arXiv subjects

Zhuang Qian

Publications and source records attributed to Zhuang Qian.

At least 19 recordsLinked to original sources

arXiv2026

Emergent Interfacial Magnetism in Epitaxial RuO$_2$

The magnetic ground state of the altermagnet candidate RuO$_2$ remains controversial, with magnetic signatures observed mainly in epitaxial films. Here we show, using first-principles calculations, that magnetism in epitaxial RuO$_2$ can emerge as an interfacial boundary phase at TiO$_2$/RuO$_2$ interfaces. While TiO$_2$-induced epitaxial strain alone does not make (001)-oriented RuO$_2$ magnetic, explicit TiO$_2$/RuO$_2$ interfaces stabilize sizable Ru moments confined to the first few Ru layers. Charge-density and orbital-resolved analyses reveal interfacial electronic reconstruction, and substrate doping provides a route to tune the induced moments. In symmetric TiO$_2$/RuO$_2$/TiO$_2$ heterostructures, the two magnetic interfaces couple through the metallic RuO$_2$ spacer, producing a thickness-dependent alternation between weak-ferromagnetic and compensated altermagnetic states. Our results identify interface engineering as a practical route to stabilize and control fragile magnetism in RuO$_2$.

cond-mat.mtrl-sci↗

arXiv2026

Giant Nonlinear Photon-Drag Currents in Moiré Bilayers

The bulk photovoltaic effect provides a fundamental pathway for direct light-to-current conversion in quantum materials. However, these nonlinear currents are often strictly constrained or forbidden by crystal symmetries, hindering their exploration in a broader range of materials. While the nonlinear photon-drag effect leverages finite photon momentum to circumvent these constraints, its investigation has been largely confined to toy models, lacking a robust numerical framework for realistic materials. Here, we develop a unified microscopic theory of nonlinear photon-drag currents formulated within a geometric-loop framework, providing both a transparent quantum-geometric interpretation and numerical tractability. Applying this formalism to twisted bilayer graphene (TBG), we demonstrate that a finite, in-plane photon momentum can trigger massive nonlinear responses, rivaling the giant photovoltaic currents reported in typical 2D materials. These currents exhibit high tunability via photon wavevector, twist angle, and light polarization. Our work not only provides a generalized framework for momentum-dependent light-matter interactions but also establishes the nonlinear photon-drag effect as a potent mechanism for unlocking unprecedented optoelectronic functionalities beyond the limitations of the conventional bulk photovoltaic effect.

cond-mat.mes-hall↗

arXiv2026

Electrical Regulation of Transverse Spin Currents in Unconventional Magnetic Ferroeletrics

We identify hexagonal YMnO$_3$ as a material realization of the elusive $β$-phase of unconventional magnetism, a noncollinear, noncoplanar antiferromagnetic state defined by intrinsic spin-momentum locking and a topological spin texture. First-principle calculations reveal that this unique electronic structure enables a perpendicular electric field to generate a transverse pure spin current, a response that occurs without requiring relativistic spin-orbit coupling. Symmetry analysis demonstrates that this spin current is intimately related to the material's ferroelectric polarization that breaks the inversion symmetry and is rigorously forbidden at domain walls where electrical polarization vanishes. This provides a blueprint for a non-volatile transistor where a gate voltage switches the spin current conductivity by controlling domain wall density, enabling all-electrical control for energy-efficient antiferromagnetic spintronics.

cond-mat.mtrl-sci↗

arXiv2025

Fragile Unconventional Magnetism in RuO$_2$ by Proximity to Landau-Pomeranchuk Instability

Altermagnetism has attracted considerable attention for its remarkable combination of spin-polarized band structures and zero net magnetization, making it a promising candidate for spintronics applications. We demonstrate that this magnetic phase represents a case of ``unconventional magnetism," first proposed nearly two decades ago by one of the present authors as part of a broader framework for understanding Landau-Pomeranchuk instabilities in the spin channel, driven by many-body interactions. By systematically analyzing the altermagnetism in RuO$_2$ with first-principles calculations, we reconcile conflicting experimental and theoretical reports by attributing it to RuO$_2$'s proximity to a quantum phase transition. We emphasize the critical role of tuning parameters, such as the Hubbard $U$, hole doping, and epitaxial strain, in modulating quasiparticle interactions near the Fermi surface. This work provides fresh insights into the origin and tunability of altermagnetism in RuO$_2$, highlighting its potential as a platform for investigating quantum phase transitions and the broader realm of unconventional magnetism.

cond-mat.mtrl-sci↗

arXiv2024

Sliding-Reversible Bandgap Modulation in Irreversible Asymmetric Multilayers

The electronic bandgap of a material is often fixed after fabrication. The capability to realize on-demand and non-volatile control over the bandgap will unlock exciting opportunities for adaptive devices with enhanced functionalities and efficiency. We introduce a general design principle for on-demand and non-volatile control of bandgap values, which utilizes reversible sliding-induced polarization driven by an external electric field to modulate the irreversible background polarization in asymmetric two-dimensional (2D) multilayers. The structural asymmetry can be conveniently achieved in homobilayers of Janus monolayers and heterobilayers of nonpolar monolayers, making the design principle applicable to a broad range of 2D materials. We demonstrate the versatility of this design principle using experimentally synthesized Janus metal dichalcogenide (TMD) multilayers as examples. Our first-principles calculations show that the bandgap modulation can reach up to 0.3 eV and even support a semimetal-to-semiconductor transition. By integrating a ferroelectric monolayer represented by 1T$'''$-MoS$_2$ into a bilayer, we show that the combination of intrinsic ferroelectricity and sliding ferroelectricity leads to multi-bandgap systems coupled to multi-step polarization switching. The sliding-reversible bandgap modulation offers an avenue to dynamically adjust the optical, thermal, and electronic properties of 2D materials through mechanical and electrical stimuli.

cond-mat.mtrl-sci↗

arXiv2024

Adaptive sampling strategy for tolerance analysis of freeform optical surfaces based on critical ray aiming

The tolerance analysis of freeform surfaces plays a crucial role in the development of advanced imaging systems. However, the intricate relationship between surface error and imaging quality poses significant challenges, necessitating dense sampling of featured rays during the computation process to ensure an accurate tolerance for different fields of view (FOVs). Here, we propose an adaptive sampling strategy called "Critical Ray Aiming" for surface tolerance analysis. By identifying the most sensitive ray to wave aberration at each surface point, our methodology facilitates flexible sampling of the FOVs and entrance pupil (EP), achieving computational efficiency without compromising accuracy in determining tolerable surface error. We demonstrate the effectiveness of our method through tolerance analysis of two different freeform imaging systems.

physics.optics↗

arXiv2024

Large Bulk Photovoltaic Effect of Nitride Perovskite LaWN3 as Photocatalyst for Hydrogen Evolution Reaction: First Principles Calculation

Bulk photovoltaic effect in noncentrosymmetric materials is a fundamental and significant property that holds potential for high-efficiency energy harvesting, such as photoelectric application and photocatalysis. Here, based on first principles calculation, we explore the electronic structure, dielectric property, shift current, and photocatalytic performance of novel nitride perovskite LaWN3. Our calculations show that LaWN3 possesses large dielectric constants and shift current. The shift current can be enhanced by considering spin-orbit coupling and is switchable by ferroelectric polarization, which suggests LaWN3 is a promising candidate for logic and neuromorphic photovoltaic devices driven by ferroelectric polarization. Additionally, LaWN3 shows advanced photocatalytic hydrogen evolution reaction as a photocatalyst. Especially, the (110) surface represents low surface energy and Gibbes free energy, implying that the (110) surface may be exposed to the active surface. Our finding highlights potential applications of novel polar nitride perovskite LaWN3 in various fields not only photoelectric devices but also photocatalysis.

cond-mat.mtrl-sci↗

arXiv2024

Surface variation analysis of freeform optical systems over surface frequency bands for prescribed wavefront errors

The surface errors of freeform surfaces reflect the manufacturing complexities and significantly impact the feasibility of processing designed optical systems. With multiple degrees of freedom, freeform surfaces pose challenges in surface tolerance analysis in the field. Nevertheless, current research has neglected the influence of surface slopes on the directions of ray propagation. A sudden alteration in the surface slope will lead to a corresponding abrupt shift in the wavefront, even when the change in surface sag is minimal. Moreover, within the realm of freeform surface manufacturing, variation in surface slope across different frequency bands may give rise to unique surface variation. Within the context of this study, we propose a tolerance analysis method to analyze surface variation in freeform surfaces considering surface frequency band slopes based on real ray data. This approach utilizes real ray data to rapidly evaluate surface variation within a specified frequency band of surface slopes. Crucially, our proposed method yields the capability to obtain system surface variation with significant wavefront aberration, in contrast to previous methodologies. The feasibility and advantages of this framework are assessed by analyzing a single-mirror system with a single field and an off-axis two-mirror system. We expect to integrate the proposed methodology with freeform surface design and manufacturing, thereby expanding the scope of freeform optics.

physics.optics↗

arXiv2024

One-dimensional Multiferroic Semiconductor WOI3: Unconventional Anisotropic d^1 Rule and Bulk Photovoltaic Effect

The pursuit of multiferroic magnetoelectrics, combining simultaneous ferroelectric and magnetic orders, remains a central focus in condensed matter physics. Here we report the centrosymmetric, one-dimensional (1D) antiferromagnetic WOI$_3$ undergoes a strain-induced ferroelectric distortion. The paraelectric-ferroelectric transition is originated from the unconventional anisotropic $d^1$ mechanism, where an unpaired d electron of each W$^{5+}$ ion contributes to magnetic orders. Employing a Heisenberg model with Dzyaloshinskii-Moriya interaction, we predict an antiferromagnetic spin configuration as the paraelectric ground state, transitioning to a ferroelectric phase with noncollinear spin arrangement under uniaxial strain. The ferroelectric polarization and noncollinear spin arrangement can be manipulated by varying the applied strain. While the energy barriers for switching ferroelectric polarizations with magnetic orders are on the order of a few dozen of meV, the shift current bulk photovoltaic effect (BPVE) exhibits remarkable differences, providing a precise and valuable tool for experimentally probing the interplay of ferroelectric and magnetic orders in 1D WOI$_3$.

cond-mat.mtrl-sci↗

arXiv2023

Switchable band topology and geometric current in sliding bilayer elemental ferroelectric

We demonstrate that sliding motion between two layers of the newly discovered ferroelectric and topologically trivial bismuth (Bi) monolayer [Nature 617, 67 (2023)] can induce a sequence of topological phase transitions, alternating between trivial and nontrivial states. Interestingly, a lateral shift, even when preserving spatial symmetry, can still switch the quantum spin Hall state on and off. The substantial band-gap modulation and band inversion due to interlayer sliding arise primarily from the intralayer in-plane charge transfer processes involving Bi atoms at the outermost atomic layers, rather than the interlayer charge redistribution. We map out the topological phase diagram and the geometric Berry curvature-dipole induced nonlinear anomalous Hall response resulting from sliding, highlighting the potential for robust mechanical control over the edge current and the Hall current. Bilayer configurations that are $\mathbb{Z}_2$ nontrivial can produce drastically different transverse currents orthogonal to the external electric field. This occurs because both the direction and magnitude of the Berry curvature dipole at the Fermi level depend sensitively on the sliding displacement. Our results suggest that bilayer bismuth could serve as a platform to realize power-efficient ``Berry slidetronics" for topology memory applications.

physics.comp-ph↗

arXiv2023

Competing charge transfer and screening effects in two-dimensional ferroelectric capacitors

Two-dimensional (2D) ferroelectrics offer the potential for ultrathin flexible nanoelectronics, typically utilizing a metal-ferroelectric-metal sandwich structure as the functional unit. Electrodes can either contribute free carriers to screen the depolarization field, enhancing nanoscale ferroelectricity, or they can induce charge doping, disrupting the long-range crystalline order. Here, we explore the dual roles of electrodes in 2D ferroelectric capacitors, supported by extensive first-principles calculations covering a range of electrode work functions. Our results reveal volcano-type relationships between ferroelectric-electrode binding affinity and work function, which are further unified by a quadratic scaling between the binding energy and the transferred interfacial charge. At the monolayer limit, the charge transfer dictates the ferroelectric stability and switching properties. This is a general characteristic confirmed in various 2D ferroelectrics including $α$-In$_2$Se$_3$, CuInP$_2$S$_6$, and SnTe. As the ferroelectric layer's thickness increases, the stability of the capacitor evolves from a charge transfer-dominated to a screening-dominated state. The delicate interplay between these two effects will have important implications for the applications of 2D ferroelectric capacitors.

cond-mat.mtrl-sci↗

arXiv2023

Shift current response in elemental two-dimensional ferroelectrics

A bulk material without inversion symmetry can generate a direct current under illumination. This interface-free current generation mechanism, referred to as the bulk photovoltaic effect (BPVE), does not rely on $p$-$n$ junctions. Here, we explore the shift current generation, a major mechanism responsible for the BPVE, in single-element two-dimensional (2D) ferroelectrics represented by phosphorene-like monolayers of As, Sb, and Bi. The strong covalency, small band gap, and large joint density of states afforded by these elemental 2D materials give rise to large shift currents, outperforming many state-of-the-art materials. We find that the shift current, due to its topological nature, depends sensitively on the details of the Bloch wave functions. It is crucial to consider the electronic exchange-correlation potential beyond the generalized gradient approximation as well as the spin-orbit interaction in density functional theory calculations to obtain reliable frequency-dependent shift current responses.

cond-mat.mtrl-sci↗

arXiv2023

Semiconducting nonperovskite ferroelectric oxynitride designed ab initio

Recent discovery of HfO2-based and nitride-based ferroelectrics that are compatible to the semiconductor manufacturing process have revitalized the field of ferroelectric-based nanoelectronics. Guided by a simple design principle of charge compensation and density functional theory calculations, we discover HfO2-like mixed-anion materials, TaON and NbON, can crystallize in the polar Pca21 phase with a strong thermodynamic driving force to adopt anion ordering spontaneously. Both oxynitrides possess large remnant polarization, low switching barriers, and unconventional negative piezoelectric effect, making them promising piezoelectrics and ferroelectrics. Distinct from HfO2 that has a wide band gap, both TaON and NbON can absorb visible light and have high charge carrier mobilities, suitable for ferroelectric photovoltaic and photocatalytic applications. This new class of multifunctional nonperovskite oxynitride containing economical and environmentally benign elements offer a platform to design and optimize high-performing ferroelectric semiconductors for integrated systems.

cond-mat.mtrl-sci↗

arXiv2022

Improving Model Robustness with Latent Distribution Locally and Globally

In this work, we consider model robustness of deep neural networks against adversarial attacks from a global manifold perspective. Leveraging both the local and global latent information, we propose a novel adversarial training method through robust optimization, and a tractable way to generate Latent Manifold Adversarial Examples (LMAEs) via an adversarial game between a discriminator and a classifier. The proposed adversarial training with latent distribution (ATLD) method defends against adversarial attacks by crafting LMAEs with the latent manifold in an unsupervised manner. ATLD preserves the local and global information of latent manifold and promises improved robustness against adversarial attacks. To verify the effectiveness of our proposed method, we conduct extensive experiments over different datasets (e.g., CIFAR-10, CIFAR-100, SVHN) with different adversarial attacks (e.g., PGD, CW), and show that our method substantially outperforms the state-of-the-art (e.g., Feature Scattering) in adversarial robustness by a large accuracy margin. The source codes are available at https://github.com/LitterQ/ATLD-pytorch.

cs.LG↗

arXiv2022

Quenched Λ spin-orbit splitting by relativistic Fock diagram in single-Λ hypernuclei

We extend the relativistic Hartree-Fock (RHF) theory to study the structure of single-$Λ$ hypernuclei. The density dependence is taken in both meson-nucleon and meson-hyperon coupling strengths, and the induced $Λ$-nucleon ($ΛN$) effective interactions are determined by fitting $Λ$ separation energies to the experimental data for several single-$Λ$ hypernuclei. The equilibrium of nuclear dynamics described by the RHF model in normal atomic nuclei, namely, the balance between nuclear attractive and repulsive interactions, is then found to be drastically changed in single-$Λ$ hypernuclei, revealing a different role of Fock terms via $Λ$ hyperon from the nucleon exchange. Since only one hyperon exists in a single-$Λ$ hypernucleus, the overwhelmed $ΛN$ and $ΛΛ$ attractions via the Hartree than the $ΛΛ$ repulsion from the Fock terms require an alternation of meson-hyperon coupling strengths in RHF to rebalance the effective nuclear force with the strangeness degree of freedom, leading to an improved description of $Λ$ Dirac mass and correspondingly a systematically reduced $σ$-$Λ$ coupling strength $g_{σΛ}$ in current models as compared to those relativistic mean-field (RMF) approaches without Fock terms. As a result, the effective $Λ$ spin-orbit coupling potential in the ground state of hypernuclei is suppressed, and these RHF models predict correspondingly a quenching effect in $Λ$ spin-orbit splitting in comparison with the RMF cases. Furthermore, the $Λ$ spin-orbit splitting could decrease efficiently by evolving the hyperon-relevant couplings $g_{σΛ}$ and $g_{ωΛ}$ simultaneously, where to reconcile with the empirical value the RHF models address a larger parameter space of meson-hyperon couplings.

nucl-th↗

arXiv2022

A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies

In the last a few decades, deep neural networks have achieved remarkable success in machine learning, computer vision, and pattern recognition. Recent studies however show that neural networks (both shallow and deep) may be easily fooled by certain imperceptibly perturbed input samples called adversarial examples. Such security vulnerability has resulted in a large body of research in recent years because real-world threats could be introduced due to vast applications of neural networks. To address the robustness issue to adversarial examples particularly in pattern recognition, robust adversarial training has become one mainstream. Various ideas, methods, and applications have boomed in the field. Yet, a deep understanding of adversarial training including characteristics, interpretations, theories, and connections among different models has still remained elusive. In this paper, we present a comprehensive survey trying to offer a systematic and structured investigation on robust adversarial training in pattern recognition. We start with fundamentals including definition, notations, and properties of adversarial examples. We then introduce a unified theoretical framework for defending against adversarial samples - robust adversarial training with visualizations and interpretations on why adversarial training can lead to model robustness. Connections will be also established between adversarial training and other traditional learning theories. After that, we summarize, review, and discuss various methodologies with adversarial attack and defense/training algorithms in a structured way. Finally, we present analysis, outlook, and remarks of adversarial training.

cs.CV↗

arXiv2020

Robust Generative Adversarial Network

Generative adversarial networks (GANs) are powerful generative models, but usually suffer from instability and generalization problem which may lead to poor generations. Most existing works focus on stabilizing the training of the discriminator while ignoring the generalization properties. In this work, we aim to improve the generalization capability of GANs by promoting the local robustness within the small neighborhood of the training samples. We also prove that the robustness in small neighborhood of training sets can lead to better generalization. Particularly, we design a robust optimization framework where the generator and discriminator compete with each other in a \textit{worst-case} setting within a small Wasserstein ball. The generator tries to map \textit{the worst input distribution} (rather than a Gaussian distribution used in most GANs) to the real data distribution, while the discriminator attempts to distinguish the real and fake distribution \textit{with the worst perturbation}. We have proved that our robust method can obtain a tighter generalization upper bound than traditional GANs under mild assumptions, ensuring a theoretical superiority of RGAN over GANs. A series of experiments on CIFAR-10, STL-10 and CelebA datasets indicate that our proposed robust framework can improve on five baseline GAN models substantially and consistently.

cs.LG↗

arXiv2019

Generative Adversarial Classifier for Handwriting Characters Super-Resolution

Generative Adversarial Networks (GAN) receive great attentions recently due to its excellent performance in image generation, transformation, and super-resolution. However, GAN has rarely been studied and trained for classification, leading that the generated images may not be appropriate for classification. In this paper, we propose a novel Generative Adversarial Classifier (GAC) particularly for low-resolution Handwriting Character Recognition. Specifically, involving additionally a classifier in the training process of normal GANs, GAC is calibrated for learning suitable structures and restored characters images that benefits the classification. Experimental results show that our proposed method can achieve remarkable performance in handwriting characters 8x super-resolution, approximately 10% and 20% higher than the present state-of-the-art methods respectively on benchmark data CASIA-HWDB1.1 and MNIST.

cs.CV↗