arXiv subjects

Xia Hong

Publications and source records attributed to Xia Hong.

33 records · Page 2Linked to original sources

arXiv2021

Giant Transport Anisotropy in ReS$_2$ Revealed via Nanoscale Conducting Path Control

The low in-plane symmetry in layered 1T'-ReS$_2$ results in strong band anisotropy, while its manifestation in the electronic properties is challenging to resolve due to the lack of effective approaches for controlling the local current path. In this work, we reveal the giant transport anisotropy in monolayer to four-layer ReS$_2$ by creating directional conducting paths via nanoscale ferroelectric control. By reversing the polarization of a ferroelectric polymer top layer, we induce conductivity switching ratio of >1.5x10$^8$ in the ReS$_2$ channel at 300 K. Characterizing the domain-defined conducting nanowires in an insulating background shows that the conductivity ratio between the directions along and perpendicular to the Re-chain can exceed 5.5x10$^4$. Theoretical modeling points to the band origin of the transport anomaly, and further reveals the emergence of a flat band in few-layer ReS$_2$. Our work paves the path for implementing the highly anisotropic 2D materials for designing novel collective phenomena and electron lensing applications.

cond-mat.mes-hall↗

arXiv2020

Process monitoring based on orthogonal locality preserving projection with maximum likelihood estimation

By integrating two powerful methods of density reduction and intrinsic dimensionality estimation, a new data-driven method, referred to as OLPP-MLE (orthogonal locality preserving projection-maximum likelihood estimation), is introduced for process monitoring. OLPP is utilized for dimensionality reduction, which provides better locality preserving power than locality preserving projection. Then, the MLE is adopted to estimate intrinsic dimensionality of OLPP. Within the proposed OLPP-MLE, two new static measures for fault detection $T_{\scriptscriptstyle {OLPP}}^2$ and ${\rm SPE}_{\scriptscriptstyle {OLPP}}$ are defined. In order to reduce algorithm complexity and ignore data distribution, kernel density estimation is employed to compute thresholds for fault diagnosis. The effectiveness of the proposed method is demonstrated by three case studies.

stat.ME↗

arXiv2020

An improved mixture of probabilistic PCA for nonlinear data-driven process monitoring

An improved mixture of probabilistic principal component analysis (PPCA) has been introduced for nonlinear data-driven process monitoring in this paper. To realize this purpose, the technique of a mixture of probabilistic principal component analysers is utilized to establish the model of the underlying nonlinear process with local PPCA models, where a novel composite monitoring statistic is proposed based on the integration of two monitoring statistics in modified PPCA-based fault detection approach. Besides, the weighted mean of the monitoring statistics aforementioned is utilised as a metrics to detect potential abnormalities. The virtues of the proposed algorithm have been discussed in comparison with several unsupervised algorithms. Finally, Tennessee Eastman process and an autosuspension model are employed to demonstrate the effectiveness of the proposed scheme further.

stat.ME↗

arXiv2020

Polar Coupling Enabled Nonlinear Optical Filtering at MoS$_2$/Ferroelectric Heterointerfaces

Complex oxide heterointerfaces and van der Waals heterostructures present two versatile but intrinsically different platforms for exploring emergent quantum phenomena and designing new functionalities. The rich opportunity offered by the synergy between these two classes of materials, however, is yet to be charted. Here, we report an unconventional nonlinear optical filtering effect resulting from the interfacial polar alignment between monolayer MoS$_2$ and a neighboring ferroelectric oxide thin film. The second harmonic generation response at the heterointerface is either substantially enhanced or almost entirely quenched by an underlying ferroelectric domain wall depending on its chirality, and can be further tailored by the polar domains. Unlike the extensively studied coupling mechanisms driven by charge, spin, and lattice, the interfacial tailoring effect is solely mediated by the polar symmetry, as well explained via our density functional theory calculations, pointing to a new material strategy for the functional design of nanoscale reconfigurable optical applications.

cond-mat.mes-hall↗

arXiv2019

Coupling Matrix Manifolds and Their Applications in Optimal Transport

Optimal transport (OT) is a powerful tool for measuring the distance between two defined probability distributions. In this paper, we develop a new manifold named the coupling matrix manifold (CMM), where each point on CMM can be regarded as the transportation plan of the OT problem. We firstly explore the Riemannian geometry of CMM with the metric expressed by the Fisher information. These geometrical features of CMM have paved the way for developing numerical Riemannian optimization algorithms such as Riemannian gradient descent and Riemannian trust-region algorithms, forming a uniform optimization method for all types of OT problems. The proposed method is then applied to solve several OT problems studied by previous literature. The results of the numerical experiments illustrate that the optimization algorithms that are based on the method proposed in this paper are comparable to the classic ones, for example, the Sinkhorn algorithm, while outperforming other state-of-the-art algorithms without considering the geometry information, especially in the case of non-entropy optimal transport.

cs.LG↗

arXiv2019

Sparse Least Squares Low Rank Kernel Machines

A general framework of least squares support vector machine with low rank kernels, referred to as LR-LSSVM, is introduced in this paper. The special structure of low rank kernels with a controlled model size brings sparsity as well as computational efficiency to the proposed model. Meanwhile, a two-step optimization algorithm with three different criteria is proposed and various experiments are carried out using the example of the so-call robust RBF kernel to validate the model. The experiment results show that the performance of the proposed algorithm is comparable or superior to several existing kernel machines.

cs.LG↗

arXiv2017

Clogging of soft particles in 2D hoppers

Using experiments and simulations, we study the flow of soft particles through quasi-two-dimensional hoppers. The first experiment uses oil-in-water emulsion droplets in a thin sample chamber. Due to surfactants coating the droplets, they easily slide past each other, approximating soft frictionless disks. For these droplets, clogging at the hopper exit requires a narrow hopper opening only slightly larger than the droplet diameter. The second experiments use soft hydrogel particles in a thin sample chamber, where we vary gravity by changing the tilt angle of the chamber. For reduced gravity, clogging becomes easier, and can occur for larger hopper openings. Our simulations mimic the emulsion experiments and demonstrate that softness is a key factor controlling clogging: with stiffer particles or a weaker gravitational force, clogging is easier. The fractional amount a single particle is deformed under its own weight is a useful parameter measuring particle softness. Data from the simulation and hydrogel experiments collapse when compared using this parameter. Our results suggest that prior studies using hard particles were in a limit where the role of softness is negligible which causes clogging to occur with significantly larger openings.

cond-mat.soft↗

arXiv2017

Ferroelectric Domain Patterning Controlled Schottky Junction State in Monolayer MoS$_2$

We exploit scanning probe controlled domain patterning in a ferroelectric top layer to induce nonvolatile modulation of the conduction characteristic of monolayer MoS$_2$ between a transistor and a junction state. In the presence of a domain wall, MoS$_2$ exhibits rectified I-V that is well described by the thermionic emission model. The induced Schottky barrier height varies from 0.38 eV to 0.57 eV and is tunabe by a SiO$_2$ global back-gate, while the tuning range of depends sensitively on the conduction band tail trapping states. Our work points to a new route to achieving programmable functionalities in van der Waals materials and sheds light on the critical performance limiting factors in these hybrid systems.

cond-mat.mes-hall↗

arXiv2017

Ferroelectric metal-oxide-semiconductor capacitors using ultrathin single crystalline SrZrxTi1-xO3

The epitaxial growth of multifunctional oxides on semiconductors has opened a pathway to introduce new functionalities to semiconductor device technologies. In particular, ferroelectric materials integrated on semiconductors could lead to low-power field-effect devices that can be used for logic and memory. Essential to realizing such field-effect devices is the development of ferroelectric metal-oxide-semiconductor (MOS) capacitors, in which the polarization of a ferroelectric gate is coupled to the surface potential of a semiconducting channel. Here we demonstrate that ferroelectric MOS capacitors can be realized using single crystalline SrZrxTi1-xO3 (x = 0.7) that has been epitaxially grown on Ge. We find that the ferroelectric properties of SrZrxTi1-xO3 are exceptionally robust, as gate layers as thin as 5 nm corresponding to an equivalent-oxide-thickness of just 1.0 nm exhibit a ~ 2 V hysteretic window in the capacitance-voltage characteristics. The development of ferroelectric MOS capacitors with nanoscale gate thicknesses opens new vistas for nanoelectronic devices.

cond-mat.mtrl-sci↗

arXiv2017

Enhanced Piezoelectric Response in Hybrid Lead Halide Perovskite Thin Films via Interfacing with Ferroelectric PbZr$_{0.2}$Ti$_{0.8}$O$_3$

We report a more than 10-fold enhancement of the piezoelectric coefficient $d_{33}$ of polycrystalline CH$_3$NH$_3$PbI$_3$ (MAPbI$_3$) films when interfacing them with ferroelectric PbZr$_{0.2}$Ti$_{0.8}$O$_3$ (PZT). Piezo-response force microscopy (PFM) studies reveal $d_{33}^{MAPbI_3}$ values of ~0.3 pm/V for MAPbI$_3$ deposited on Au and ITO surfaces, with small phase angles fluctuating at length scales smaller than the grain size. In sharp contrast, on samples prepared on epitaxial PZT films, we observe large scale polar domains exhibiting clear, close to 90° PFM phase angles, pointing to polar axes along the film normal. By separating the contributions from the MAPbI$_3$ and PZT layers, we extract a significantly enhanced $d_{33}^{MAPbI_3}$ value of ~4 pm/V, which is attributed to the long-range dipole-dipole interaction facilitated domain nucleation. We also discuss the effect of the interfacial screening layer on the preferred polar direction.

cond-mat.mtrl-sci↗

arXiv2015

l1-norm Penalized Orthogonal Forward Regression

A l1-norm penalized orthogonal forward regression (l1-POFR) algorithm is proposed based on the concept of leaveone- out mean square error (LOOMSE). Firstly, a new l1-norm penalized cost function is defined in the constructed orthogonal space, and each orthogonal basis is associated with an individually tunable regularization parameter. Secondly, due to orthogonal computation, the LOOMSE can be analytically computed without actually splitting the data set, and moreover a closed form of the optimal regularization parameter in terms of minimal LOOMSE is derived. Thirdly, a lower bound for regularization parameters is proposed, which can be used for robust LOOMSE estimation by adaptively detecting and removing regressors to an inactive set so that the computational cost of the algorithm is significantly reduced. Illustrative examples are included to demonstrate the effectiveness of this new l1-POFR approach.

cs.LG↗

arXiv2015

Low Rank Representation on Riemannian Manifold of Square Root Densities

In this paper, we present a novel low rank representation (LRR) algorithm for data lying on the manifold of square root densities. Unlike traditional LRR methods which rely on the assumption that the data points are vectors in the Euclidean space, our new algorithm is designed to incorporate the intrinsic geometric structure and geodesic distance of the manifold. Experiments on several computer vision datasets showcase its noise robustness and superior performance on classification and subspace clustering compared to other state-of-the-art approaches.

cs.CV↗

arXiv2015

Heterogeneous Tensor Decomposition for Clustering via Manifold Optimization

Tensors or multiarray data are generalizations of matrices. Tensor clustering has become a very important research topic due to the intrinsically rich structures in real-world multiarray datasets. Subspace clustering based on vectorizing multiarray data has been extensively researched. However, vectorization of tensorial data does not exploit complete structure information. In this paper, we propose a subspace clustering algorithm without adopting any vectorization process. Our approach is based on a novel heterogeneous Tucker decomposition model. In contrast to existing techniques, we propose a new clustering algorithm that alternates between different modes of the proposed heterogeneous tensor model. All but the last mode have closed-form updates. Updating the last mode reduces to optimizing over the so-called multinomial manifold, for which we investigate second order Riemannian geometry and propose a trust-region algorithm. Numerical experiments show that our proposed algorithm compete effectively with state-of-the-art clustering algorithms that are based on tensor factorization.

cs.CV↗

arXiv2012

Thermal quench effects on ferroelectric domain walls

Using piezoresponse force microscopy on epitaxial ferroelectric thin films, we have measured the evolution of domain wall roughening as a result of heat-quench cycles up to 735C, with the effective roughness exponent ζ changing from 0.25 to 0.5. We discuss two possible mechanisms for the observed ζ increase: a quench from a thermal 1-dimensional configuration, and from a locally-equilibrated pinned configuration with a crossover from a 2- to 1-dimensional regime. We find that the post-quench spatial structure of the metastable states, qualitatively consistent with the existence of a growing dynamical length scale whose ultra slow evolution is primarily controlled by the defect configuration and heating process parameters, makes the second scenario more plausible. This interpretation suggests that pinning is relevant in a wide range of temperatures, and in particular, that purely thermal domain wall configurations might not be observable in this glassy system. We also demonstrate the crucial effects of oxygen vacancies in stabilizing domain structures.

cond-mat.dis-nn↗

arXiv2009

The Deposition of High-Quality HfO2 on Graphene and the Effect of Remote Oxide Phonon Scattering

We demonstrate the atomic layer deposition of high-quality HfO2 film on graphene and report the magnitude of remote oxide phonon (ROP) scattering in dual-oxide graphene transistors. Top gates with 30 nm HfO2 oxide layer exhibit excellent doping capacity of greater than 1.5x10^(13)/cm^(2). The carrier mobility in HfO2-covered graphene reaches 20,000 cm^(2)/Vs at low temperature, which is the highest among oxide-covered graphene and compares to that of pristine samples. The temperature-dependent resistivity exhibits the effect of ROP scattering from both the SiO2 substrate and the HfO2 over-layer. At room temperature, surface phonon modes of the HfO2 film centered at 54 meV dominate and limit the carrier mobility to ~20,000 cm^(2)/Vs. Our results highlight the important choice of oxide in graphene devices.

cond-mat.mtrl-sci↗