arXiv subjects

Fan Ye

Publications and source records attributed to Fan Ye.

At least 37 records · Page 2Linked to original sources

arXiv2023

Impact of Zr substitution on the electronic structure of ferroelectric hafnia

$\mathrm{HfO_2}$-based dielectrics are promising for nanoscale ferroelectric applications, and the most favorable material within the family is Zr-substituted hafnia, i.e., $\mathrm{Hf_{1-x}Zr_xO_2}$ (HZO). The extent of Zr substitution can be great, and x is commonly set to 0.5. However, the band gap of $\mathrm{ZrO_2}$ is lower than $\mathrm{HfO_2}$, thus it is uncertain how the Zr content should influence the electronic band structure of HZO. A reduced band gap is detrimental to the cycling endurance as charge injection and dielectric breakdown would become easier. Another issue is regarding the comparison on the band gaps between $\mathrm{HfO_2}$/$\mathrm{ZrO_2}$ superlattices and HZO solid-state solutions. In this work we systematically investigated the electronic structures of $\mathrm{HfO_2}$, $\mathrm{ZrO_2}$ and HZO using self-energy corrected density functional theory. In particular, the conduction band minimum of $Pca2_1$-$\mathrm{HfO_2}$ is found to lie at an ordinary k-point on the Brillouin zone border, not related to any interlines between high-symmetry k-points. Moreover, the rule of HZO band gap variation with respect to x has been extracted. The physical mechanisms for the exponential reduction regime and linear decay regime have been revealed. The band gaps of $\mathrm{HfO_2}$/$\mathrm{ZrO_2}$ ferroelectric superlattices are investigated in a systematic manner, and the reason why the superlattice could possess a band gap lower than that of $\mathrm{ZrO_2}$ is revealed through comprehensive analysis.

cond-mat.mtrl-sci↗

arXiv2022

PromptEM: Prompt-tuning for Low-resource Generalized Entity Matching

Entity Matching (EM), which aims to identify whether two entity records from two relational tables refer to the same real-world entity, is one of the fundamental problems in data management. Traditional EM assumes that two tables are homogeneous with the aligned schema, while it is common that entity records of different formats (e.g., relational, semi-structured, or textual types) involve in practical scenarios. It is not practical to unify their schemas due to the different formats. To support EM on format-different entity records, Generalized Entity Matching (GEM) has been proposed and gained much attention recently. To do GEM, existing methods typically perform in a supervised learning way, which relies on a large amount of high-quality labeled examples. However, the labeling process is extremely labor-intensive, and frustrates the use of GEM. Low-resource GEM, i.e., GEM that only requires a small number of labeled examples, becomes an urgent need. To this end, this paper, for the first time, focuses on the low-resource GEM and proposes a novel low-resource GEM method, termed as PromptEM. PromptEM has addressed three challenging issues (i.e., designing GEM-specific prompt-tuning, improving pseudo-labels quality, and running efficient self-training) in low-resource GEM. Extensive experimental results on eight real benchmarks demonstrate the superiority of PromptEM in terms of effectiveness and efficiency.

cs.DB↗

arXiv2022

Shell DFT-1/2 method towards engineering accuracy for semiconductors: GGA versus LDA

The Kohn-Sham gaps of density functional theory (DFT) obtained in terms of local density approximation (LDA) or generalized gradient approximation (GGA) cannot be directly linked to the fundamental gaps of semiconductors, but in engineering there is a strong demand to match them through certain rectification methods. Shell DFT-1/2 (shDFT-1/2), as a variant of DFT-1/2, is a potential candidate to yield much improved band gaps for covalent semiconductors, but its accuracy depends on the LDA/GGA ground state, including optimized lattice parameters, basic Kohn-Sham gap before self-energy correction and the amount of self-energy correction that is specific to the exchange-correlation (XC) functional. In this work, we test the LDA/GGA as well as shDFT-1/2 results of six technically important covalent semiconductors Si, Ge, GaN, GaP, GaAs and GaSb, with an additional ionic insulator LiF for comparison. The impact of XC flavor (LDA, PBEsol, PBE and RPBE), either directly on the gap value, or indirectly through the optimized lattice constant, is examined comprehensively. Moreover, we test the impact of XC flavor on LDA/GGA and shDFT-1/2 gaps under the condition of fixed experimental lattice constants. In-depth analysis reveals the rule of reaching the best accuracy in calculating the electronic band structures of typical covalent semiconductors. Relevant parameters like lattice constant, self-consistency in shDFT-1/2 runs, as well as the exchange enhancement factor of GGA, are discussed in details.

cond-mat.mtrl-sci↗

arXiv2022

Identification and classification of exfoliated graphene flakes from microscopy images using a hierarchical deep convolutional neural network

Identification of the mechanically exfoliated graphene flakes and classification of the thickness is important in the nanomanufacturing of next-generation materials and devices that overcome the bottleneck of Moore's Law. Currently, identification and classification of exfoliated graphene flakes are conducted by human via inspecting the optical microscope images. The existing state-of-the-art automatic identification by machine learning is not able to accommodate images with different backgrounds while different backgrounds are unavoidable in experiments. This paper presents a deep learning method to automatically identify and classify the thickness of exfoliated graphene flakes on Si/SiO2 substrates from optical microscope images with various settings and background colors. The presented method uses a hierarchical deep convolutional neural network that is capable of learning new images while preserving the knowledge from previous images. The deep learning model was trained and used to classify exfoliated graphene flakes into monolayer (1L), bi-layer (2L), tri-layer (3L), four-to-six-layer (4-6L), seven-to-ten-layer (7-10L), and bulk categories. Compared with existing machine learning methods, the presented method possesses high accuracy and efficiency as well as robustness to the backgrounds and resolutions of images. The results indicated that our deep learning model has accuracy as high as 99% in identifying and classifying exfoliated graphene flakes. This research will shed light on scaled-up manufacturing and characterization of graphene for advanced materials and devices.

cs.CV↗

arXiv2022

Disconnection-Mediated Twin/Twin-Junction Migration in FCC metals

We present the results of novel, time-resolved, in situ HRTEM observations, molecular dynamics (MD) simulations, and disconnection theory that elucidate the mechanism by which the motion of grain boundaries (GBs) in polycrystalline materials are coupled through disconnection motion/reactions at/adjacent to GB triple junctions (TJs). We focus on TJs composed of a pair of coherent twin boundaries (CTBs) and a Σ9 GB. As for all GBs, disconnection theory implies that multiple modes/local mechanisms for CTB migration are possible and that the mode selection is affected by the nature of the driving force for migration. While we observe (HRTEM and MD) CTB migration through the motion of pure steps driven by chemical potential jump, other experimental observations (and our simulations) show that stress-driven CTB migration occurs through the motion of disconnections with a non-zero Burgers vector; these are pure-step and twinning-partial CTB migration mechanisms. Our experimental observations and simulations demonstrate that the motion of a GB drags its delimiting TJ and may force the motion of the other GBs meeting at the TJ. Our experiments and simulations focus on two types of TJs composed of a pair of CTBs and a Σ9 GB; a 107° TJ readily migrates while a 70° TJ is immobile (experiment, simulation) in agreement with our disconnection theory even though the intrinsic mobilities of the constituent GBs do not depend on TJ-type. We also demonstrate that disconnections may be formed at TJs (chemical potential jump/stress driven) and at GB/free surface junctions (stress-driven).

cond-mat.mtrl-sci↗

arXiv2021

Instanton Floer homology, sutures, and Heegaard diagrams

This paper establishes a new technique that enables us to access some fundamental structural properties of instanton Floer homology. As an application, we establish, for the first time, a relation between the instanton Floer homology of a $3$-manifold or a null-homologous knot inside a $3$-manifold and the Heegaard diagram of that $3$-manifold or knot. We further use this relation to compute the instanton knot homology of some families of $(1,1)$-knots, including all torus knots in $S^3$, which were mostly unknown before. As a second application, we also study the relation between the instanton knot homology $KHI(Y,K)$ and the framed instanton Floer homology $I^\sharp(Y)$. In particular, we prove the inequality $\dim_\mathbb{C} I^\sharp(Y)\le \dim_\mathbb{C}KHI(Y,K)$ for all rationally null-homologous knots $K\subset Y$ and we constructed a new decomposition of the framed instanton Floer homology of Dehn surgeries along $K$ that corresponds to the decomposition along torsion spin$^c$ decompositions in monopole and Heegaard Floer theory.

math.GT↗

arXiv2021

Constrained knots in lens spaces

In this paper, we study a special family of $(1,1)$ knots called constrained knots, which includes 2-bridge knots in the 3-sphere $S^3$ and simple knots in lens spaces. Constrained knots are parameterized by five integers and characterized by the distribution of spin$^c$ structures in the corresponding $(1,1)$ diagrams. The knot Floer homology $\widehat{HFK}$ of a constrained knot is thin. We obtain a complete classification of constrained knots based on the calculation of $\widehat{HFK}$ and presentations of knot groups. We provide many examples of constrained knots constructed from surgeries on links in $S^3$, which are related to 2-bridge knots and 1-bridge braids. We also show many examples of constrained knots whose knot complements are orientable hyperbolic 1-cusped manifolds with simple ideal triangulations.

math.GT↗

arXiv2021

Small Dehn surgery and SU(2)

We prove that the fundamental group of 3-surgery on a nontrivial knot in the 3-sphere always admits an irreducible SU(2)-representation. This answers a question of Kronheimer and Mrowka dating from their work on the Property P conjecture. An important ingredient in our proof is a relationship between instanton Floer homology and the symplectic Floer homology of genus-2 surface diffeomorphisms, due to Ivan Smith. We use similar arguments at the end to extend our main result to infinitely many surgery slopes in the interval [3,5).

math.GT↗

arXiv2021

Second-Harmonic Generation in Etchless Lithium Niobate Nanophotonic Waveguides with Bound States in the Continuum

Bound states in the continuum (BICs) have been extensively studied in various systems since its first proposal in quantum mechanics. Photonic BICs can enable optical mode confinement and provide field enhancement for nonlinear optics, but they have rarely been explored in nonlinear integrated photonic waveguides. Applying BICs in photonic integrated circuits enables low-loss light guidance and routing in low-refractive-index waveguides on high-refractive-index substrates, which is suitable for integrated photonics with nonlinear materials. Here, we report experimental demonstration of second-harmonic generation from telecom to near-visible wavelengths on an etchless lithium niobate platform by using a photonic BIC for the second-harmonic mode. The devices feature second-harmonic conversion efficiency of 0.175%W-1cm-2 and excellent thermal stability with a wavelength shift of only 1.7 nm from 25°C to 100°C. Our results represent a new paradigm of nonlinear integrated photonics on a cost-effective and convenient platform, which can enable a broad range of on-chip applications such as optical parametric generation, signal processing, and quantum photonics.

physics.optics↗

arXiv2021

Ultrawide Frequency Tuning of Atomic Layer van der Waals Heterostructure Electromechanical Resonators

We report on the experimental demonstration of atomically thin molybdenum disulfide (MoS2)-graphene van der Waals (vdW) heterostructure nanoelectromechanical resonators with ultrawide frequency tuning. With direct electrostatic gate tuning, these vdW resonators exhibit exceptional tunability, in general, Δf/f0 >200%, for continuously tuning the same device and the same mode (e.g., from ~23 to ~107MHz), up to Δf/f0 = 370%, the largest fractional tuning range in such resonators to date. This remarkable electromechanical resonance tuning is investigated by two different analytical models and finite element simulations. Further, we carefully perform clear control experiments and simulations to elucidate the difference in frequency tuning between heterostructure and single-material resonators. At a given initial strain level, the tuning range depends on the two-dimensional (2D) Young's moduli of the constitutive crystals; devices built on materials with lower 2D moduli show wider tuning ranges. This study exemplifies that vdW heterostructure resonators can retain unconventionally broad, continuous tuning, which is promising for voltage-controlled, tunable nanosystems.

cond-mat.mes-hall↗

arXiv2021

Very High Interfacial Thermal Conductance in Fully hBN-Encapsulated MoS2 van der Waals Heterostructure

We report experimental and computational studies of thermal transport properties in hexagonal boron nitride (hBN) encapsulated molybdenum disulfide (MoS2) structure using refined optothermal Raman techniques, and reveal very high interfacial thermal conductance between hBN and MoS2. By studying the Raman shift of hBN and MoS2 in suspended and substrate-supported thin films under varying laser power and temperature, we calibrate lateral (in-plane) thermal conductivity of hBN and MoS2 and the vertical interfacial thermal conductance in the hBN/MoS2/hBN heterostructure as well as the interfaces between heterostructure and substrate. Crucially, we have found that interfacial thermal conductance between hBN and encapsulated MoS2 is 74MW/m2K and 72MW/m2K in supported and suspended films, respectively, which are significantly higher than interfacial thermal conductance between MoS2 and other substrates. Molecular dynamics (MD) computations conducted in parallel have shown consistent results. This work provides clear evidence of significantly efficient heat dissipation in hBN/MoS2/hBN heterostructures and sheds light on building novel hBN encapsulated nanoelectronics with efficient thermal management.

cond-mat.mes-hall↗

arXiv2020

Online Detection of Low-Quality Synchrophasor Data Considering Frequency Similarity

This letter proposes a new approach for online detection of low-quality synchrophasor data under both normal and event conditions. The proposed approach utilizes the features of synchrophasor data in time and frequency domains to distinguish multiple regional PMU signals and detect low-quality synchrophasor data. The proposed approach does not require any offline study and it is more effective to detect low-quality data with apparently indistinguishable profiles. Case studies from recorded synchrophasor measurements verify the effectiveness of the proposed approach.

eess.SY↗

arXiv2020

Sutured instanton homology and Heegaard diagrams

Suppose H is an admissible Heegaard diagram for a balanced sutured manifold (M,γ). We prove that the number of generators of the associated sutured Heegaard Floer complex is an upper bound on the dimension of the sutured instanton homology of (M,γ). It follows, in particular, that strong L-spaces are instanton L-spaces.

math.GT↗

arXiv2020

GFTE: Graph-based Financial Table Extraction

Tabular data is a crucial form of information expression, which can organize data in a standard structure for easy information retrieval and comparison. However, in financial industry and many other fields tables are often disclosed in unstructured digital files, e.g. Portable Document Format (PDF) and images, which are difficult to be extracted directly. In this paper, to facilitate deep learning based table extraction from unstructured digital files, we publish a standard Chinese dataset named FinTab, which contains more than 1,600 financial tables of diverse kinds and their corresponding structure representation in JSON. In addition, we propose a novel graph-based convolutional neural network model named GFTE as a baseline for future comparison. GFTE integrates image feature, position feature and textual feature together for precise edge prediction and reaches overall good results.

cs.CV↗

arXiv2017

Atomic Layer MoS2-Graphene van der Waals Heterostructure Nanomechanical Resonators

Heterostructures play significant roles in modern semiconductor devices and micro/nanosystems in a plethora of applications in electronics, optoelectronics, and transducers. While state-of-the-art heterostructures often involve stacks of crystalline epi-layers each down to a few nanometers thick, the intriguing limit would be heterto-atomic-layer structures. Here we report the first experimental demonstration of freestanding van der Waals heterostructures and their functional nanomechanical devices. By stacking single-layer (1L) MoS2 on top of suspended single-, bi-, tri- and four-layer (1L to 4L) graphene sheets, we realize array of MoS2-graphene heterostructures with varying thickness and size. These heterostructures all exhibit robust nanomechanical resonances in the very high frequency (VHF) band (up to ~100 MHz). We observe that fundamental-mode resonance frequencies of the heterostructure devices fall between the values of graphene and MoS2 devices. Quality (Q) factors of heterostructure resonators are lower than those of graphene but comparable to those of MoS2 devices, suggesting interface damping related to interlayer interactions in the van der Waals heterostructures. This study validates suspended atomic layer heterostructures as an effective device platform and opens opportunities for exploiting mechanically coupled effects and interlayer interactions in such devices.

cond-mat.mes-hall↗

arXiv2017

A simple Python code for computing effective properties of 2D and 3D representative volume element under periodic boundary conditions

Multiscale optimization is an attractive research field recently. For the most of optimization tools, design parameters should be updated during a close loop. Therefore, a simple Python code is programmed to obtain effective properties of Representative Volume Element (RVE) under Periodic Boundary Conditions (PBCs). It can compute the mechanical properties of a composite with a periodic structure, in two or three dimensions. The computation method is based on the Asymptotic Homogenization Theory (AHT). With simple modifications, the basic Python code may be extended to the computation of the effective properties of more complex microstructure. Moreover, the code provides a convenient platform upon the optimization for the material and geometric composite design. The user may experiment with various algorithms and tackle a wide range of problems. To verify the effectiveness and reliability of the code, a three-dimensional case is employed to illuminate the code. Finally numerical results obtained by the code agree well with the available theoretical and experimental results

cs.CE↗

arXiv2016

Solving the Dual Problems of Dynamic Programs via Regression

In recent years, information relaxation and duality in dynamic programs have been studied extensively, and the resulted primal-dual approach has become a powerful procedure in solving dynamic programs by providing lower-upper bounds on the optimal value function. Theoretically, with the so called value-based optimal dual penalty, the optimal value function could be recovered exactly via strong duality. However, in practice, obtaining tight dual bounds usually requires good approximations of the optimal dual penalty, which could be time-consuming due to the conditional expectations that need to be estimated via nested simulation. In this paper, we will develop a framework of regression approach to approximating the optimal dual penalty in a non-nested manner, by exploring the structure of the function space consisting of all feasible dual penalties. The resulted approximations maintain to be feasible dual penalties, and thus yield valid dual bounds on the optimal value function. We show that the proposed framework is computationally efficient, and the resulted dual penalties lead to numerically tractable dual problems. Finally, we apply the framework to a high-dimensional dynamic trading problem to demonstrate its effectiveness in solving the dual problems of complex dynamic programs.

math.OC↗

arXiv2016

Environmental Instability and Degradation of Single- and Few-Layer WTe2 Nanosheets in Ambient Conditions

Since the discovery of large, non-saturating magnetoresistance in bulk WTe2 which allows microexfoliation, single- and few-layer WTe2 crystals have attracted increasing interests. However, as it mentioned in existing studies, WTe2 flakes appear to degrade in ambient conditions. Here we report experimental observations of saturating degradation in few-layer WTe2 through Raman spectroscopy characterization and careful monitoring of the degradation of single-, bi- and tri-layer (1L, 2L & 3L) WTe2 over long time. Raman peak intensity decreases during WTe2 degradation and 1L flakes degrade faster than 2L and 3L flakes. The relatively faster degradation in 1L WTe2 could be attributed to low energy barrier of oxygen reaction with WTe2. We further investigate the degradation mechanisms of WTe2 using XPS and AES and find that oxidation of Te and W atoms is the main reason of WTe2 degradation. In addition, we observe oxidation occurs only in the depth of 0.5nm near the surface, and the oxidized WTe2 surface could help prevent inner layers from further degradation.

cond-mat.mes-hall↗