arXiv subjects

Qinghua Zhang

Publications and source records attributed to Qinghua Zhang.

At least 73 records · Page 4Linked to original sources

arXiv2024

High resistance of superconducting TiN thin films against environmental attacks

Superconductors, an essential class of functional materials, hold a vital position in both fundamental science and practical applications. However, most superconductors, including MgB$_2$, Bi$_2$Sr$_2$CaCu$_2$O$_{8+δ}$, and FeSe, are highly sensitive to environmental attacks (such as water and moist air), hindering their wide applications. More importantly, the surface physical and chemical processes of most superconductors in various environments remain poorly understood. Here, we comprehensively investigate the high resistance of superconducting titanium nitride (TiN) epitaxial films against acid and alkali attacks. Unexpectedly, despite immersion in acid and alkaline solutions for over 7 days, the crystal structure and superconducting properties of TiN films remain stable, as demonstrated by high-resolution X-ray diffraction, electrical transport, atomic force microscopy, and scanning electron microscope. Furthermore, combining scanning transmission electron microscopy analysis with density functional theory calculations revealed the corrosion mechanisms: acid corrosions lead to the creation of numerous defects due to the substitution of Cl ions for N anions, whereas alkaline environments significantly reduce the film thickness through the stabilization of OH$^\ast$ adsorbates. Our results uncover the unexpected stability and durability of superconducting materials against environmental attacks, highlighting their potential for enhanced reliability and longevity in diverse applications.

cond-mat.supr-con↗

arXiv2024

Versatile Method of Engineering the Band Alignment and the Electron Wavefunction Hybridization of Hybrid Quantum Devices

With the development of quantum technology, hybrid devices that combine superconductors (S) and semiconductors (Sm) have attracted great attention due to the possibility of engineering structures that benefit from the integration of the properties of both materials. However, until now, none of the experiments have reported good control of band alignment at the interface, which determines the strength of S-Sm coupling and the proximitized superconducting gap. Here, we fabricate hybrid devices in a generic way with argon milling to modify the interface while maintaining its high quality. First, after the milling the atomically connected S-Sm interfaces appear, resulting in a large induced gap, as well as the ballistic transport revealed by the multiple Andreev reflections and quantized above-gap conductance plateaus. Second, by comparing transport measurement with Schrödinger-Poisson (SP) calculations, we demonstrate that argon milling is capable of varying the band bending strength in the semiconducting wire as the electrons tend to accumulate on the etched surface for longer milling time. Finally, we perform nonlocal measurements on advanced devices to demonstrate the coexistence and tunability of crossed Andreev reflection (CAR) and elastic co-tunneling (ECT) -- key ingredients for building the prototype setup for realization of Kitaev chain and quantum entanglement probing. Such a versatile method, compatible with the standard fabrication process and accompanied by the well-controlled modification of the interface, will definitely boost the creation of more sophisticated hybrid devices for exploring physics in solid-state systems.

cond-mat.mes-hall↗

arXiv2024

Inferior interfacial superconductivity in 1 UC FeSe/SrVO$_3$/SrTiO$_3$ with screened interfacial electron-phonon coupling

Monolayer FeSe/TiO$_x$ and FeSe/FeO$_x$ interfaces exhibit significant superconductivity enhancement compared to bulk FeSe, with interfacial electron-phonon coupling (EPC) playing a crucial role. However, the reduced dimensionality in monolayer FeSe, which may drive superconducting fluctuations, complicates the understanding of the enhancement mechanisms. Here we construct a new superconducting interface: monolayer FeSe/SrVO$_3$/SrTiO$_3$, in which the itinerant electrons of highly metallic SrVO$_3$ films can screen all the high-energy Fuchs-Kliewer phonons, including those of SrTiO$_3$, making it the first FeSe/oxide system with screened interfacial EPC while maintaining the monolayer FeSe thickness. Despite comparable doping levels, the heavily electron-doped monolayer FeSe/SrVO$_3$ exhibits a lower pairing temperature ($T_\mathrm{g}$ $\sim$ 48 K) than FeSe/SrTiO$_3$ and FeSe/LaFeO$_3$. Our findings disentangle the contributions of interfacial EPC from dimensionality on enhancing $T_\mathrm{g}$ in FeSe/oxide interfaces, underscoring the importance of interfacial EPC in $T_\mathrm{g}$ enhancement. This FeSe/VO$_x$ interface also provides a platform for studying the interfacial superconductivity.

cond-mat.supr-con↗

arXiv2024

A robust three-way classifier with shadowed granular-balls based on justifiable granularity

The granular-ball (GB)-based classifier introduced by Xia, exhibits adaptability in creating coarse-grained information granules for input, thereby enhancing its generality and flexibility. Nevertheless, the current GB-based classifiers rigidly assign a specific class label to each data instance and lacks of the necessary strategies to address uncertain instances. These far-fetched certain classification approachs toward uncertain instances may suffer considerable risks. To solve this problem, we construct a robust three-way classifier with shadowed GBs for uncertain data. Firstly, combine with information entropy, we propose an enhanced GB generation method with the principle of justifiable granularity. Subsequently, based on minimum uncertainty, a shadowed mapping is utilized to partition a GB into Core region, Important region and Unessential region. Based on the constructed shadowed GBs, we establish a three-way classifier to categorize data instances into certain classes and uncertain case. Finally, extensive comparative experiments are conducted with 2 three-way classifiers, 3 state-of-the-art GB-based classifiers, and 3 classical machine learning classifiers on 12 public benchmark datasets. The results show that our model demonstrates robustness in managing uncertain data and effectively mitigates classification risks. Furthermore, our model almost outperforms the other comparison methods in both effectiveness and efficiency.

cs.LG↗

arXiv2024

A multi-field decomposed model order reduction approach for thermo-mechanically coupled gradient-extended damage simulations

Numerical simulations are crucial for comprehending how engineering structures behave under extreme conditions, particularly when dealing with thermo-mechanically coupled issues compounded by damage-induced material softening. However, such simulations often entail substantial computational expenses. To mitigate this, the focus has shifted towards employing model order reduction (MOR) techniques, which hold promise for accelerating computations. Yet, applying MOR to highly nonlinear, multi-physical problems influenced by material softening remains a relatively new area of research, with numerous unanswered questions. Addressing this gap, this study proposes and investigates a novel multi-field decomposed MOR technique, rooted in a snapshot-based Proper Orthogonal Decomposition-Galerkin (POD-G) projection approach. Utilizing a recently developed thermo-mechanically coupled gradient-extended damage-plasticity model as a case study, this work demonstrates that splitting snapshot vectors into distinct physical fields (displacements, damage, temperature) and projecting them onto separate lower-dimensional subspaces can yield more precise and stable outcomes compared to conventional methods. Through a series of numerical benchmark tests, our multi-field decomposed MOR technique demonstrates its capacity to significantly reduce computational expenses in simulations involving severe damage, while maintaining a high level of accuracy.

math.AP↗

arXiv2024

Sequential three-way group decision-making for double hierarchy hesitant fuzzy linguistic term set

Group decision-making (GDM) characterized by complexity and uncertainty is an essential part of various life scenarios. Most existing researches lack tools to fuse information quickly and interpret decision results for partially formed decisions. This limitation is particularly noticeable when there is a need to improve the efficiency of GDM. To address this issue, a novel multi-level sequential three-way decision for group decision-making (S3W-GDM) method is constructed from the perspective of granular computing. This method simultaneously considers the vagueness, hesitation, and variation of GDM problems under double hierarchy hesitant fuzzy linguistic term sets (DHHFLTS) environment. First, for fusing information efficiently, a novel multi-level expert information fusion method is proposed, and the concepts of expert decision table and the extraction/aggregation of decision-leveled information based on the multi-level granularity are defined. Second, the neighborhood theory, outranking relation and regret theory (RT) are utilized to redesign the calculations of conditional probability and relative loss function. Then, the granular structure of DHHFLTS based on the sequential three-way decision (S3WD) is defined to improve the decision-making efficiency, and the decision-making strategy and interpretation of each decision-level are proposed. Furthermore, the algorithm of S3W-GDM is given. Finally, an illustrative example of diagnosis is presented, and the comparative and sensitivity analysis with other methods are performed to verify the efficiency and rationality of the proposed method.

cs.AI↗

arXiv2024

Chern insulator phase realized in dual-gate-tuned MnBi2Te4 thin films grown by molecular beam epitaxy

The intrinsic magnetic order, large topological-magnetic gap and rich topological phases make MnBi2Te4 a wonderful platform to study exotic topological quantum states such as axion insulator and Chern insulator. To realize and manipulate these topological phases in a MnBi2Te4 thin film, precise manipulation of the electric field across the film is essential, which requires a dual-gate structure. In this work, we achieve dual-gate tuning of MnBi2Te4 thin films grown with molecular beam epitaxy on SrTiO3(111) substrates by applying the substrate and an AlOx layer as the gate dielectrics of bottom and top gates, respectively. Under magnetic field of 9T and temperature of 20 mK, the Hall and longitudinal resistivities of the films show inversed gate-voltage dependence, for both top- and bottom-gates, signifying the existence of the dissipationless edge state contributed by Chern insulator phase in the ferromagnetic configuration. The maximum of the Hall resistivity only reaches 0.8 h/e2, even with dual-gate tuning, probably due to the high density of bulk carriers introduced by secondary phases. In the antiferromagnetic state under zero magnetic field, the films show normal insulator behavior. The dual-gated MnBi2Te4 thin films lay the foundation for developing devices based on electrically tunable topological quantum states.

cond-mat.mtrl-sci↗

arXiv2024

Momentum-resolved electronic structures and strong electronic correlations in graphene-like nitride superconductors

Although transition-metal nitrides have been widely applied for several decades, experimental investigations of their high-resolution electronic band structures are rare due to the lack of high-quality single-crystalline samples. Here, we report on the first momentum-resolved electronic band structures of titanium nitride (TiN) films, a remarkable nitride superconductor. The measurements of crystal structures and electrical transport properties confirmed the high quality of these films. More importantly, with a combination of high-resolution angle-resolved photoelectron spectroscopy and the first-principles calculations, the extracted Coulomb interaction strength of TiN films can be as large as 8.5 eV, whereas resonant photoemission spectroscopy yields a value of 6.26 eV. These large values of Coulomb interaction strength indicate that superconducting TiN is a strongly correlated system. Our results uncover the unexpected electronic correlations in transition-metal nitrides, potentially providing a perspective not only to understand their emergent quantum states but also to develop their applications in quantum devices.

cond-mat.mtrl-sci↗

arXiv2024

Disorder-broadened phase boundary with enhanced amorphous superconductivity in pressurized In2Te5

As an empirical tool in materials science and engineering, the iconic phase diagram owes its robustness and practicality to the topological characteristics rooted in the celebrated Gibbs phase law (F = C - P + 2). When crossing the phase diagram boundary, the structure transition occurs abruptly, bringing about an instantaneous change in physical properties and limited controllability on the boundaries (F = 1). Here, we expand the sharp phase boundary to an amorphous transition region (F = 2) by partially disrupting the long-range translational symmetry, leading to a sequential crystalline-amorphous-crystalline (CAC) transition in a pressurized In2Te5 single crystal. Through detailed in-situ synchrotron diffraction, we elucidate that the phase transition stems from the rotation of immobile blocks [In2Te2]2+, linked by hinge-like [Te3]2- trimers. Remarkably, within the amorphous region, the amorphous phase demonstrates a notable 25 % increase of the superconducting transition temperature (Tc), while the carrier concentration remains relatively constant. Furthermore, we propose a theoretical framework revealing that the unconventional boost in amorphous superconductivity might be attributed to an intensified electron correlation, triggered by a disorder-augmented multifractal behavior. These findings underscore the potential of disorder and prompt further exploration of unforeseen phenomena on the phase boundaries.

cond-mat.supr-con↗

arXiv2024

Type-printable photodetector arrays for multichannel meta-infrared imaging

Multichannel meta-imaging, inspired by the parallel-processing capability of neuromorphic computing, offers significant advancements in resolution enhancement and edge discrimination in imaging systems, extending even into the mid- to far-infrared spectrum. Currently typical multichannel infrared imaging systems consist of separating optical gratings or merging multi-cameras, which require complex circuit design and heavy power consumption, hindering the implementation of advanced human-eye-like imagers. Here, we present a novel approach for printable graphene plasmonic photodetector arrays driven by a ferroelectric superdomain for multichannel meta-infrared imaging with enhanced edge discrimination. The fabricated photodetectors exhibited multiple spectral responses with zero-bias operation by directly rescaling the ferroelectric superdomain instead of reconstructing the separated gratings. We also demonstrated enhanced and faster shape classification (98.1%) and edge detection (98.2%) using our multichannel infrared images compared with single-channel detectors. Our proof-of-concept photodetector arrays simplify multichannel infrared imaging systems and hold great potential for applications in efficient edge detection in human-brain-type machine vision.

physics.optics↗

arXiv2024

A robust and tunable Luttinger liquid in correlated edge of transition-metal second-order topological insulator Ta$_2$Pd$_3$Te$_5$

The interplay between topology and interaction always plays an important role in condensed matter physics and induces many exotic quantum phases, while rare transition metal layered material (TMLM) has been proved to possess both. Here we report a TMLM Ta$_2$Pd$_3$Te$_5$ has the two-dimensional second-order topology (also a quadrupole topological insulator) with correlated edge states - Luttinger liquid. It is ascribed to the unconventional nature of the mismatch between charge- and atomic- centers induced by a remarkable double-band inversion. This one-dimensional protected edge state preserves the Luttinger liquid behavior with robustness and universality in scale from micro- to macro- size, leading to a significant anisotropic electrical transport through two-dimensional sides of bulk materials. Moreover, the bulk gap can be modulated by the thickness, resulting in an extensive-range phase diagram for Luttinger liquid. These provide an attractive model to study the interaction and quantum phases in correlated topological systems.

cond-mat.mes-hall↗

arXiv2024

Global solvability for the Boussinesq system with fractional Laplacian

This paper focuses on the global solvability for the Boussinesq system with fractional Laplacian $(-Δ)^α$ in $\mathbb{R}^{n}$ for $n\geq3$. It proves the existence of a small positive number $\varepsilon=\varepsilon(n,α)$ such that for each $0<T<\infty$, if $\frac{1}{2}<α<\frac{2+n}{4}$ and $\|u_{0}\|_{\dot{H}^{s_{0}}}+T^{1/2}\|θ_{0}\|_{\dot{H}^{s_{0}-α}}\leq \varepsilon$, then the fractional Boussinesq system has a unique strong solution on the bounded interval $[0,T]$. If $\frac{1}{2}<α<\frac{2+n}{6}$ and $\|u_{0}\|_{\dot{H}^{s_{0}}}+\|θ_{0}\|_{\dot{H}^{s_{0}-2α}}\leq \varepsilon$, then the fractional Boussinesq system has a unique strong solution on the whole interval $[0,\infty)$.

math.AP↗

arXiv2024

Ultralarge polarization in ferroelectric hafnia-based thin films

Hafnia-based ferroelectrics have become a valuable class of electronic functional materials at the nanoscale, showing great potential for next-generation memory and logic devices. However, more robust ferroelectric properties and better understanding of the polarization mechanisms are currently needed both in technology and science. Herein, we report the properties of oxygen-deficient Hf0.5Zr0.5O2 films with ultralarge remanent polarization (Pr) of 387 uC cm-2 at room temperature (1 kHz). Structure characterizations identify a new ferroelectric monoclinic Pc phase in these Hf0.5Zr0.5O2 films. The in-situ STEM measurements evidence polar displacements of the oxygen atoms, which move up and down in the Pc structure under applied DC bias fields, showing a huge displacement (1.6 A). DFT calculations optimized the Pc structure and also predicted a large polarization. The coexistence of the ferroelectric monoclinic (Pc) phases and orthorhombic (Pca21) is responsible for this superior ferroelectric properties. These findings are promising for hafnia-based ferroelectric applications in integrated ferroelectric devices, energy harvesting and actuators, etc.

cond-mat.mtrl-sci↗

arXiv2024

Synthesis of epitaxial magnetic pyrochlore heterojunctions

The synthesis of stoichiometric and epitaxial pyrochlore iridate thin films presents significant challenges yet is critical for unlocking experimental access to novel topological and magnetic states. Towards this goal, we unveil an in-situ two-stage growth mechanism that facilitates the synthesis of high-quality oriented pyrochlore iridate thin films. The growth starts with the deposition of a pyrochlore titanate as an active iso-structural template, followed by the application of an in-situ solid phase epitaxy technique in the second stage to accomplish the formation of single crystalline, large-area films. This novel protocol ensures the preservation of stoichiometry and structural homogeneity, leading to a marked improvement in surface and interface qualities over previously reported methods. The success of this synthesis approach is attributed to the application of directional laser-heat annealing, which effectively reorganizes the continuous random network of ions into a crystalline structure, as evidenced by our comprehensive analysis of the growth kinetics. This new synthesis approach advances our understanding of pyrochlore iridate film fabrication and opens a new perspective for investigating their unique physical properties.

cond-mat.str-el↗

arXiv2024

Multiscale Positive-Unlabeled Detection of AI-Generated Texts

Recent releases of Large Language Models (LLMs), e.g. ChatGPT, are astonishing at generating human-like texts, but they may impact the authenticity of texts. Previous works proposed methods to detect these AI-generated texts, including simple ML classifiers, pretrained-model-based zero-shot methods, and finetuned language classification models. However, mainstream detectors always fail on short texts, like SMSes, Tweets, and reviews. In this paper, a Multiscale Positive-Unlabeled (MPU) training framework is proposed to address the difficulty of short-text detection without sacrificing long-texts. Firstly, we acknowledge the human-resemblance property of short machine texts, and rephrase AI text detection as a partial Positive-Unlabeled (PU) problem by regarding these short machine texts as partially ``unlabeled". Then in this PU context, we propose the length-sensitive Multiscale PU Loss, where a recurrent model in abstraction is used to estimate positive priors of scale-variant corpora. Additionally, we introduce a Text Multiscaling module to enrich training corpora. Experiments show that our MPU method augments detection performance on long AI-generated texts, and significantly improves short-text detection of language model detectors. Language Models trained with MPU could outcompete existing detectors on various short-text and long-text detection benchmarks. The codes are available at https://github.com/mindspore-lab/mindone/tree/master/examples/detect_chatgpt and https://github.com/YuchuanTian/AIGC_text_detector.

cs.CL↗

arXiv2024

Utilizing Autoregressive Networks for Full Lifecycle Data Generation of Rolling Bearings for RUL Prediction

The prediction of rolling bearing lifespan is of significant importance in industrial production. However, the scarcity of high-quality, full lifecycle data has been a major constraint in achieving precise predictions. To address this challenge, this paper introduces the CVGAN model, a novel framework capable of generating one-dimensional vibration signals in both horizontal and vertical directions, conditioned on historical vibration data and remaining useful life. In addition, we propose an autoregressive generation method that can iteratively utilize previously generated vibration information to guide the generation of current signals. The effectiveness of the CVGAN model is validated through experiments conducted on the PHM 2012 dataset. Our findings demonstrate that the CVGAN model, in terms of both MMD and FID metrics, outperforms many advanced methods in both autoregressive and non-autoregressive generation modes. Notably, training using the full lifecycle data generated by the CVGAN model significantly improves the performance of the predictive model. This result highlights the effectiveness of the data generated by CVGans in enhancing the predictive power of these models.

cs.LG↗

arXiv2023

Pressure-induced structure phase transitions and superconductivity in dual topological insulator BiTe

The (Bi2)m(Bi2Te3)n homologous series possess natural multilayer heterostructure with intriguing physical properties at ambient pressure. Herein, we report the pressure-dependent evolution of the structure and electrical transport of the dual topological insulator BiTe, a member of the (Bi2)m(Bi2Te3)n series. With applied pressure, BiTe exhibits several different crystal structures and distinct superconducting states, which is remarkably similar to other members of the (Bi2)m(Bi2Te3)n series. Our results provide a systematic phase diagram for the pressure-induced superconductivity in BiTe, contributing to the highly interesting physics in this (Bi2)m(Bi2Te3)n series.

cond-mat.supr-con↗

arXiv2023

Metal-to-insulator transition in oxide semimetals by anion doping

Oxide semimetals exhibiting both nontrivial topological characteristics stand as exemplary parent compounds and multiple degrees of freedom, offering great promise for the realization of novel electronic states. In this study, we present compelling evidence of profound structural and transport phase shifts in a recently uncovered oxide semimetal, SrNbO3, achieved through effective in-situ anion doping. Notably, a remarkable increase in resistivity of more than three orders of magnitude at room temperature is observed upon nitrogen-doping. The extent of electronic modulation in SrNbO3 is strongly correlated with the misfit strain, underscoring its phase instability to both chemical doping and crystallographic symmetry variations. Using first-principles calculations, we discern that elevating the level of nitrogen doping induces an upward shift in the conductive bands of SrNbO3-dNd. Consequently, a transition from a metallic state to an insulating state becomes apparent as the nitrogen concentration reaches a threshold of 1/3. This investigation sheds light on the potential of anion engineering in oxide semimetals, offering pathways for manipulating their physical properties. These insights hold promise for future applications that harness these materials for tailored functionalities.

cond-mat.mtrl-sci↗