arXiv subjects

Xiaofeng Qian

Publications and source records attributed to Xiaofeng Qian.

At least 37 records · Page 2Linked to original sources

arXiv2024

Two-Fold Anisotropic Superconductivity in Bilayer T$_d$-MoTe$_2$

Noncentrosymmetric 2D superconductors with large spin-orbit coupling offer an opportunity to explore superconducting behaviors far beyond the Pauli limit. One such superconductor, few-layer T$_d$-MoTe$_2$, has large upper critical fields that can exceed the Pauli limit by up to 600%. However, the mechanisms governing this enhancement are still under debate, with theory pointing towards either spin-orbit parity coupling or tilted Ising spin-orbit coupling. Moreover, ferroelectricity concomitant with superconductivity has been recently observed in the bilayer, where strong changes to superconductivity can be observed throughout the ferroelectric transition pathway. Here, we report the superconducting behavior of bilayer T$_d$-MoTe$ _2$ under an in-plane magnetic field, while systematically varying magnetic field angle and out-of-plane electric field strength. We find that superconductivity in bilayer MoTe$_2$ exhibits a two-fold symmetry with an upper critical field maxima occurring along the b-axis and minima along the a-axis. The two-fold rotational symmetry remains robust throughout the entire superconducting region and ferroelectric hysteresis loop. Our experimental observations of the spin-orbit coupling strength (up to 16.4 meV) agree with the spin texture and spin splitting from first-principles calculations, indicating that tilted Ising spin-orbit coupling is the dominant underlying mechanism.

cond-mat.supr-con↗

arXiv2024

A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction

We consider the prediction of general tensor properties of crystalline materials, including dielectric, piezoelectric, and elastic tensors. A key challenge here is how to make the predictions satisfy the unique tensor equivariance to O(3) group and invariance to crystal space groups. To this end, we propose a General Materials Tensor Network (GMTNet), which is carefully designed to satisfy the required symmetries. To evaluate our method, we curate a dataset and establish evaluation metrics that are tailored to the intricacies of crystal tensor predictions. Experimental results show that our GMTNet not only achieves promising performance on crystal tensors of various orders but also generates predictions fully consistent with the intrinsic crystal symmetries. Our code is publicly available as part of the AIRS library (https://github.com/divelab/AIRS).

cond-mat.mtrl-sci↗

arXiv2024

Observation of the dual quantum spin Hall insulator by density-tuned correlations in a van der Waals monolayer

The convergence of topology and correlations represents a highly coveted realm in the pursuit of novel quantum states of matter. Introducing electron correlations to a quantum spin Hall (QSH) insulator can lead to the emergence of a fractional topological insulator and other exotic time-reversal-symmetric topological order, not possible in quantum Hall and Chern insulator systems. However, the QSH insulator with quantized edge conductance remains rare, let alone that with significant correlations. In this work, we report a novel dual QSH insulator within the intrinsic monolayer crystal of TaIrTe4, arising from the interplay of its single-particle topology and density-tuned electron correlations. At charge neutrality, monolayer TaIrTe4 demonstrates the QSH insulator that aligns with single-particle band structure calculations, manifesting enhanced nonlocal transport and quantized helical edge conductance. Interestingly, upon introducing electrons from charge neutrality, TaIrTe4 only shows metallic behavior in a small range of charge densities but quickly goes into a new insulating state, entirely unexpected based on TaIrTe4's single-particle band structure. This insulating state could arise from a strong electronic instability near the van Hove singularities (VHS), likely leading to a charge density wave (CDW). Remarkably, within this correlated insulating gap, we observe a resurgence of the QSH state, marked by the revival of nonlocal transport and quantized helical edge conduction. Our observation of helical edge conduction in a CDW gap could bridge spin physics and charge orders. The discovery of a dual QSH insulator introduces a new method for creating topological flat minibands via CDW superlattices, which offer a promising platform for exploring time-reversal-symmetric fractional phases and electromagnetism.

cond-mat.mes-hall↗

arXiv2024

QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules

Supervised machine learning approaches have been increasingly used in accelerating electronic structure prediction as surrogates of first-principle computational methods, such as density functional theory (DFT). While numerous quantum chemistry datasets focus on chemical properties and atomic forces, the ability to achieve accurate and efficient prediction of the Hamiltonian matrix is highly desired, as it is the most important and fundamental physical quantity that determines the quantum states of physical systems and chemical properties. In this work, we generate a new Quantum Hamiltonian dataset, named as QH9, to provide precise Hamiltonian matrices for 999 or 2998 molecular dynamics trajectories and 130,831 stable molecular geometries, based on the QM9 dataset. By designing benchmark tasks with various molecules, we show that current machine learning models have the capacity to predict Hamiltonian matrices for arbitrary molecules. Both the QH9 dataset and the baseline models are provided to the community through an open-source benchmark, which can be highly valuable for developing machine learning methods and accelerating molecular and materials design for scientific and technological applications. Our benchmark is publicly available at https://github.com/divelab/AIRS/tree/main/OpenDFT/QHBench.

physics.chem-ph↗

arXiv2024

Complete and Efficient Graph Transformers for Crystal Material Property Prediction

Crystal structures are characterized by atomic bases within a primitive unit cell that repeats along a regular lattice throughout 3D space. The periodic and infinite nature of crystals poses unique challenges for geometric graph representation learning. Specifically, constructing graphs that effectively capture the complete geometric information of crystals and handle chiral crystals remains an unsolved and challenging problem. In this paper, we introduce a novel approach that utilizes the periodic patterns of unit cells to establish the lattice-based representation for each atom, enabling efficient and expressive graph representations of crystals. Furthermore, we propose ComFormer, a SE(3) transformer designed specifically for crystalline materials. ComFormer includes two variants; namely, iComFormer that employs invariant geometric descriptors of Euclidean distances and angles, and eComFormer that utilizes equivariant vector representations. Experimental results demonstrate the state-of-the-art predictive accuracy of ComFormer variants on various tasks across three widely-used crystal benchmarks. Our code is publicly available as part of the AIRS library (https://github.com/divelab/AIRS).

cs.LG↗

arXiv2023

Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian

We consider the prediction of the Hamiltonian matrix, which finds use in quantum chemistry and condensed matter physics. Efficiency and equivariance are two important, but conflicting factors. In this work, we propose a SE(3)-equivariant network, named QHNet, that achieves efficiency and equivariance. Our key advance lies at the innovative design of QHNet architecture, which not only obeys the underlying symmetries, but also enables the reduction of number of tensor products by 92\%. In addition, QHNet prevents the exponential growth of channel dimension when more atom types are involved. We perform experiments on MD17 datasets, including four molecular systems. Experimental results show that our QHNet can achieve comparable performance to the state of the art methods at a significantly faster speed. Besides, our QHNet consumes 50\% less memory due to its streamlined architecture. Our code is publicly available as part of the AIRS library (\url{https://github.com/divelab/AIRS}).

cs.LG↗

arXiv2023

MyoFold: rapid Myocardial tissue and movement quantification via a highly Folded sequence

Purpose: To develop and evaluate a cardiovascular magnetic resonance sequence (MyoFold) for rapid myocardial tissue and movement characterization. Method: MyoFold sequentially performs joint T1/T2 mapping and cine for one left-ventricle slice within a breathing-holding of 12 heartbeats. MyoFold uses balanced Steady-State-Free-Precession (bSSFP) with 2-fold acceleration for data readout and adopts an electrocardiogram (ECG) to synchronize the cardiac cycle. MyoFold first acquires six single-shot inversion-recovery images at the diastole of the first six heartbeats. For joint T1/T2 mapping, T2 preparation (T2-prep) adds different T2 weightings to the last three images. On the remaining six heartbeats, segmented bSSFP is continuously performed for each cardiac phase for cine. We build a neural network and trained it using the numerical simulation of MyoFold for T1 and T2 calculations. MyoFold was validated through phantom and in-vivo experiments and compared to MOLLI, SASHA, T2-prep bSSFP, and convention cine. Results: MyoFold phantom T1 had a 10% overestimation while MyoFold T2 had high accuracy. MyoFold in-vivo T1 had comparable accuracy to that of SASHA and precision to that of MOLLI. MyoFold had good agreement with T2-prep bSSFP in myocardium T2 measurement. There was no difference in the myocardium thickness measurement between the MyoFold cine and convention cine. Conclusion: MyoFold can simultaneously quantify myocardial tissue and movement, with accuracy and precision comparable to dedicated sequences, saving three-fold scan time.

physics.med-ph↗

arXiv2022

Bridging Coherence Optics and Classical Mechanics -- A Universal Light Polarization-Entanglement Complementary Relation

While optics and mechanics are two distinct branches of physics, they are connected. It is well known that geometrical/ray treatment of light has direct analogies to mechanical descriptions of particle motion. However, connections between coherence wave optics and classical mechanics are rarely reported. Here we explore links of the two for an arbitrary light field by performing a quantitative analysis of two optical coherence properties: polarization and entanglement (implied by a wave picture of light due to Huygens and Fresnel). A universal complementary identity relation is obtained. More surprisingly, optical polarization, entanglement, and their identity relation are shown to be quantitatively associated with mechanical concepts of center of mass and moment of inertia through the Huygens-Steiner theorem for rigid body rotation. The obtained result bridges coherence wave optics and classical mechanics through the two theories of Huygens.

physics.optics↗

arXiv2022

Generalized Wilson Loop Method for Nonlinear Light-Matter Interaction

Nonlinear light-matter interaction, as the core of ultrafast optics, bulk photovoltaics, nonlinear optical sensing and imaging, and efficient generation of entangled photons, has been traditionally studied by first-principles theoretical methods with the sum-over-states approach. However, this indirect method often suffers from the divergence at band degeneracy and optical zeros as well as convergence issues and high computation costs when summing over the states. Here, using shift vector and shift current conductivity tensor as an example, we present a gauge-invariant generalized approach for efficient and direct calculations of nonlinear optical responses by representing interband Berry curvature, quantum metric, and shift vector in a generalized Wilson loop. This generalized Wilson loop method avoids the above cumbersome challenges and allows for easy implementation and efficient calculations. More importantly, the Wilson loop representation provides a succinct geometric interpretation of nonlinear optical processes and responses based on quantum geometric tensors and quantum geometric potentials and can be readily applied to studying other excited-state responses.

cond-mat.mtrl-sci↗

arXiv2021

Highly directional and coherent emission from dark excitons enabled by bound states in the continuum

A double-edged sword in two-dimensional material science and technology is an optically forbidden dark exciton. On the one hand, it is fascinating for condensed matter physics, quantum information processing, and optoelectronics due to its long lifetime. On the other hand, it is notorious for being optically inaccessible from both excitation and detection standpoints. Here, we provide an efficient and low-loss solution to the dilemma by reintroducing photonics bound states in the continuum (BICs) to manipulate dark excitons in the momentum space. In a monolayer tungsten diselenide under normal incidence, we observed a giant enhancement with an enhancement factor of ~3,100 for dark excitons enabled by transverse magnetic BICs with intrinsic out-of-plane electric fields. By further employing widely tunable Friedrich-Wintgen BICs, we demonstrated highly directional emission from the dark excitons with a divergence angle of merely 7 degrees. We found that the directional emission is coherent at room temperature, unambiguously shown in polarization analyses and interference measurements. Therefore, the BICs reintroduced as a momentum-space photonic environment could be an intriguing platform to reshape and redefine light-matter interactions in nearby quantum materials, such as low-dimensional materials, otherwise challenging or even impossible to achieve.

physics.optics↗

arXiv2021

The Joint Automated Repository for Various Integrated Simulations (JARVIS) for data-driven materials design

The Joint Automated Repository for Various Integrated Simulations (JARVIS) is an integrated infrastructure to accelerate materials discovery and design using density functional theory (DFT), classical force-fields (FF), and machine learning (ML) techniques. JARVIS is motivated by the Materials Genome Initiative (MGI) principles of developing open-access databases and tools to reduce the cost and development time of materials discovery, optimization, and deployment. The major features of JARVIS are: JARVIS-DFT, JARVIS-FF, JARVIS-ML, and JARVIS-Tools. To date, JARVIS consists of 40,000 materials and 1 million calculated properties in JARVIS-DFT, 1,500 materials and 110 force-fields in JARVIS-FF, and 25 ML models for material-property predictions in JARVIS-ML, all of which are continuously expanding. JARVIS-Tools provides scripts and workflows for running and analyzing various simulations. We compare our computational data to experiments or high-fidelity computational methods wherever applicable to evaluate error/uncertainty in predictions. In addition to the existing workflows, the infrastructure can support a wide variety of other technologically important applications as part of the data-driven materials design paradigm. The JARVIS datasets and tools are publicly available at the website: https://jarvis.nist.gov .

cond-mat.mtrl-sci↗

arXiv2021

Complex Dirac-like Electronic Structure in Atomic Site Ordered Rh3In3.4Ge3.6

We report the synthesis via an indium flux method of a novel single-crystalline compound Rh3In3.4Ge3.6 that belongs to the cubic Ir3Ge7 structure type. In Rh3In3.4Ge3.6, the In and Ge atoms choose to preferentially occupy, respectively, the 12d and 16f sites of the Im-3m space group, thus creating a colored version of the Ir3Ge7 structure. Like the other compounds of the Ir3Ge7 family, Rh3In3.4Ge3.6 shows potential as a thermoelectric displaying a relatively large power factor, PF ~ 2 mW/cmK2, at a temperature T ~ 225 K albeit showing a modest figure of merit, ZT = 8 x 10-4, due to the lack of a finite band gap. These figures might improve through a use of chemical substitution strategies to achieve band gap opening. Remarkably, electronic band structure calculations reveal that this compound displays a complex Dirac-like electronic structure relatively close to the Fermi level. The electronic structure is composed of several Dirac type-I and type-II nodes, and even Dirac type-III nodes that result from the touching between a flat band and a linearly dispersing band. This rich Dirac-like electronic dispersion offers the possibility to observe Dirac type-III nodes and study their role in the physical properties of Rh3In3.4Ge3.6 and related Ir3Ge7-type materials.

cond-mat.mtrl-sci↗

arXiv2020

Large Family of Two-Dimensional Ferroelectric Metals Discovered via Machine Learning

Ferroelectricity and metallicity are usually believed not to coexist because conducting electrons would screen out static internal electric fields. In 1965, Anderson and Blount proposed the concept of 'ferroelectric metal', however, it is only until recently that very rare ferroelectric metals were reported. Here, by combining high-throughput ab initio calculations and data-driven machine learning method with new electronic orbital based descriptors, we systematically investigated a large family (2,964) of two-dimensional (2D) bimetal phosphates, and discovered 60 stable ferroelectrics with out-of-plane polarization, including 16 ferroelectric metals and 44 ferroelectric semiconductors that contain seven multiferroics. The ferroelectricity origins from spontaneous symmetry breaking induced by the opposite displacements of bimetal atoms, and the full-d-orbital coinage metal elements cause larger displacements and polarization than other elements. For 2D ferroelectric metals, the odd electrons per unit cell without spin polarization may lead to a half-filled energy band around Fermi level and is responsible for the metallicity. It is revealed that the conducting electrons mainly move on a single-side surface of the 2D layer, while both the ionic and electric contributions to polarization come from the other side and are vertical to the above layer, thereby causing the coexistence of metallicity and ferroelectricity. Van der Waals heterostructures based on ferroelectric metals may enable the change of Schottky barrier height or the Schottky-Ohmic contact type and induce a dramatic change of their vertical transport properties. Our work greatly expands the family of 2D ferroelectric metals and will spur further exploration of 2D ferroelectric metals.

cond-mat.mtrl-sci↗

arXiv2020

Enhanced Superconductivity in Monolayer $T_d$-MoTe$_2$ with Tilted Ising Spin Texture

Crystalline two-dimensional (2D) superconductors with low carrier density are an exciting new class of materials in which superconductivity coexists with strong interactions, the effects of complex topology are not obscured by disorder, and electronic properties can be strongly tuned by electrostatic gating. Very recently, two such materials, 'magic-angle' twisted bilayer graphene and monolayer $T_d$-WTe$_2$, have been reported to show superconductivity at temperatures near 1 K. Here we report superconductivity in semimetallic monolayer $T_d$-MoTe$_2$. The critical temperature $T_\textrm{c}$ reaches 8 K, a sixty-fold enhancement as compared to the bulk. This anomalous increase in $T_\textrm{c}$ is only observed in monolayers, and may be indicative of electronically mediated pairing. Reflecting the low carrier density, the critical temperature, magnetic field, and current density are all tunable by an applied gate voltage, revealing a superconducting dome that extends across both hole and electron pockets. The temperature dependence of the in-plane upper critical field is distinct from that of $2H$ transition metal dichalcogenides (TMDs), consistent with a tilted spin texture as predicted by \textit{ab initio} theory.

cond-mat.supr-con↗

arXiv2020

Electrically-Tunable High Curie Temperature Two-Dimensional Ferromagnetism in Van der Waals Layered Crystals

Identifying intrinsic low-dimensional ferromagnets with high transition temperature and electrically tunable magnetism is crucial for the development of miniaturized spintronics and magnetoelectrics. Recently long-range 2D ferromagnetism was observed in van der Waals crystals CrI$_3$ and Cr$_2$Ge$_2$Te$_6$, however their Curie temperature is significantly lowered when reducing down to monolayer/few layers. Herein, using renormalized spin-wave theory and first-principles electronic structure theory, we present a theoretical study of electrically tunable 2D ferromagnetism in van der Waals layered CrSBr and CrSeBr semiconductors with high Curie temperature of ~150K and sizable band gap. High transition temperature is attributed to strong anion-mediated superexchange interaction and a sizable spin-wave excitation gap due to large exchange and single-ion anisotropy. Remarkably, hole and electron doping can switch magnetization easy axis from in-plane to out-of-plane direction. These unique characteristics establish monolayer CrSBr and CrSeBr as promising platform for realizing 2D spintronics and magnetoelectrics such as 2D spin field effect transistor.

cond-mat.mtrl-sci↗

arXiv2020

Berry curvature memory through electrically driven stacking transitions

In two-dimensional layered quantum materials, the stacking order of the layers determines both the crystalline symmetry and electronic properties such as the Berry curvature, topology and electron correlation. Electrical stimuli can influence quasiparticle interactions and the free-energy landscape, making it possible to dynamically modify the stacking order and reveal hidden structures that host different quantum properties. Here we demonstrate electrically driven stacking transitions that can be applied to design nonvolatile memory based on Berry curvature in few-layer WTe$_2$. The interplay of out-of-plane electric fields and electrostatic doping controls in-plane interlayer sliding and creates multiple polar and centrosymmetric stacking orders. In situ nonlinear Hall transport reveals such stacking rearrangements result in a layer-parity-selective Berry curvature memory in momentum space, where the sign reversal of the Berry curvature and its dipole only occurs in odd-layer crystals. Our findings open an avenue towards exploring coupling between topology, electron correlations, and ferroelectricity in hidden stacking orders and demonstrate a new low-energy-cost, electrically controlled topological memory in the atomically thin limit.

cond-mat.mtrl-sci↗

arXiv2020

Giant nonlinear photocurrent in $\mathcal{PT}$-symmetric magnetic topological quantum materials

Nonlinear photocurrent in time-reversal invariant noncentrosymmetric systems have attracted substantial interest. Here we propose two new types of second-order nonlinear direct photocurrent as the counterpart of normal shift photocurrent (NSC) and normal injection photocurrent (NIC), namely magnetic shift photocurrent (MSC) and magnetic injection photocurrent (MIC) in time-reversal symmetry and inversion symmetry broken system. We show that MSC is mainly governed by shift vector and interband Berry curvature, and MIC is dominated by absorption strength and asymmetry of the group velocity difference at time-reversed $\pm$$\textbf{k}$ points. MSC and MIC can be induced by circularly and linearly polarized light, respectively, in $\mathcal{PT}$-symmetric systems with $\mathcal{P}$ and $\mathcal{T}$ being individually broken. Taking $\mathcal{PT}$-symmetric magnetic topological quantum material bilayer antiferromagnetic (AFM) MnBi$_2$Te$_4$ as an example, we predict the presence of large MIC in the terahertz frequency regime which can be magnetically switched between two AFM states with time-reversed spin orderings. While NSC vanishes in $\mathcal{T}$-symmetric systems, external electric field breaks $\mathcal{PT}$ symmetry and enables large NSC response which can be electrically switched. MIC and NSC are perpendicular to each other upon linearly $x$/$y$-polarized light, and are highly tunable under electric field, resulting in giant nonlinear photocurrent response down to a few THz regime. It suggests bilayer AFM MnBi$_2$Te$_4$ as a tunable platform with rich THz and magneto-optoelectronic applications. The present work reveals that nonlinear photocurrent provides a powerful tool for deciphering magnetic structures and interactions, particularly fruitful for probing and understanding magnetic topological quantum materials.

cond-mat.mtrl-sci↗

arXiv2020

Graph Neural Network for Hamiltonian-Based Material Property Prediction

Development of next-generation electronic devices for applications call for the discovery of quantum materials hosting novel electronic, magnetic, and topological properties. Traditional electronic structure methods require expensive computation time and memory consumption, thus a fast and accurate prediction model is desired with increasing importance. Representing the interactions among atomic orbitals in any material, a material Hamiltonian provides all the essential elements that control the structure-property correlations in inorganic compounds. Effective learning of material Hamiltonian by developing machine learning methodologies therefore offers a transformative approach to accelerate the discovery and design of quantum materials. With this motivation, we present and compare several different graph convolution networks that are able to predict the band gap for inorganic materials. The models are developed to incorporate two different features: the information of each orbital itself and the interaction between each other. The information of each orbital includes the name, relative coordinates with respect to the center of super cell and the atom number, while the interaction between orbitals are represented by the Hamiltonian matrix. The results show that our model can get a promising prediction accuracy with cross-validation.

physics.comp-ph↗