonic vibration, which is particularly attractive for the addictive manufacture and thermoplastic forming of metallic glasses, however, the effect and mechanism of oscillatory loading on the nucleation process are still elusive. By using molecular dynamics simulation, the changes in the time-temperature-transformation (TTT) curve under oscillatory external loading are systematically investigated in two typical binary alloys. A glass forming ability dependent response to the external loading is found, and the shortest incubation time is insensitive to the external loading, while the corresponding temperature can be significantly shifted. Within the framework of classical nucleation theory, a fitting formula is proposed to describe the simulation data quantitatively. In contrast to stationary shear, the elastic stress, rather than the strain rate, is the key parameter to control the evolution of TTT curve under oscillatory loading. Furthermore, the model shows that oscillatory loading can decouple the mobility and nucleation in the deeply supercooled liquid, hence the formation ability can be enhanced while the nucleation is suppressed, which is particularly helpful for the forming and manufacturing of metallic glasses.

cond-mat.mtrl-sci↗

arXiv2022

Investigating magnetically-induced distortions of neutron stars through gamma-ray burst X-ray plateaus

Magnetic field may distort neutron stars (NSs), but its effect has not been robustly tested through gravitational-wave observation yet due to the absence of a fast rotating Galactic magnetar. Part of gamma-ray bursts (GRBs) are potential to investigate the magnetically-induced distortion since their central objects may be millisecond magnetars. In this paper, we propose a method to estimate the distortions of these possible magnetars under GRB magnetar scenario. According to the case study of GRB 070521, we find a relation between the effective magnetically-induced ellipticity, $ε_{\rm B,eff}$, and the effective dipole magnetic field strength on NS surfaces, $B_{\rm eff}$, namely $ε_{\rm B,eff}\sim 10^{-3}(B_{\rm eff}/10^{15}\rm G)^{2}$. Furthermore, we constrain the internal magnetic-field structure of the magnetar to be $B_{\rm eff}\sim 0.02 $ and $B_{\rm eff}\sim 0.1B_{\rm t}$, where $ $ is the volume-averaged internal toroidal field. The constraint may be used as the initial condition in modeling the structure of NS magnetospheres. At last, the possibility of testing the method shown in this paper through gravitational-wave observations is discussed.

astro-ph.HE↗

arXiv2022

Atomic Origin of Annealing Embrittlement in Metallic Glasses

An atomistic understanding of annealing embrittlement is a longstanding issue for metallic glasses, which is still lacking due to the insurmountable gap between the thermal history of atomic models and laboratory-made samples. Here, based on a thermal-cycling annealing method that can vary the effective quenching rate over ten orders of magnitude, we perform an atomistic study of the ductile-brittle transition in a ternary model metallic glass, which can be keyed to the annealing embrittlement in bulk metallic glasses. We reveal that thermal annealing can effectively obliterate thermally active-able "defects", which are abundant in the hyper-quenched and ductile glass but gives rise to strain-created shear events in the well-annealed and brittle glass. While the activation of the strain-created events eventually causes single shear banding, other local structural disruptions can be "healed" by the same type of events upon stress reversal, thereby hindering shear band broadening or multiplication, and resulting in annealing embrittlement.

cond-mat.mtrl-sci↗

arXiv2022

Atomic-scale Deformation Process of Glasses Unveiled by Stress-induced Structural Anisotropy

Experimentally resolving atomic-scale structural changes of a deformed glass remains challenging owing to the disordered nature of glass structure. Here, we show that the structural anisotropy emerges as a general hallmark for different types of glasses (metallic glasses, oxide glass, amorphous selenium, and polymer glass) after thermo-mechanical deformation, and it is highly correlates with local nonaffine atomic displacements detected by the high-energy X-ray diffraction technique. By analyzing the anisotropic pair density function, we unveil the atomic-level mechanism responsible for the plastic flow, which notably differs between metallic glasses and covalent glasses. The structural rearrangements in metallic glasses are mediated through cutting and formation of atomic bonds, which occurs in some localized inelastic regions embedded in elastic matrix, whereas that of covalent glasses is mediated through the rotation of atomic bonds or chains without bond length change, which occurs in a less localized manner.

cond-mat.mtrl-sci↗

arXiv2022

Geometric Effect of High-Resolution Electron Energy Loss Spectroscopy on the Identification of Plasmons: An Example of Graphene

High-resolution electron energy loss spectroscopy (HREELS) is one of the most powerful methods to detect the dispersion of plasmons. However, we find that in the HREELS measurement, the scattering geometric configuration will seriously affect the identification of plasmons. Here, taking graphene as an example, using the HREELS capable of two-dimensional energy-momentum mapping combined with the intensity distribution calculations, we visually display the intensity distribution of the scattering geometric factor. We demonstrate that the energy loss peaks from the scattering geometric effect may be misinterpreted as the features of an acoustic plasmon. In any HREELS measurement, it is necessary to evaluate the effect of the scattering geometry quantitatively to identify the intrinsic surface excitations.

cond-mat.mes-hall↗

arXiv2021

$p$-Kirchhoff type equation with Neumann boundary conditions

This paper is concerned with the multiplicity results to a class of $p$-Kirchhoff type elliptic equation with the homogeneous Neumann boundary conditions by an abstract linking lemma due to Brézis and Nirenberg. We obtain the twofold results in subcritical and critical cases, which is a meaningful addition and completeness to the known results about Kirchhoff equation.

math.AP↗