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Jing Wu

Publications and source records attributed to Jing Wu.

At least 145 records · Page 8Linked to original sources
arXiv2023

Direct observation of two-dimensional small polarons at correlated oxide interface

Two-dimensional (2D) perovskite oxide interfaces are ideal systems where diverse emergent properties can be uncovered.The formation and modification of polaronic properties due to short-range strong charge-lattice interactions of 2D interfaces remains hugely intriguing.Here, we report the direct observation of small-polarons at the LaAlO3/SrTiO3 (LAO/STO) conducting interface using high-resolution spectroscopic ellipsometry.First-principles investigations further reveals that strong coupling between the interfacial electrons and the Ti-lattice result in the formation of localized 2D small polarons.These findings resolve the longstanding issue where the excess experimentally measured interfacial carrier density is significantly lower than theoretically predicted values.The charge-phonon induced lattice distortion further provides an analogue to the superconductive states in magic-angle twisted bilayer graphene attributed to the many-body correlations induced by broken periodic lattice symmetry.Our study sheds light on the multifaceted complexity of broken periodic lattice induced quasi-particle effects and its relationship with superconductivity.

cond-mat.str-el↗
arXiv2023

Self-passivated freestanding superconducting oxide film for flexible electronics

The integration of high-temperature superconducting YBa2Cu3O6+x (YBCO) into flexible electronic devices has the potential to revolutionize the technology industry. The effective preparation of high-quality flexible YBCO films therefore plays a key role in this development. We present a novel approach for transferring water-sensitive YBCO films onto flexible substrates without any buffer layer. Freestanding YBCO film on a polydimethylsiloxane substrate is extracted by etching the Sr3Al2O6 sacrificial layer from the LaAlO3 substrate. In addition to the obtained freestanding YBCO thin film having a Tc of 89.1 K, the freestanding YBCO thin films under inward and outward bending conditions have Tc of 89.6 K and 88.9 K, respectively. A comprehensive characterization involving multiple experimental techniques including high-resolution transmission electron microscopy, scanning electron microscopy, Raman and X-ray Absorption Spectroscopy is conducted to investigate the morphology, structural and electronic properties of the YBCO film before and after the extraction process where it shows the preservation of the structural and superconductive properties of the freestanding YBCO virtually in its pristine state. Further investigation reveals the formation of a YBCO passivated layer serves as a protective layer which effectively preserves the inner section of the freestanding YBCO during the etching process. This work plays a key role in actualizing the fabrication of flexible oxide thin films and opens up new possibilities for a diverse range of device applications involving thin-films and low-dimensional materials.

cond-mat.supr-con↗
arXiv2023

Engineering Perovskite Emissions via Optical Quasi-Bound-States-in-the-Continuum

Metal halide perovskite quantum dots (PQDs) have emerged as promising materials due to their exceptional photoluminescence (PL) properties. A wide range of applications could benefit from adjustable luminescence properties, while preserving the physical and chemical properties of the PQDs. Therefore, post-synthesis engineering has gained attention recently, involving the use of ion-exchange or external stimuli, such as extreme pressure, magnetic and electric fields. Nevertheless, these methods typically suffer from spectrum broadening, intensity quenching or yield multiple bands. Alternatively, photonic antennas can modify the radiative decay channel of perovskites via the Purcell effect, with the largest wavelength shift being 8 nm to date, at an expense of 5-fold intensity loss. Here, we present an optical nanoantenna array with polarization-controlled quasi-bound-states-in-the-continuum (q-BIC) resonances, which can engineer and shift the photoluminescence wavelength over a ~39 nm range and confers a 21-fold emission enhancement of FAPbI3 perovskite QDs. The spectrum is engineered in a non-invasive manner via lithographically defined antennas and the pump laser polarization at ambient conditions. Our research provides a path towards advanced optoelectronic devices, such as spectrally tailored quantum emitters and lasers.

physics.optics↗
arXiv2023

Simultaneous Single Crystal Growth and Segregation of Ni-Rich Cathode Enabled by Nanoscale Phase Separation for Advanced Lithium-Ion Batteries

Synthesis of high-performance single crystal LiNi0.8Mn0.1Co0.1O2 (NMC811) in the absence of molten salt is challenging with no success yet. An innovative drop-in approach is discovered to synthesize single crystal NMC811 by controlling the morphology of transition metal hydroxide TM(OH)2 precursors followed by a simple decomposition step to form transition metal oxide (TMO) intermediates. Ni redistribution in TMO, as a result of the concurrent formation of mixed spinel and rock salt phases, helps deagglomerate the later formed NMC811 clusters of single crystals. As-prepared single crystal NMC811 is validated in a 2Ah pouch cell demonstrating 1000 stable cycling. The fundamentally new reaction mechanism of single crystal growth and segregation without molten salt provides a new direction towards cost-efficient manufacturing of single crystal NMC811 cathode for advanced lithium-based batteries.

cond-mat.mtrl-sci↗
arXiv2023

Exceptional domains in higher dimensions

We prove the existence of nontrivial unbounded exceptional domains in the Euclidean space $\R^N$, $N\geq4$. These domains arise as perturbations of complements of straight cylinders in $\R^N$, and by definition they support a positive harmonic function with vanishing Dirichlet boundary values and constant Neumann boundary values, the so-called roof function. While the domains have a similar shape as those constructed in the recent work \cite{Fall-MinlendI-Weth3} for the case $N=3$, there is a striking constrast with regard to the shape of corresponding roof functions which are bounded for $N \ge 4$. Moreover, while the analysis in \cite{Fall-MinlendI-Weth3} does not extend to higher dimensions, the approach of the present paper depends heavily on the assumption $N \ge 4$.

math.AP↗
arXiv2023

Ultrahigh oxygen ion mobility in ferroelectric hafnia

Ferroelectrics and ionic conductors are important functional materials, each supporting a plethora of applications in information and energy technology. The underlying physics governing their functional properties is ionic motion, and yet studies of ferroelectrics and ionic conductors are often considered separate fields. Based on first-principles calculations and deep-learning-assisted large-scale molecular dynamics (MD) simulations, we report ferroelectric-switching-promoted oxygen ion transport in HfO$_2$, a wide-band-gap insulator with both ferroelectricity and ionic conductivity. Applying a unidirectional bias can activate multiple switching pathways in ferroelectric HfO$_2$, leading to polar-antipolar phase cycling that appears to contradict classical electrodynamics. This apparent conflict is resolved by the geometric-quantum-phase nature of electric polarization that carries no definite direction. Our MD simulations demonstrate bias-driven successive ferroelectric transitions facilitate ultrahigh oxygen ion mobility at moderate temperatures, highlighting the potential of combining ferroelectricity and ionic conductivity for the development of advanced materials and technologies.

cond-mat.mtrl-sci↗
arXiv2023

Teleportation-based microwave-optical quantum transduction enhanced by squeezing

Quantum transduction is an important building block for quantum networking. Although various platforms have been proposed, the efficiency of the-state-of-the-art systems is still way below the threshold to provide robust quantum information transduction via a direct conversion approach. In [Phys. Rev. Applied 16, 064044 (2021)], we propose a transduction paradigm based on continuous-variable quantum teleportation that shows a much higher rate in the low cooperativitiy region. While more recently, [Phys. Rev. Research 4, L042013 (2022)] proposes to utilize microwave squeezing to assist direct conversion. In this work, we explore the role of squeezing in a teleportation-based transduction protocol and identify a significant performance boost via evaluating quantum capacity lower and upper bounds. Our analyses include both microwave squeezing and optical squeezing, and provide a systematical benchmark between the teleportation-based approach and direct conversion approach. Although with the help of large squeezing, the difference between the teleportation-based protocol and direct conversion protocol becomes smaller, teleportation-based protocol still provides an overall better performance in the practical cooperativity region. In particular, the teleportation-based approach is more robust against imperfect extraction efficiency, even compared with direct conversion with the optimal squeezing.

quant-ph↗
arXiv2023

Overdetermined elliptic problems in nontrivial contractible domains of the sphere

In this paper, we prove the existence of nontrivial contractible domains $Ω\subset\mathbb{S}^{d}$, $d\geq2$, such that the overdetermined elliptic problem \begin{equation*} \begin{cases} -\varepsilonΔ_{g} u +u-u^{p}=0 &\mbox{in $Ω$, } u>0 &\mbox{in $Ω$, } u=0 &\mbox{on $\partialΩ$, } \partial_ν u=\mbox{constant} &\mbox{on $\partialΩ$, } \end{cases} \end{equation*} admits a positive solution. Here $Δ_{g}$ is the Laplace-Beltrami operator in the unit sphere $\mathbb{S}^{d}$ with respect to the canonical round metric $g$, $\varepsilon>0$ is a small real parameter and $1 1$ if $d=2$). These domains are perturbations of $\mathbb{S}^{d}\setminus D,$ where $D$ is a small geodesic ball. This shows in particular that Serrin's theorem for overdetermined problems in the Euclidean space cannot be generalized to the sphere even for contractible domains.

math.AP↗
arXiv2023

Sobolev inequalities in manifolds with nonnegative intermediate Ricci curvature

We prove Michael-Simon type Sobolev inequalities for $n$-dimensional submanifolds in $(n+m)$-dimensional Riemannian manifolds with nonnegative $k$-th intermediate Ricci curvature by using the Alexandrov-Bakelman-Pucci method. Here $k=\min(n-1,m-1)$. These inequalities extends Brendle's Michael-Simon type Sobolev inequalities on Riemannian manifolds with nonnegative sectional curvature (arXiv:2009.13717) and Dong-Lin-Lu's Michael-Simon type Sobolev inequalities on Riemannian manifolds with asymptotically nonnegative sectional curvature (arXiv:2203.14624) to the $k$-Ricci curvature setting. In particular, a simple application of these inequalities gives rise to some isoperimetric inequalities for minimal submanifolds in Riemannian manifolds.

math.DG↗
arXiv2023

Modular development of deep potential for complex solid solutions

The multicomponent oxide solid solution is a versatile platform to tune the delicate balance between competing spin, charge, orbital, and lattice degrees of freedom for materials design and discovery. The development of compositionally complex oxides with superior functional properties has been largely empirical and serendipitous, in part due to the exceedingly complex chemistry and structure of solid solutions that span a range of length scales. The classical molecular dynamics (MD), as a powerful statistical method to investigate materials properties over large spatial and temporal scales, often plays a secondary role in computer-aided materials discovery because of the limited availability and accuracy of classical force fields. Here, we introduce the strategy of ``modular developing deep potential" (ModDP) that enables a systematic development and improvement of deep neural network-based model potential, termed as deep potential, for complex solid solutions with minimum human intervention. The converged training database associated with an end-member material is treated as an independent module and is reused to train the deep potential of solid solutions via a concurrent learning procedure. We apply ModDP to obtain classical force fields of two technologically important solid solutions, Pb$_x$Sr$_{1-x}$TiO$_3$ and Hf$_x$Zr$_{1-x}$O$_2$. For both materials systems, a single model potential is capable of predicting various properties of solid solutions including temperature-driven and composition-driven phase transitions over a wide range of compositions. In particular, the deep potential of Pb$_x$Sr$_{1-x}$TiO$_3$ reproduces a few known topological textures such as polar vortex lattice and electric dipole waves in PbTiO$_3$/SrTiO$_3$ superlattices, paving the way for MD investigations on the dynamics of topological structures in response to external stimuli.

cond-mat.mtrl-sci↗
arXiv2023

Recent Advances of Deep Robotic Affordance Learning: A Reinforcement Learning Perspective

As a popular concept proposed in the field of psychology, affordance has been regarded as one of the important abilities that enable humans to understand and interact with the environment. Briefly, it captures the possibilities and effects of the actions of an agent applied to a specific object or, more generally, a part of the environment. This paper provides a short review of the recent developments of deep robotic affordance learning (DRAL), which aims to develop data-driven methods that use the concept of affordance to aid in robotic tasks. We first classify these papers from a reinforcement learning (RL) perspective, and draw connections between RL and affordances. The technical details of each category are discussed and their limitations identified. We further summarise them and identify future challenges from the aspects of observations, actions, affordance representation, data-collection and real-world deployment. A final remark is given at the end to propose a promising future direction of the RL-based affordance definition to include the predictions of arbitrary action consequences.

cs.RO↗
arXiv2023

Extended Agriculture-Vision: An Extension of a Large Aerial Image Dataset for Agricultural Pattern Analysis

A key challenge for much of the machine learning work on remote sensing and earth observation data is the difficulty in acquiring large amounts of accurately labeled data. This is particularly true for semantic segmentation tasks, which are much less common in the remote sensing domain because of the incredible difficulty in collecting precise, accurate, pixel-level annotations at scale. Recent efforts have addressed these challenges both through the creation of supervised datasets as well as the application of self-supervised methods. We continue these efforts on both fronts. First, we generate and release an improved version of the Agriculture-Vision dataset (Chiu et al., 2020b) to include raw, full-field imagery for greater experimental flexibility. Second, we extend this dataset with the release of 3600 large, high-resolution (10cm/pixel), full-field, red-green-blue and near-infrared images for pre-training. Third, we incorporate the Pixel-to-Propagation Module Xie et al. (2021b) originally built on the SimCLR framework into the framework of MoCo-V2 Chen et al.(2020b). Finally, we demonstrate the usefulness of this data by benchmarking different contrastive learning approaches on both downstream classification and semantic segmentation tasks. We explore both CNN and Swin Transformer Liu et al. (2021a) architectures within different frameworks based on MoCo-V2. Together, these approaches enable us to better detect key agricultural patterns of interest across a field from aerial imagery so that farmers may be alerted to problematic areas in a timely fashion to inform their management decisions. Furthermore, the release of these datasets will support numerous avenues of research for computer vision in remote sensing for agriculture.

cs.CV↗
arXiv2023

Re-recognition of the ideal gas and real gas

Ideal gas is the most fundamental and simple system in thermodynamics, which has extensive applications in energy research and engineering. By reviewing the physical concept of ideal gas, it is found that the current understanding of ideal gas is still inappropriate and ambiguous, making it challenging to reveal the essential difference between ideal and real gases. Therefore, the macro and microscopic definitions and properties of ideal gas need to be reconceptualized. On the microscopic level, an ideal gas is a hypothetical collection of classical masses in irregular motion, which does not involve quantum mechanics; on the macroscopic level, any real gas cannot strictly obey the equation of state of ideal gas. Moreover, the heat capacity is a constant which should be an endogenous attribute of ideal gas model in order to unify the macroscopic and microscopic definitions of ideal gas. Finally, according to the law of heat capacity, the real gas can be divided into three categories: far-ideal, near-ideal, and quasi-ideal. This makes it easier to perform thermodynamic calculations with the assistance of ideal gas. Among them, the far-ideal gas heat capacity is a function of temperature and pressure, the near-ideal gas heat capacity is a single-valued function of temperature, and the quasi-ideal gas heat capacity is a constant.

physics.class-ph↗
arXiv2023

Optimizing Crop Management with Reinforcement Learning and Imitation Learning

Crop management, including nitrogen (N) fertilization and irrigation management, has a significant impact on the crop yield, economic profit, and the environment. Although management guidelines exist, it is challenging to find the optimal management practices given a specific planting environment and a crop. Previous work used reinforcement learning (RL) and crop simulators to solve the problem, but the trained policies either have limited performance or are not deployable in the real world. In this paper, we present an intelligent crop management system which optimizes the N fertilization and irrigation simultaneously via RL, imitation learning (IL), and crop simulations using the Decision Support System for Agrotechnology Transfer (DSSAT). We first use deep RL, in particular, deep Q-network, to train management policies that require all state information from the simulator as observations (denoted as full observation). We then invoke IL to train management policies that only need a limited amount of state information that can be readily obtained in the real world (denoted as partial observation) by mimicking the actions of the previously RL-trained policies under full observation. We conduct experiments on a case study using maize in Florida and compare trained policies with a maize management guideline in simulations. Our trained policies under both full and partial observations achieve better outcomes, resulting in a higher profit or a similar profit with a smaller environmental impact. Moreover, the partial-observation management policies are directly deployable in the real world as they use readily available information.

cs.AI↗
arXiv2023

Active Learning in Brain Tumor Segmentation with Uncertainty Sampling, Annotation Redundancy Restriction, and Data Initialization

Deep learning models have demonstrated great potential in medical 3D imaging, but their development is limited by the expensive, large volume of annotated data required. Active learning (AL) addresses this by training a model on a subset of the most informative data samples without compromising performance. We compared different AL strategies and propose a framework that minimizes the amount of data needed for state-of-the-art performance. 638 multi-institutional brain tumor MRI images were used to train a 3D U-net model and compare AL strategies. We investigated uncertainty sampling, annotation redundancy restriction, and initial dataset selection techniques. Uncertainty estimation techniques including Bayesian estimation with dropout, bootstrapping, and margins sampling were compared to random query. Strategies to avoid annotation redundancy by removing similar images within the to-be-annotated subset were considered as well. We determined the minimum amount of data necessary to achieve similar performance to the model trained on the full dataset (α = 0.1). A variance-based selection strategy using radiomics to identify the initial training dataset is also proposed. Bayesian approximation with dropout at training and testing showed similar results to that of the full data model with less than 20% of the training data (p=0.293) compared to random query achieving similar performance at 56.5% of the training data (p=0.814). Annotation redundancy restriction techniques achieved state-of-the-art performance at approximately 40%-50% of the training data. Radiomics dataset initialization had higher Dice with initial dataset sizes of 20 and 80 images, but improvements were not significant. In conclusion, we investigated various AL strategies with dropout uncertainty estimation achieving state-of-the-art performance with the least annotated data.

cs.CV↗
arXiv2022

Orbital hybridization-driven charge density wave transition in CsV3Sb5 kagome superconductor

Owing to its inherent non-trivial geometry, the unique structural motif of the recently discovered Kagome topological superconductor AV3Sb5 is an ideal host of diverse topologically non-trivial phenomena, including giant anomalous Hall conductivity, topological charge order, charge density wave, and unconventional superconductivity. Despite possessing a normal-state CDW order in the form of topological chiral charge order and diverse superconducting gaps structures, it remains unclear how fundamental atomic-level properties and many-body effects including Fermi surface nesting, electron-phonon coupling, and orbital hybridization contribute to these symmetry-breaking phenomena. Here, we report the direct participation of the V3d-Sb5p orbital hybridization in mediating the CDW phase transition in CsV3Sb5. The combination of temperature-dependent X-ray absorption and first principles studies clearly indicate the Inverse Star of David structure as the preferred reconstruction in the low-temperature CDW phase. Our results highlight the critical role that Sb orbitals plays and establish orbital hybridization as the direct mediator of the CDW states and structural transition dynamics in Kagome unconventional superconductors. This is a significant step towards the fundamental understanding and control of the emerging correlated phases from the Kagome lattice through the orbital interactions and provide promising approaches to novel regimes in unconventional orders and topology.

cond-mat.supr-con↗
arXiv2022

Two-Dimensional Charge Localization at the Perovskite Oxide Interface

The effects of atomic-scale disorder and charge (de)localization holds significant importance,and they provide essential insights in unravelling the role that strong and weak correlations play in condensed matter systems.For perovskite oxide heterostructures,while disorders introduced via various external stimuli have strong influences on the (de)localization of the interfacial two-dimensional (2D) electrons, these factors alone could not fully account for the system's charge dynamics where interfacial hybridization holds very strong influence.Here, we determine that the displaced 2D free electrons are localized in the specific hybridized states at the LaAlO3/SrTiO3(LAO/STO) interface.This experimental study combines both transport measurements and temperature-dependent X-ray absorption spectroscopy and suggests the localization of 2D electrons can be induced via temperature reduction or ionic liquid gating and it applies to both amorphous and crystalline interfacial systems.Specifically, we demonstrate that interfacial hybridization plays a pivotal role in regulating the 2D electron localization effects.Our study resolves the location where the 2D electrons are localized and highlights the importance of interfacial hybridization and opens further scientific investigation of its influence on 2D charge localization in oxide heterointerfaces.

cond-mat.str-el↗
arXiv2022

Quadrupole Topological Insulator in Non-Hermitian Thermal Diffusion

Quantized bulk quadrupole moment has unveiled a nontrivial boundary state, exhibiting lower-dimensional topological edge states and simultaneously hosting the in-gap corner modes of zero dimension. All state-of-the-art strategies for topological thermal metamaterials have so far failed to observe such higher-order hierarchical features, since the absence of quantized bulk quadrupole moments in thermal diffusion fundamentally forbids the possible expansions of band topology, unlike its photonic counterpart. Here, we report a recipe of creating quantized bulk quadrupole moments in diffusion, and observe the quadrupole topological phases in non-Hermitian thermal systems. The experiments demonstrate that both the real- and imaginary-valued bands showcase the hierarchical hallmarks of bulk, gapped edge, and in-gap corner states, in stark contrast to the higher-order states only observed on real-valued bands in classic wave fields. Our findings open up unique possibilities for diffusive manipulations and establish an unexplored playground for multipolar topological physics.

cond-mat.mes-hall↗