Showing 1–50 of 135 results for author: Zhong, Z

Dual instability of superconductivity from oxygen defects in La$_3$Ni$_2$O$_{7+δ}$

Authors: Peiheng Jiang, Jie Li, Yu-Han Cao, Xiaodong Cao, Zhicheng Zhong, Yi Lu, Qiang-Hua Wang

Abstract: We uncover a dual mechanism by which oxygen defects suppress superconductivity in the bilayer nickelate La$_3$Ni$_2$O$_{7+δ}$ using density functional theory, dynamical mean-field theory, and functional renormalization group analysis. Apical vacancies and interbilayer interstitials emerge as the dominant low-energy defect species and are further stabilized by orthorhombic domain walls. These two d… ▽ More We uncover a dual mechanism by which oxygen defects suppress superconductivity in the bilayer nickelate La$_3$Ni$_2$O$_{7+δ}$ using density functional theory, dynamical mean-field theory, and functional renormalization group analysis. Apical vacancies and interbilayer interstitials emerge as the dominant low-energy defect species and are further stabilized by orthorhombic domain walls. These two defect classes drive the electronic structure in opposing directions. Vacancy-induced disorder generates local magnetic moments and promotes Anderson localization at moderate concentrations, whereas periodic interstitial ordering yields a coherent but weakly correlated metallic background that fails to support superconductivity. These findings highlight the decisive role of oxygen defects in shaping the superconducting and provide microscopic guidance for improving superconductivity through controlled defect engineering. △ Less

Submitted 28 November, 2025; originally announced December 2025.

Surface elasticity effect on Plateau-Rayleigh instability in soft solids

Authors: Pingping Zhu, Dun Li, Xiang Yu, Zheng Zhong

Abstract: Soft solids exhibit instability and develop surface undulations due to surface effects, a phenomenon known as the elastic Plateau-Rayleigh (PR) instability, driven by the interplay of surface and bulk elasticity. Previous studies on the PR instability in solids mainly focused on the case of constant surface tension and ignored the effect of surface elasticity. It has been shown by experiments that… ▽ More Soft solids exhibit instability and develop surface undulations due to surface effects, a phenomenon known as the elastic Plateau-Rayleigh (PR) instability, driven by the interplay of surface and bulk elasticity. Previous studies on the PR instability in solids mainly focused on the case of constant surface tension and ignored the effect of surface elasticity. It has been shown by experiments that the surface effects in solid-like materials depend both on the surface tension and surface elasticity, but little is known about the role of the latter in the elasto-capillary instabilities in soft solids. Here, we conduct an in-depth exploration of the effect of surface elasticity on the PR instability in an elastic cylinder by coupling theoretical and numerical methods. We derive an asymptotically consistent one-dimensional (1d) model to characterize the PR instability from three-dimensional (3d) nonlinear bulk-surface elasticity, and develop a new finite-element (FE) scheme for simulating 3d deformations of the bulk-surface system. The initiation and evolution of the PR instability are obtained analytically with the aid of the 1d model. The 1d results are further validated by the 3d FE simulations. By synthesizing the 1d analytic solutions and 3d numerical results, the effects of surface elasticity, surface compressibility, surface tension, axial force and geometrical size on the PR instability are thoroughly elucidated. Our results can be applied to calibrate surface parameters for solid-like materials and develop constitutive models for elastic surfaces. △ Less

Submitted 20 November, 2025; originally announced November 2025.

Comments: 33 pages, 10 figures

Neural network impurity solver for real-frequency dynamical mean-field theory

Authors: Fenglin Deng, Yi Lu, Xiaodong Cao, Zhicheng Zhong

Abstract: We introduce a neural network impurity solver for real-frequency DMFT that employs a multihead cross-attention mechanism to map hybridization functions to spectral functions, conditioned on impurity parameters. Trained on high-quality MPS data from complex contour time evolution and incorporating derivative constraints with respect to the complex-time angle, our model achieves smooth generalizatio… ▽ More We introduce a neural network impurity solver for real-frequency DMFT that employs a multihead cross-attention mechanism to map hybridization functions to spectral functions, conditioned on impurity parameters. Trained on high-quality MPS data from complex contour time evolution and incorporating derivative constraints with respect to the complex-time angle, our model achieves smooth generalization to the real-frequency axis. Benchmarking on the single-band Hubbard model for the Bethe lattice demonstrates quantitative accuracy across metallic, strongly correlated, and insulating regimes. △ Less

Submitted 18 November, 2025; originally announced November 2025.

Comments: 9 pages, 9 figures

Chemical-space completeness: a new strategy for crystalline materials exploration

Authors: Fengyu Xie, Ruoyu Wang, Taoyuze Lv, Yuxiang Gao, Hongyu Wu, Zhicheng Zhong

Abstract: The emergence of deep learning has brought the long-standing goal of comprehensively understanding and exploring crystalline materials closer to reality. Yet, universal exploration across all elements remains hindered by the combinatorial explosion of possible chemical environments, making it difficult to balance accuracy and efficiency. Crucially, within any finite set of elements, the diversity… ▽ More The emergence of deep learning has brought the long-standing goal of comprehensively understanding and exploring crystalline materials closer to reality. Yet, universal exploration across all elements remains hindered by the combinatorial explosion of possible chemical environments, making it difficult to balance accuracy and efficiency. Crucially, within any finite set of elements, the diversity of short-range bonding types and local geometric motifs is inherently limited. Guided by this chemical intuition, we propose a chemical-system-centric strategy for crystalline materials exploration. In this framework, generative models are coupled with machine-learned force fields as fast energy evaluators, and both are iteratively refined in a closed-loop cycle of generation, evaluation, and fine-tuning. Using the Li-P-S ternary system as a case study, we show that this approach captures the diversity of local environments with minimal additional first-principles data while maintaining structural creativity, achieving closed-loop convergence toward chemical completeness within a bounded chemical space. We further demonstrate downstream applications, including phase-diagram construction, ionic-diffusivity screening, and electronic-structure prediction. Together, this strategy provides a systematic and data-efficient framework for modeling both atomistic and electronic structures within defined chemical spaces, bridging accuracy and efficiency, and paving the way toward scalable, AI-driven discovery of crystalline materials with human-level creativity and first-principles fidelity. △ Less

Submitted 15 November, 2025; originally announced November 2025.

Comments: 23 pages, 7 figures

AtomWorld: A Benchmark for Evaluating Spatial Reasoning in Large Language Models on Crystalline Materials

Authors: Taoyuze Lv, Alexander Chen, Fengyu Xie, Chu Wu, Jeffrey Meng, Dongzhan Zhou, Bram Hoex, Zhicheng Zhong, Tong Xie

Abstract: Large Language Models (LLMs) excel at textual reasoning and are beginning to develop spatial understanding, prompting the question of whether these abilities can be combined for complex, domain-specific tasks. This question is essential in fields like materials science, where deep understanding of 3D atomic structures is fundamental. While initial studies have successfully applied LLMs to tasks in… ▽ More Large Language Models (LLMs) excel at textual reasoning and are beginning to develop spatial understanding, prompting the question of whether these abilities can be combined for complex, domain-specific tasks. This question is essential in fields like materials science, where deep understanding of 3D atomic structures is fundamental. While initial studies have successfully applied LLMs to tasks involving pure crystal generation or coordinate understandings, a standardized benchmark to systematically evaluate their core reasoning abilities across diverse atomic structures has been notably absent. To address this gap, we introduce the AtomWorld benchmark to evaluate LLMs on tasks based in Crystallographic Information Files (CIFs), a standard structure representation format. These tasks, including structural editing, CIF perception, and property-guided modeling, reveal a critical limitation: current models, despite establishing promising baselines, consistently fail in structural understanding and spatial reasoning. Our experiments show that these models make frequent errors on structure modification tasks, and even in the basic CIF format understandings, potentially leading to cumulative errors in subsequent analysis and materials insights. By defining these standardized tasks, AtomWorld lays the ground for advancing LLMs toward robust atomic-scale modeling, crucial for accelerating materials research and automating scientific workflows. △ Less

Submitted 7 October, 2025; v1 submitted 6 October, 2025; originally announced October 2025.

Intrinsic Strain-Driven Topological Evolution in SrRuO3 via Flexural Strain Engineering

Authors: Liguang Gong, Hongping Jiang, Bin Lao, Xuan Zheng, Xuejiao Chen, Zhicheng Zhong, Yan Sun, Xianfeng Hao, Milan Radovic, Run-Wei Li, Zhiming Wang

Abstract: Strain engineering offers a powerful route to tailor topological electronic structures in correlated oxides, yet conventional epitaxial strain approaches introduce extrinsic factors such as substrate-induced phase transitions and crystalline quality variations, which makes the unambiguous identification of the intrinsic strain effects challenging. Here, we develop a flexural strain platform based… ▽ More Strain engineering offers a powerful route to tailor topological electronic structures in correlated oxides, yet conventional epitaxial strain approaches introduce extrinsic factors such as substrate-induced phase transitions and crystalline quality variations, which makes the unambiguous identification of the intrinsic strain effects challenging. Here, we develop a flexural strain platform based on van der Waals epitaxy and flexible micro-fabrication, enabling precise isolation and quantification of intrinsic strain effects on topological electronic structures in correlated oxides without extrinsic interference. Through strain-dependent transport measurements of the Weyl semimetal SrRuO3, we observed a significant enhancement of anomalous Hall conductivity by 21% under a tiny strain level of 0.2%, while longitudinal resistivity remains almost constant -- a hallmark of intrinsic topological response. First-principles calculations reveal a distinct mechanism where strain-driven non-monotonic evolution of Weyl nodes across the Fermi level, exclusively governed by lattice constant modulation, drives the striking AHC behavior. Our work not only highlights the pivotal role of pure lattice strain in topological regulation but also establishes a universal platform for designing flexible topological oxide devices with tailored functionalities. △ Less

Submitted 22 August, 2025; originally announced August 2025.

Comments: 19 pages, 4 figures

Mechanism of Anisotropic Crystallization and Phase Transitions under Van der Waals Squeezing

Authors: Yuxiang Gao, Zhicheng Zhong

Abstract: Mechanical confinement strategies, such as van der Waals (vdW) squeezing, have emerged as promising routes for synthesizing non-vdW two-dimensional (2D) layers, surprisingly yielding high-quality single crystals with lateral sizes approaching 100 micrometer. However, the underlying mechanisms by which such a straightforward approach overcomes the long-standing synthesis challenges of non-vdW 2D ma… ▽ More Mechanical confinement strategies, such as van der Waals (vdW) squeezing, have emerged as promising routes for synthesizing non-vdW two-dimensional (2D) layers, surprisingly yielding high-quality single crystals with lateral sizes approaching 100 micrometer. However, the underlying mechanisms by which such a straightforward approach overcomes the long-standing synthesis challenges of non-vdW 2D materials remains a puzzle. Here, we investigate the crystallization dynamics and phase evolution of Bi under vdW confinement through molecular dynamics (MD) simulations powered by a machine-learning force filed fine-tuned and distilled from a pre-trained model with DFT-level accuracy. We reveal that pressure-dependent layer modulation arises from a quantum confinement-driven anisotropic crystallization mechanism, in which out-of-plane layering occurs nearly two orders of magnitude faster than in-plane ordering. Two critical transitions are identified: an alpha-to-beta phase transformation at 1.64 GPa, and a subsequent collapse into a single-atomic layer at 2.19 GPa. The formation of large-area single crystals is enabled by substrate-induced orientational selection and accelerated grain boundary migration, driven by atomic diffusion at elevated temperatures. These findings resolve the mechanistic origin of high-quality 2D crystal growth under confinement and establish guiding principles for the controlled synthesis of metastable 2D single crystals, with implications for next-generation quantum and nanoelectronic devices. △ Less

Submitted 9 August, 2025; originally announced August 2025.

Comments: 5 pages, 4 figures

EAC-Net: Predicting real-space charge density via equivariant atomic contributions

Authors: Xuejian Qin, Taoyuze Lv, Zhicheng Zhong

Abstract: Charge density is central to density functional theory (DFT), as it fully defines the ground-state properties of a material system. Obtaining it with high accuracy is a computational bottleneck. Existing machine learning models are constrained by trade-offs among accuracy, efficiency, and generalization. Here, we introduce the Equivariant Atomic Contribution Network (EAC-Net), which couples atoms… ▽ More Charge density is central to density functional theory (DFT), as it fully defines the ground-state properties of a material system. Obtaining it with high accuracy is a computational bottleneck. Existing machine learning models are constrained by trade-offs among accuracy, efficiency, and generalization. Here, we introduce the Equivariant Atomic Contribution Network (EAC-Net), which couples atoms and grids to integrate the strengths of grid-based and basis-function frameworks. EAC-Net achieves high accuracy (typically below 1% error), enhanced efficiency, and strong generalization across complex systems. Building on this framework, we develop EAC-mp, a universal charge density model covering the periodic table. The model demonstrates robust zero-shot performance across diverse systems, and generalizes beyond the training distribution, supporting downstream applications such as band structure calculations. By linking local chemical environments to charge densities, EAC-Net provides a scalable framework for accelerating electronic structure prediction and enabling high-throughput materials discovery. △ Less

Submitted 28 September, 2025; v1 submitted 5 August, 2025; originally announced August 2025.

Comments: 21pages, 5figures

Uncovering coupled ionic-polaronic dynamics and interfacial enhancement in Li$_x$FePO$_4$

Authors: Fengyu Xie, Yuxiang Gao, Ruoyu Wang, Zhicheng Zhong

Abstract: Understanding and controlling coupled ionic-polaronic dynamics is crucial for optimizing electrochemical performance in battery materials. However, studying such coupled dynamics remains challenging due to the intricate interplay between Li-ion configurations, polaron charge ordering, and lattice vibrations. Here, we develop a fine-tuned machine-learned force field (MLFF) for Li$_x$FePO$_4$ that c… ▽ More Understanding and controlling coupled ionic-polaronic dynamics is crucial for optimizing electrochemical performance in battery materials. However, studying such coupled dynamics remains challenging due to the intricate interplay between Li-ion configurations, polaron charge ordering, and lattice vibrations. Here, we develop a fine-tuned machine-learned force field (MLFF) for Li$_x$FePO$_4$ that captures coupled ion-polaron behavior. Our simulations reveal picosecond-scale polaron flips occurring orders of magnitude faster than Li-ion migration, featuring strong correlation to Li configurations. Notably, polaron charge fluctuations are further enhanced at Li-rich/Li-poor phase boundaries, suggesting a potential interfacial electronic conduction mechanism. These results demonstrate the capability of fine-tuned MLFFs to resolve complex coupled transport and provide insight into emergent ionic-polaronic dynamics in multivalent battery cathodes. △ Less

Submitted 7 July, 2025; originally announced July 2025.

Conditional Generative Modeling for Amorphous Multi-Element Materials

Authors: Honglin Li, Chuhao Liu, Yongfeng Guo, Xiaoshan Luo, Yijie Chen, Guangsheng Liu, Yu Li, Ruoyu Wang, Zhenyu Wang, Jianzhuo Wu, Cheng Ma, Zhuohang Xie, Jian Lv, Yufei Ding, Huabin Zhang, Jian Luo, Zhicheng Zhong, Mufan Li, Yanchao Wang, Wan-Lu Li

Abstract: Amorphous multi-element materials offer unprecedented tunability in composition and properties, yet their rational design remains challenging due to the lack of predictive structure-property relationships and the vast configurational space. Traditional modeling struggles to capture the intricate short-range order that dictates their stability and functionality. We here introduce ApolloX, a pioneer… ▽ More Amorphous multi-element materials offer unprecedented tunability in composition and properties, yet their rational design remains challenging due to the lack of predictive structure-property relationships and the vast configurational space. Traditional modeling struggles to capture the intricate short-range order that dictates their stability and functionality. We here introduce ApolloX, a pioneering predictive framework for amorphous multi-element materials, establishing a new paradigm by integrating physics-informed generative modeling with particle swarm optimization, using chemical short-range order as an explicit constraint. By systematically navigating the disordered energy landscape, ApolloX enables the targeted design of thermodynamically stable amorphous configurations. It accurately predicts atomic-scale arrangements, including composition-driven metal clustering and amorphization trends, which are well-validated by experiments, while also guiding synthesis by leveraging sluggish diffusion to control elemental distribution and disorder. The resulting structural evolution, governed by composition, directly impacts catalytic performance, leading to improved activity and stability with increasing amorphization. This predictive-experimental synergy transforms the discovery of amorphous materials, unlocking new frontiers in catalysis, energy storage, and functional disordered systems. △ Less

Submitted 10 March, 2025; originally announced March 2025.

Temperature-driven structural phase transitions in SmNiO$_3$: insights from deep potential molecular dynamics simulations

Authors: Guoyong Shi, Fenglin Deng, Ri He, Dachuan Chen, Xuejiao Chen, Peiheng Jiang, Zhicheng Zhong

Abstract: The metal-insulator transition (MIT) in rare-earth nickelates exemplifies the intricate interplay between electronic correlations and lattice dynamics in quantum materials. This work focuses on SmNiO$_3$ as a prototypical system, employing molecular dynamics simulations based on a "hidden" magnetic potential model. Our simulations reveal two key findings. First, the structural phase transition in… ▽ More The metal-insulator transition (MIT) in rare-earth nickelates exemplifies the intricate interplay between electronic correlations and lattice dynamics in quantum materials. This work focuses on SmNiO$_3$ as a prototypical system, employing molecular dynamics simulations based on a "hidden" magnetic potential model. Our simulations reveal two key findings. First, the structural phase transition in SmNiO$_3$ is intrinsically temperature-driven and occurs spontaneously via collective lattice distortions. Moreover, systematic high-pressure simulations demonstrate a distinct pressure dependence of the transition temperature, which decreases monotonically with increasing external hydrostatic pressure. These results provide atomistic insights into the cooperative mechanisms underlying the MIT and the interplay between structural distortions and electron correlation effects. The computational approach developed herein offers a generalizable framework for investigating complex phase transitions in correlated quantum materials. △ Less

Submitted 7 March, 2025; originally announced March 2025.

Comments: 15pages, 7 figues

T-MSD: An improved method for ionic diffusion coefficient calculation from molecular dynamics

Authors: Yuxiang Gao, Xiaodong Cao, Zhicheng Zhong

Abstract: Ionic conductivity is a critical property of solid ionic conductors, directly influencing the performance of energy storage devices such as batteries. However, accurately calculating ionic conductivity or diffusion coefficient remains challenging due to the complex, dynamic nature of ionic motion, which often yield significant deviations, especially at room temperature. In this study, we propose a… ▽ More Ionic conductivity is a critical property of solid ionic conductors, directly influencing the performance of energy storage devices such as batteries. However, accurately calculating ionic conductivity or diffusion coefficient remains challenging due to the complex, dynamic nature of ionic motion, which often yield significant deviations, especially at room temperature. In this study, we propose an improved method, T-MSD, to enhance the accuracy and reliability of diffusion coefficient calculations. Combining time-averaged mean square displacement analysis with block jackknife resampling, this method effectively addresses the impact of rare, anomalous diffusion events and provides robust statistical error estimates from a single simulation. Applied to large-scale deep-potential molecular dynamics simulations, we show that T-MSD eliminates the need for multiple independent simulations while ensuring accurate diffusion coefficient calculations across systems of varying sizes and simulation durations. This approach offers a practical and reliable framework for precise ionic conductivity estimation, advancing the study and design of high-performance solid ionic conductors. △ Less

Submitted 6 March, 2025; originally announced March 2025.

Pre-training, fine-tuning, and distillation (PFD): Automatically generating machine learning force fields from universal models

Authors: Ruoyu Wang, Yuxiang Gao, Hongyu Wu, Zhicheng Zhong

Abstract: Universal force fields generalizable across the periodic table represent a new trend in computational materials science. However, the applications of universal force fields in material simulations are limited by their slow inference speed and the lack of first-principles accuracy. Instead of building a single model simultaneously satisfying these characteristics, a strategy that quickly generates… ▽ More Universal force fields generalizable across the periodic table represent a new trend in computational materials science. However, the applications of universal force fields in material simulations are limited by their slow inference speed and the lack of first-principles accuracy. Instead of building a single model simultaneously satisfying these characteristics, a strategy that quickly generates material-specific models from the universal model may be more feasible. Here, we propose a new workflow pattern, PFD (Pre-training, Fine-tuning, and Distillation), which automatically generates machine-learning force fields for specific materials from a pre-trained universal model through fine-tuning and distillation. By fine-tuning the pre-trained model, our PFD workflow generates force fields with first-principles accuracy while requiring one to two orders of magnitude less training data compared to traditional methods. The inference speed of the generated force field is further improved through distillation, meeting the requirements of large-scale molecular simulations. Comprehensive testing across diverse materials including complex systems, such as amorphous carbon, interface, etc., reveals marked enhancements in training efficiency, which suggests the PFD workflow a practical and reliable approach for force field generation in computational material sciences. △ Less

Submitted 10 December, 2025; v1 submitted 28 February, 2025; originally announced February 2025.

Comments: 11 pages, 8 figures

Journal ref: Phys. Rev. Materials (2025) 9, 113802

Undamped Soliton-like Domain Wall Motion in Sliding Ferroelectrics

Authors: Yubai Shi, Yuxiang Gao, Ri He, Hua Wang, Binwen Zhang, Zhicheng Zhong

Abstract: Sliding ferroelectricity in bilayer van der Waals materials exhibits ultrafast switching speed and fatigue resistance during the polarization switching, offering an avenue for the design of memories and neuromorphic devices. The unique polarization switching behavior originates from the distinct characteristics of domain wall (DW), which possesses broader width and faster motion compared to conven… ▽ More Sliding ferroelectricity in bilayer van der Waals materials exhibits ultrafast switching speed and fatigue resistance during the polarization switching, offering an avenue for the design of memories and neuromorphic devices. The unique polarization switching behavior originates from the distinct characteristics of domain wall (DW), which possesses broader width and faster motion compared to conventional ferroelectrics. Herein, using machine-learning-assisted molecular dynamics simulations and field theory analysis, we predict an undamped soliton-like DW motion in sliding ferroelectrics. It is found that the DW in sliding ferroelectric bilayer 3R-MoS2 exhibits uniformly accelerated motion under an external field, with its velocity ultimately reaches the relativistic-like limit due to continuous acceleration. Remarkably, the DW velocity remains constant even after the external field removal, completely deviating from the velocity breakdown observed in conventional ferroelectrics. This work provides opportunities for applications of sliding ferroelectrics in memory devices based on DW engineering. △ Less

Submitted 19 February, 2025; v1 submitted 4 February, 2025; originally announced February 2025.

Domain-Pair Intertwined Topological Domain Structure in Elemental Bi Monolayer

Authors: Yunfei Hong, Junkai Deng, Yang Yang, Ri He, Zhicheng Zhong, Xiangdong Ding, Jun Sun, Jefferson Zhe Liu

Abstract: Ferroelectric domain structures, separated by domain walls, often display unconventional physics and hold significant potential for applications in nano-devices. Most naturally growth domain walls are charge-neutral to avoid increased electrostatic energy, while the intrinsically stable charged 180° domain walls in Bi monolayer challenged this conventional knowledge and emerged an unexplored field… ▽ More Ferroelectric domain structures, separated by domain walls, often display unconventional physics and hold significant potential for applications in nano-devices. Most naturally growth domain walls are charge-neutral to avoid increased electrostatic energy, while the intrinsically stable charged 180° domain walls in Bi monolayer challenged this conventional knowledge and emerged an unexplored field. Here, using machine-learning potential and molecular dynamics (MD) simulations, we investigated the finite-temperature dynamics of domain walls and discovered a domain-pair intertwined topological domain structure in Bi monolayer. In 180° domain walls, a unique polarization switching mechanism is observed, characterized by the out-of-plane shuffle of Bi atoms without bond breaking. This shuffle mechanism reverses the charge properties of Bi atoms, transforming Bi anions into cations and vice versa, ultimately reversing the polarization. Then, we observed a topological multi-domain structure with two groups of domain pairs intertwined. The charged 180° domain walls form local domain pairs, with the 90° domain walls emerge between different domain pairs. This multi-domain maintains a stable topological structure within the strain range (ε_x = 0 to 4.70%) and exhibits rich domain wall reactions under further applied strain. Our findings provide insights into the charged 180° domain walls and the related topological domain structures, enabling new opportunities for applications in electronic and nano-electronic devices. △ Less

Submitted 13 December, 2024; originally announced December 2024.

Comments: 25 pages, 4 main figures and 17 supplemental figures

Mechanics of soft-body rolling motion without external torque

Authors: Xudong Liang, Yimiao Ding, Zihao Yuan, Junqi Jiang, Zongling Xie, Peng Fei, Yixuan Sun, Guoying Gu, Zheng Zhong, Feifei Chen, Guangwei Si, Zhefeng Gong

Abstract: The Drosophila larva, a soft-body animal, can bend its body and roll efficiently to escape danger. However, contrary to common belief, this rolling motion is not driven by the imbalance of gravity and ground reaction forces. Through functional imaging and ablation experiments, we demonstrate that the sequential actuation of axial muscles within an appropriate range of angles is critical for genera… ▽ More The Drosophila larva, a soft-body animal, can bend its body and roll efficiently to escape danger. However, contrary to common belief, this rolling motion is not driven by the imbalance of gravity and ground reaction forces. Through functional imaging and ablation experiments, we demonstrate that the sequential actuation of axial muscles within an appropriate range of angles is critical for generating rolling. We model the interplay between muscle contraction, hydrostatic skeleton deformation, and body-environment interactions, and systematically explain how sequential muscle actuation generates the rolling motion. Additionally, we constructed a pneumatic soft robot to mimic the larval rolling strategy, successfully validating our model. This mechanics model of soft-body rolling motion not only advances the study of related neural circuits, but also holds potential for applications in soft robotics. △ Less

Submitted 10 October, 2024; originally announced October 2024.

Hong-Ou-Mandel Interference in a temporal-average-inversion-symmetric chain

Authors: Shi Hu, Meiqing Hu, Shihao Li, Zihui Zhong, Zhoutao Lei

Abstract: We show how to implement tunable beam splitter and Hong-Ou-Mandel interference in the Su-Schrieffer-Heeger chain by manipulating the topological edge states adiabatically. The boson initially injected in the one end of the chain can be transferred to the two-end with a tunable proportion depends on the dynamical phases accumulated during the adiabatic evolution. We also observe Hong-Ou-Mandel inte… ▽ More We show how to implement tunable beam splitter and Hong-Ou-Mandel interference in the Su-Schrieffer-Heeger chain by manipulating the topological edge states adiabatically. The boson initially injected in the one end of the chain can be transferred to the two-end with a tunable proportion depends on the dynamical phases accumulated during the adiabatic evolution. We also observe Hong-Ou-Mandel interference via the tunable beam splitter ($50:50$) and achieve a spatially entangled two-particle NOON state. We demonstrate the robustness of our proposal under chiral- and time-reversal-symmetry-preserving disorder. However, the chiral symmetry is scarce for realist system. Therefore, we demonstrate Hong-Ou-Mandel interference are robust to inversion symmetric disorder breaking the chiral symmetry, highlighting the protection of inversion symmetry. More importantly, the inversion symmetry violated by static disorder can be restored for more common situations where disorder becomes time dependent, giving rise to the temporal-average-inversion-symmetry protected Hong-Ou-Mandel interference. Our approach opens a new way to study quantum effects in topological matter with potential applications. △ Less

Submitted 4 September, 2024; originally announced September 2024.

Journal ref: PhysRevA.110, 032438 (2024)

Spontaneous curvature in two-dimensional van der Waals heterostructures

Authors: Yuxiang Gao, Fenglin Deng, Ri He, Zhicheng Zhong

Abstract: Two-dimensional (2D) van der Waals (vdW) heterostructures consist of different 2D crystals with diverse properties, constituting the cornerstone of the new generation of 2D electronic devices. Yet interfaces in heterostructures inevitably break bulk symmetry and structural continuity, resulting in delicate atomic rearrangements and novel electronic structures. In this paper, we predict that 2D int… ▽ More Two-dimensional (2D) van der Waals (vdW) heterostructures consist of different 2D crystals with diverse properties, constituting the cornerstone of the new generation of 2D electronic devices. Yet interfaces in heterostructures inevitably break bulk symmetry and structural continuity, resulting in delicate atomic rearrangements and novel electronic structures. In this paper, we predict that 2D interfaces undergo spontaneous curvature, which means when two flat 2D layers approach each other, they inevitably experience out-of-plane curvature. Based on deep-learning-assisted large-scale molecular dynamics simulations, we observed significant out-of-plane displacements up to 3.8 angstrom in graphene/BN bilayers induced by curvature, producing a stable hexagonal moire pattern, which agrees well with experimentally observations. Additionally, the out-of-plane flexibility of 2D crystals enables the propagation of curvature throughout the system, thereby influencing the mechanical properties of the heterostructure. These findings offer fundamental insights into the atomic structure in 2D vdW heterostructures and pave the way for their applications in devices. △ Less

Submitted 3 September, 2024; originally announced September 2024.

Comments: 21 pages and 6 figures

Vision Transformer Neural Quantum States for Impurity Models

Authors: Xiaodong Cao, Zhicheng Zhong, Yi Lu

Abstract: Transformer neural networks, known for their ability to recognize complex patterns in high-dimensional data, offer a promising framework for capturing many-body correlations in quantum systems. We employ an adapted Vision Transformer (ViT) architecture to model quantum impurity models, optimizing it with a subspace expansion scheme that surpasses conventional variational Monte Carlo in both accura… ▽ More Transformer neural networks, known for their ability to recognize complex patterns in high-dimensional data, offer a promising framework for capturing many-body correlations in quantum systems. We employ an adapted Vision Transformer (ViT) architecture to model quantum impurity models, optimizing it with a subspace expansion scheme that surpasses conventional variational Monte Carlo in both accuracy and efficiency. Benchmarks against matrix product states in single- and three-orbital Anderson impurity models show that these ViT-based neural quantum states achieve comparable or superior accuracy with significantly fewer variational parameters. We further extend our approach to compute dynamical quantities by constructing a restricted excitation space that effectively captures relevant physical processes, yielding accurate core-level X-ray absorption spectra. These findings highlight the potential of ViT-based neural quantum states for accurate and efficient modeling of quantum impurity models. △ Less

Submitted 23 August, 2024; originally announced August 2024.

Sliding Flexoelectricity in Two-Dimensional van der Waals Systems

Authors: Ri He, Hua Wang, Fenglin Deng, Yuxiang Gao, Binwen Zhang, Yubai Shi, Run-Wei Li, Zhicheng Zhong

Abstract: Two-dimensional sliding ferroelectrics, with their unique stacking degrees of freedom, offer a different approach to manipulate polarization by interlayer sliding. Bending sliding ferroelectrics inevitably leads to interlayer sliding motion, thus altering stacking orders and polarization properties. Here, by using machine-learning force field, we investigate the effects of bending deformation on g… ▽ More Two-dimensional sliding ferroelectrics, with their unique stacking degrees of freedom, offer a different approach to manipulate polarization by interlayer sliding. Bending sliding ferroelectrics inevitably leads to interlayer sliding motion, thus altering stacking orders and polarization properties. Here, by using machine-learning force field, we investigate the effects of bending deformation on geometries, stackings, energies, and polarizations in sliding ferroelectric bilayer h-BN and 3R-MoS2. We predict that bent ferroelectric bilayer forms irreversible kinks instead of arc when the bending angle exceeds a critical value. We demonstrate that the kinks originate from the competition between bending energy and interlayer van der Waals energy. The kink contains a ferroelectric domain wall that reverses the polarization, effectively inducing a flexoelectric effect. We term this phenomenon "sliding flexoelectricity" to distinguish it from conventional strain-gradient-induced flexoelectricity. △ Less

Submitted 1 August, 2024; originally announced August 2024.

Comments: 4 figures in the maintext, 11 figures in the Supplemental Material

A compositional ordering-driven morphotropic phase boundary in ferroelectric solid solutions

Authors: Yubai Shi, Yifan Shan, Hongyu Wu, Zhicheng Zhong, Ri He, Run-Wei Li

Abstract: Ferroelectric solid solutions usually exhibit giant dielectric response and high piezoelectricity in the vicinity of the morphotropic phase boundary (MPB), where the structural phase transitions between the rhombohedral and the tetragonal phases as a result of the composition or strain variation. Here, we propose a compositional ordering-driven MPB in the specified compositional solid solutions. B… ▽ More Ferroelectric solid solutions usually exhibit giant dielectric response and high piezoelectricity in the vicinity of the morphotropic phase boundary (MPB), where the structural phase transitions between the rhombohedral and the tetragonal phases as a result of the composition or strain variation. Here, we propose a compositional ordering-driven MPB in the specified compositional solid solutions. By preforming machine-learning potential based molecular dynamics simulations on lead zirconate titanate, we find a phase transition from the rhombohedral to tetragonal phase with the decrease of compositional ordering, leading to the MPB on temperature-ordering phase diagram. The compositional ordering-driven MPB can enhances the piezoelectricity with a magnitude comparable to that at the composition-driven MPB. Finally, we demonstrate that the mechanism of high piezoelectricity is polarization rotation driven by external field. This work provides an additional degree of freedom, compositional ordering, to design the high-performance piezoelectric materials. △ Less

Submitted 29 June, 2024; originally announced July 2024.

Noncentrosymmetric Nowotny Chimney Ladder Ferromagnet Cr4Ge7 with a High Curie Temperature of ~ 207 K

Authors: Zhenhai Yu, Kaijuan Zhou, Xiaofei Hou, Xuejiao Chen, Zhen Tao, Yunguan Ye, Wei Xia, Zhongyang Li, Jinggeng Zhao, Wei Wu, Ziyi Liu, Xia Wang, Na Yu, Jinguang Cheng, Jianlin Luo, Qiang Zhang, Vladimir Pomjakushin, Zhicheng Zhong, Soh Jian Rui, Xingye Lu, Yanfeng Guo

Abstract: Noncentrosymmetric magnets usually host intriguing magnetic interactions inherent the crystal structure with broken inversion symmetry, which can give rise to rich magnetic behaviors. We report herein the high-pressure synthesis, crystal structure, magnetizations and magnetic structure of a so-called Nowotny chimney ladder compound Cr4Ge7. Our analysis on the powder neutron diffraction data revise… ▽ More Noncentrosymmetric magnets usually host intriguing magnetic interactions inherent the crystal structure with broken inversion symmetry, which can give rise to rich magnetic behaviors. We report herein the high-pressure synthesis, crystal structure, magnetizations and magnetic structure of a so-called Nowotny chimney ladder compound Cr4Ge7. Our analysis on the powder neutron diffraction data revises the crystal structure as a noncentrosymmetric space group (P-4c2, No.116). It exhibits two magnetic orders within the temperature range of 2 - 400 K. The first order at ~ 207 K associated with a small magnetic moment of ~ 0.75 miuB is assigned to a commensurate ferromagnetic structure with a propagation vector k = (0, 0, 0). The weak itinerant ferromagnet nature should be caused by the complex Cr spin orders from different Wyckoff positions. The second order at ~ 18 K is assumed to arise from a competition between the Dzyaloshinskii-Moria and Heisenberg interactions. The results provide an excellent platform for study on intricate interactions between various magnetic exchanges as well as for the exploration of high temperature exotic magnetic properties which host potential applications in next-generation spintronics. △ Less

Submitted 3 March, 2024; originally announced March 2024.

Comments: 21 pages, 5 figures, 2 tables; Supporting Information is not included

Journal ref: Chemistry of Materials, 2024

DPA-2: a large atomic model as a multi-task learner

Authors: Duo Zhang, Xinzijian Liu, Xiangyu Zhang, Chengqian Zhang, Chun Cai, Hangrui Bi, Yiming Du, Xuejian Qin, Anyang Peng, Jiameng Huang, Bowen Li, Yifan Shan, Jinzhe Zeng, Yuzhi Zhang, Siyuan Liu, Yifan Li, Junhan Chang, Xinyan Wang, Shuo Zhou, Jianchuan Liu, Xiaoshan Luo, Zhenyu Wang, Wanrun Jiang, Jing Wu, Yudi Yang , et al. (18 additional authors not shown)

Abstract: The rapid advancements in artificial intelligence (AI) are catalyzing transformative changes in atomic modeling, simulation, and design. AI-driven potential energy models have demonstrated the capability to conduct large-scale, long-duration simulations with the accuracy of ab initio electronic structure methods. However, the model generation process remains a bottleneck for large-scale applicatio… ▽ More The rapid advancements in artificial intelligence (AI) are catalyzing transformative changes in atomic modeling, simulation, and design. AI-driven potential energy models have demonstrated the capability to conduct large-scale, long-duration simulations with the accuracy of ab initio electronic structure methods. However, the model generation process remains a bottleneck for large-scale applications. We propose a shift towards a model-centric ecosystem, wherein a large atomic model (LAM), pre-trained across multiple disciplines, can be efficiently fine-tuned and distilled for various downstream tasks, thereby establishing a new framework for molecular modeling. In this study, we introduce the DPA-2 architecture as a prototype for LAMs. Pre-trained on a diverse array of chemical and materials systems using a multi-task approach, DPA-2 demonstrates superior generalization capabilities across multiple downstream tasks compared to the traditional single-task pre-training and fine-tuning methodologies. Our approach sets the stage for the development and broad application of LAMs in molecular and materials simulation research. △ Less

Submitted 16 August, 2024; v1 submitted 24 December, 2023; originally announced December 2023.

Journal ref: npj Comput Mater 10, 293 (2024)

Revisit the phase diagram and piezoelectricity of lead zirconate titanate from first principles

Authors: Yubai Shi, Ri He, Bingwen Zhang, Zhicheng Zhong

Abstract: Lead zirconate titanate (PbZr1-xTixO3, PZT) exhibits excellent piezoelectric properties in the morphotropic phase boundary (MPB) region of its temperature-composition phase diagram. However, the microscopic origin of its high piezoelectric response remains controversial. Here, we develop a machine-learning-based deep potential (DP) model of PZT using the training dataset from first principles dens… ▽ More Lead zirconate titanate (PbZr1-xTixO3, PZT) exhibits excellent piezoelectric properties in the morphotropic phase boundary (MPB) region of its temperature-composition phase diagram. However, the microscopic origin of its high piezoelectric response remains controversial. Here, we develop a machine-learning-based deep potential (DP) model of PZT using the training dataset from first principles density functional theory calculations. Based on DP-assisted large-scale atomic simulations, we reproduce the temperature-composition phase diagram of PZT, in good agreement with the experiment except the absence of structural transition from R3c to R3m. We find that the rhombohedral phase maintains R3c symmetry with slight oxygen octahedral tilting as increase of temperature, instead of appearing R3m symmetry. This discrepancy can trace back to the lack of experimental measurements to identify such slight octahedral tilting. More importantly, we clarify the atomic-level feature of PZT at the MPB, exhibiting the competing coupling of ferroelectric nanodomains with various polarization orientations. The high piezoelectric response is driven by polarization rotation of nanodomains induced by an external electric field. △ Less

Submitted 20 December, 2023; originally announced December 2023.

Comments: 19 pages, 8 figures

Giant domain wall anomalous Hall effect in an antiferromagnet

Authors: Wei Xia, Bo Bai, Xuejiao Chen, Yichen Yang, Yang Zhang, Jian Yuan, Qiang Li, Kunya Yang, Xiangqi Liu, Yang Shi, Haiyang Ma, Huali Yang, Mingquan He, Lei Li, Chuanying Xi, Li Pi, Xiaodong Lv, Xia Wang, Xuerong Liu, Shiyan Li, Xiaodong Zhou, Jianpeng Liu, Yulin Chen, Jian Shen, Dawei Shen , et al. (3 additional authors not shown)

Abstract: Generally, the dissipationless Hall effect in solids requires time-reversal symmetry breaking (TRSB), where TRSB induced by external magnetic field results in ordinary Hall effect, while TRSB caused by spontaneous magnetization gives rise to anomalous Hall effect (AHE) which scales with the net magnetization. The AHE is therefore not expected in antiferromagnets with vanishing small magnetization.… ▽ More Generally, the dissipationless Hall effect in solids requires time-reversal symmetry breaking (TRSB), where TRSB induced by external magnetic field results in ordinary Hall effect, while TRSB caused by spontaneous magnetization gives rise to anomalous Hall effect (AHE) which scales with the net magnetization. The AHE is therefore not expected in antiferromagnets with vanishing small magnetization. However, large AHE was recently observed in certain antiferromagnets with noncolinear spin structure and nonvanishing Berry curvature. Here, we report another origin of AHE in a layered antiferromagnet EuAl2Si2, namely the domain wall (DW) skew scattering with Weyl points near the Fermi level, in experiments for the first time. Interestingly, the DWs form a unique periodic stripe structure with controllable periodicity by external magnetic field, which decreases nearly monotonically from 975 nm at 0 T to 232 nm at 4 T. Electrons incident on DW with topological bound states experience strong asymmetric scattering, leading to a giant AHE, with the DW Hall conductivity (DWHC) at 2 K and 1.2 T reaching a record value of ~ 1,5100 S cm-1 among bulk systems and being two orders of magnitude larger than the intrinsic anomalous Hall conductivity. The observation not only sets a new paradigm for exploration of large anomalous Hall effect, but also provides potential applications in spintronic devices. △ Less

Submitted 18 October, 2024; v1 submitted 12 December, 2023; originally announced December 2023.

Comments: 20 pages Main Text+ SI 33 pages, 5 main figures

Journal ref: Physical Review Letters 2024, 133: 216602

Real-Space Visualization of Frequency-Dependent Anisotropy of Atomic Vibrations

Authors: Xingxu Yan, Paul M. Zeiger, Yifeng Huang, Haoying Sun, Jie Li, Chaitanya A. Gadre, Hongbin Yang, Ri He, Toshihiro Aoki, Zhicheng Zhong, Yuefeng Nie, Ruqian Wu, Ján Rusz, Xiaoqing Pan

Abstract: The underlying dielectric properties of materials, intertwined with intriguing phenomena such as topological polariton modes and anisotropic thermal conductivities, stem from the anisotropy in atomic vibrations. Conventionally, X-ray diffraction techniques have been employed to estimate thermal ellipsoids of distinct elements, albeit lacking the desired spatial and energy resolutions. Here we intr… ▽ More The underlying dielectric properties of materials, intertwined with intriguing phenomena such as topological polariton modes and anisotropic thermal conductivities, stem from the anisotropy in atomic vibrations. Conventionally, X-ray diffraction techniques have been employed to estimate thermal ellipsoids of distinct elements, albeit lacking the desired spatial and energy resolutions. Here we introduce a novel approach utilizing the dark-field monochromated electron energy-loss spectroscopy for momentum-selective vibrational spectroscopy, enabling the cartographic delineation of variations of phonon polarization vectors. By applying this technique to centrosymmetric cubic-phase strontium titanate, we successfully discern two types of oxygen atoms exhibiting contrasting vibrational anisotropies below and above 60 meV due to their frequency-linked thermal ellipsoids. This method establishes a new pathway to visualize phonon eigenvectors at specific crystalline sites for diverse elements, thus delving into uncharted realms of dielectric, optical, and thermal property investigations with unprecedented spatial resolutions. △ Less

Submitted 4 December, 2023; originally announced December 2023.

Journal ref: Nature 2025

Ferroelastic twin wall mediated ferro-flexoelectricity and bulk photovoltaic effect in SrTiO$_3$

Authors: Ri He, Haowei Xu, Peijun Yang, Kai Chang, Hua Wang, Zhicheng Zhong

Abstract: Ferroelastic twin walls in nonpolar materials can give rise to a spontaneous polarization due to symmetry breaking. Nevertheless, the bi-stable polarity of twin walls and its reversal have not yet been demonstrated. Here, we report that the polarity of SrTiO$_3$ twin walls can be switched by ultra-low strain gradient. Using first-principles-based machine-learning potential, we demonstrate that the… ▽ More Ferroelastic twin walls in nonpolar materials can give rise to a spontaneous polarization due to symmetry breaking. Nevertheless, the bi-stable polarity of twin walls and its reversal have not yet been demonstrated. Here, we report that the polarity of SrTiO$_3$ twin walls can be switched by ultra-low strain gradient. Using first-principles-based machine-learning potential, we demonstrate that the twin walls can be deterministically rotated and realigned in specific directions under strain gradient, which breaks the inversion symmetry of a sequence of walls and leads to a macroscopic polarization. The system can maintain polarity even after the strain gradient is removed. As a result, the polarization of twin walls can exhibit ferroelectric-like hysteresis loop upon cyclic bending, namely ferro-flexoelectricity. Finally, we propose a scheme to experimentally detect the polarity of twin wall by measuring the bulk photovoltaic responses. Our findings suggest a twin-wall-mediated ferro-flexoelectricity in SrTiO$_3$, which could be potentially exploited as functional elements in nano-electronic devices design. △ Less

Submitted 16 October, 2023; originally announced October 2023.

Comments: 5 figures, 14pages

Report number: 14

Pressure-induced one-dimensional oxygen ion diffusion channel in lead-apatite

Authors: Ri He, Hongyu Wu, Xuejian Qin, Xuejiao Chen, Zhicheng Zhong

Abstract: Recently, Lee et al. claimed that the experimental observation of room-temperature ambient-pressure superconductivity in a Cu-doped lead-apatite (Pb10-xCux(PO4)6O). The study revealed the Cu doping induces a chemical pressure, resulting in a structural contraction of one-dimensional Cu-O-Cu atomic column. This unique structure promotes a one-dimensional electronic conduction channel along the c-ax… ▽ More Recently, Lee et al. claimed that the experimental observation of room-temperature ambient-pressure superconductivity in a Cu-doped lead-apatite (Pb10-xCux(PO4)6O). The study revealed the Cu doping induces a chemical pressure, resulting in a structural contraction of one-dimensional Cu-O-Cu atomic column. This unique structure promotes a one-dimensional electronic conduction channel along the c-axis mediated by the O atoms, which may be related to superconductivity. These O atoms occupy 1/4 of the equivalent positions along the c-axis and exhibit a low diffusion activation energy of 0.8 eV, indicating the possibility of diffusion between these equivalent positions. Here, using machine-learning based deep potential, we predict the pressure-induced fast diffusion of 1/4-occupied O atoms along the one-dimensional channel in Pb10(PO4)6O at 500 K, while the frameworks of Pb triangles and PO4 tetrahedrons remain stable. The calculation results also indicate Cu doping can provide appropriate effective chemical pressure, indicating the one-dimensional ion diffusion channel may appear in Pb9Cu(PO4)6O, even at ambient pressure. Our finding shows that the one-dimensional ions diffusion channel may be an important factor to affects the fabrication and electrical measurement of doped lead-apatite. △ Less

Submitted 28 September, 2023; originally announced September 2023.

Comments: 15 pages, 7 figures

Atomistic simulations of thermodynamic properties of liquid gallium from first principles

Authors: Hongyu Wu, Wenliang Shi, Ri He, Guoyong Shi, Chunxiao Zhang, Zhicheng Zhong, Run-wei Li

Abstract: In the research of condensed matter, atomistic dynamic simulations play a crucial role, particularly in revealing dynamic processes, phase transitions and thermodynamic statistics macroscopic physical properties in systems such as solids and liquids. For a long time, simulating complex and disordered liquids has been a challenge compared to ordered crystalline structures. The primary reasons for t… ▽ More In the research of condensed matter, atomistic dynamic simulations play a crucial role, particularly in revealing dynamic processes, phase transitions and thermodynamic statistics macroscopic physical properties in systems such as solids and liquids. For a long time, simulating complex and disordered liquids has been a challenge compared to ordered crystalline structures. The primary reasons for this challenge are the lack of precise force field functions and the neglect of nuclear quantum effects. To overcome these two limits in simulation of liquids, we use a deep potential (DP) with quantum thermal bath (QTB) approach. DP is a machine learning model are sampled from density functional theory and able to do large-scale atomic simulations with its precision. QTB is a method which incorporates nuclear quantum effects by quantum fluctuation dissipation. The application of this first principles approach enable us to successfully describe the phase transition processes in solid and liquid Gallium (Ga) as well as the associated dynamic phenomena. More importantly, we obtain the thermodynamic properties of liquid Ga, such as internal energy, specific heat, enthalpy change, entropy and Gibbs free energy, and these results align remarkably well with experiments. Our research has opened up a new paradigm for the study of dynamics and thermodynamics in liquids, amorphous materials, and other disordered systems, providing valuable insights and references for future investigations. △ Less

Submitted 14 November, 2023; v1 submitted 26 September, 2023; originally announced September 2023.

Comments: 7 pages, 11 figures for maintext; 6pages, 8 figures for supplementary materials

Deep Charge: A Deep Learning Model of Electron Density from One-Shot Density Functional Theory Calculation

Authors: Taoyuze Lv, Zhicheng Zhong, Yuhang Liang, Feng Li, Jun Huang, Rongkun Zheng

Abstract: Electron charge density is a fundamental physical quantity, determining various properties of matter. In this study, we have proposed a deep-learning model for accurate charge density prediction. Our model naturally preserves physical symmetries and can be effectively trained from one-shot density functional theory calculation toward high accuracy. It captures detailed atomic environment informati… ▽ More Electron charge density is a fundamental physical quantity, determining various properties of matter. In this study, we have proposed a deep-learning model for accurate charge density prediction. Our model naturally preserves physical symmetries and can be effectively trained from one-shot density functional theory calculation toward high accuracy. It captures detailed atomic environment information, ensuring accurate predictions of charge density across bulk, surface, molecules, and amorphous structures. This implementation exhibits excellent scalability and provides efficient analyses of material properties in large-scale condensed matter systems. △ Less

Submitted 25 September, 2023; originally announced September 2023.

Electronic band reconstruction across the insulator-metal transition in colossal magnetoresistive EuCd2P2

Authors: Huali Zhang, Feng Du, Xiaoying Zheng, Shuaishuai Luo, Yi Wu, Hao Zheng, Shengtao Cui, Zhe Sun, Zhengtai Liu, Dawei Shen, Michael Smidman, Yu Song, Ming Shi, Zhicheng Zhong, Chao Cao, Huiqiu Yuan, Yang Liu

Abstract: While colossal magnetoresistance (CMR) in Eu-based compounds is often associated with strong spin-carrier interactions, the underlying reconstruction of the electronic bands is much less understood from spectroscopic experiments. Here using angle-resolved photoemission, we directly observe an electronic band reconstruction across the insulator-metal (and magnetic) transition in the recently discov… ▽ More While colossal magnetoresistance (CMR) in Eu-based compounds is often associated with strong spin-carrier interactions, the underlying reconstruction of the electronic bands is much less understood from spectroscopic experiments. Here using angle-resolved photoemission, we directly observe an electronic band reconstruction across the insulator-metal (and magnetic) transition in the recently discovered CMR compound EuCd2P2. This transition is manifested by a large magnetic band splitting associated with the magnetic order, as well as unusual energy shifts of the valence bands: both the large ordered moment of Eu and carrier localization in the paramagnetic phase are crucial. Our results provide spectroscopic evidence for an electronic structure reconstruction underlying the enormous CMR observed in EuCd2P2, which could be important for understanding Eu-based CMR materials, as well as designing CMR materials based on large-moment rare-earth magnets. △ Less

Submitted 31 August, 2023; originally announced August 2023.

Comments: 6 pages, 4 figures

Journal ref: Phys. Rev. B 108, L241115 (2023)

Magnetism and berry phase manipulation in an emergent structure of perovskite ruthenate by (111) strain engineering

Authors: Zhaoqing Ding, Xuejiao Chen, Zhenzhen Wang, Qinghua Zhang, Fang Yang, Jiachang Bi, Ting Lin, Zhen Wang, Xiaofeng Wu, Minghui Gu, Meng Meng, Yanwei Cao, Lin Gu, Jiandi Zhang, Zhicheng Zhong, Xiaoran Liu, Jiandong Guo

Abstract: The interplay among symmetry of lattices, electronic correlations, and Berry phase of the Bloch states in solids has led to fascinating quantum phases of matter. A prototypical system is the magnetic Weyl candidate SrRuO3, where designing and creating electronic and topological properties on artificial lattice geometry is highly demanded yet remains elusive. Here, we establish an emergent trigonal… ▽ More The interplay among symmetry of lattices, electronic correlations, and Berry phase of the Bloch states in solids has led to fascinating quantum phases of matter. A prototypical system is the magnetic Weyl candidate SrRuO3, where designing and creating electronic and topological properties on artificial lattice geometry is highly demanded yet remains elusive. Here, we establish an emergent trigonal structure of SrRuO3 by means of heteroepitaxial strain engineering along the [111] crystallographic axis. Distinctive from bulk, the trigonal SrRuO3 exhibits a peculiar XY-type ferromagnetic ground state, with the coexistence of high-mobility holes likely from linear Weyl bands and low-mobility electrons from normal quadratic bands as carriers. The presence of Weyl nodes are further corroborated by capturing intrinsic anomalous Hall effect, acting as momentum-space sources of Berry curvatures. The experimental observations are consistent with our first-principles calculations, shedding light on the detailed band topology of trigonal SrRuO3 with multiple pairs of Weyl nodes near the Fermi level. Our findings signify the essence of magnetism and Berry phase manipulation via lattice design and pave the way towards unveiling nontrivial correlated topological phenomena. △ Less

Submitted 26 August, 2023; originally announced August 2023.

Active learning of effective Hamiltonian for super-large-scale atomic structures

Authors: Xingyue Ma, Hongying Chen, Ri He, Zhanbo Yu, Sergei Prokhorenko, Zheng Wen, Zhicheng Zhong, Jorge Iñiguez, L. Bellaiche, Di Wu, Yurong Yang

Abstract: The first-principles-based effective Hamiltonian scheme provides one of the most accurate modeling technique for large-scale structures, especially for ferroelectrics. However, the parameterization of the effective Hamiltonian is complicated and can be difficult for some complex systems such as high-entropy perovskites. Here, we propose a general form of effective Hamiltonian and develop an active… ▽ More The first-principles-based effective Hamiltonian scheme provides one of the most accurate modeling technique for large-scale structures, especially for ferroelectrics. However, the parameterization of the effective Hamiltonian is complicated and can be difficult for some complex systems such as high-entropy perovskites. Here, we propose a general form of effective Hamiltonian and develop an active machine learning approach to parameterize the effective Hamiltonian based on Bayesian linear regression. The parameterization is employed in molecular dynamics simulations with the prediction of energy, forces, stress and their uncertainties at each step, which decides whether first-principles calculations are executed to retrain the parameters. Structures of BaTiO$_3$, Pb(Zr$_{0.75}$Ti$_{0.25}$)O$_3$ and (Pb,Sr)TiO$_3$ system are taken as examples to show the accuracy of this approach, as compared with conventional parametrization method and experiments. This machine learning approach provides a universal and automatic way to compute the effective Hamiltonian parameters for any considered complex systems with super-large-scale (more than $10^7$ atoms) atomic structures. △ Less

Submitted 14 May, 2024; v1 submitted 17 July, 2023; originally announced July 2023.

Comments: 11 pages, 4 figures

Charge and spin instabilities in superconducting La$_3$Ni$_2$O$_7$

Authors: Xuejiao Chen, Peiheng Jiang, Jie Li, Zhicheng Zhong, Yi Lu

Abstract: Motivated by the recent discovery of superconductivity in La$_3$Ni$_2$O$_7$ under high pressure, we explore its potential charge and spin instabilities through combined model analysis and first-principles calculations. Taking into account the small charge-transfer nature of high valence nickel, a fully correlated two-cluster model identifies a lattice-coupled charge instability characterized by su… ▽ More Motivated by the recent discovery of superconductivity in La$_3$Ni$_2$O$_7$ under high pressure, we explore its potential charge and spin instabilities through combined model analysis and first-principles calculations. Taking into account the small charge-transfer nature of high valence nickel, a fully correlated two-cluster model identifies a lattice-coupled charge instability characterized by substantial short-range fluctuations of oxygen holes. This instability is corroborated by density-functional-theory plus $U$ calculations that also reveal a strong tendency towards concurrent antiferromagnetic ordering. The charge, spin, and associated lattice instabilities are significantly suppressed with increasing external pressure, contributing to the emergence of superconductivity in pressurized La$_3$Ni$_2$O$_7$. Carrier doping is found to effectively suppress these instabilities, suggesting a viable strategy to stabilize a superconducting phase under ambient pressure. △ Less

Submitted 2 September, 2024; v1 submitted 14 July, 2023; originally announced July 2023.

Journal ref: Phys. Rev. B 111, 014515 (2025)

Sub-micrometer phonon mean free paths in metal-organic frameworks revealed by machine-learning molecular dynamics simulations

Authors: Penghua Ying, Ting Liang, Ke Xu, Jin Zhang, Jianbin Xu, Zheng Zhong, Zheyong Fan

Abstract: Metal-organic frameworks (MOFs) are a family of materials that have high porosity and structural tunability and hold great potential in various applications, many of which requiring a proper understanding of the thermal transport properties. Molecular dynamics (MD) simulations play an important role in characterizing the thermal transport properties of various materials. However, due to the comple… ▽ More Metal-organic frameworks (MOFs) are a family of materials that have high porosity and structural tunability and hold great potential in various applications, many of which requiring a proper understanding of the thermal transport properties. Molecular dynamics (MD) simulations play an important role in characterizing the thermal transport properties of various materials. However, due to the complexity of the structures, it is difficult to construct accurate empirical interatomic potentials for reliable MD simulations of MOFs. To this end, we develop a set of accurate yet highly efficient machine-learned potentials for three typical MOFs, including MOF-5, HKUST-1, and ZIF-8, using the neuroevolution potential approach as implemented in the GPUMD package, and perform extensive MD simulations to study thermal transport in the three MOFs. Although the lattice thermal conductivity (LTC) values of the three MOFs are all predicted to be smaller than 1 $\rm{W/(m\ K)}$ at room temperature, the phonon mean free paths (MFPs) are found to reach the sub-micrometer scale in the low-frequency region. As a consequence, the apparent LTC only converges to the diffusive limit for micrometer single crystals, which means that the LTC is heavily reduced in nanocrystalline MOFs. The sub-micrometer phonon MFPs are also found to be correlated with a moderate temperature dependence of LTC between those in typical crystalline and amorphous materials. Both the large phonon MFPs and the moderate temperature dependence of LTC fundamentally change our understanding of thermal transport in MOFs. △ Less

Submitted 3 June, 2023; originally announced June 2023.

Comments: 12 pages, 9 figures

Journal ref: ACS Appl.Mater.Interfaces, 2023,15, 36412

Zero-Point Quantum Diffusion of Proton in Hydrogen-rich Superconductor $LaH_{10}$

Authors: Xuejian Qin, Hongyu Wu, Guyong Shi, Chao Zhang, Peiheng Jiang, Zhicheng Zhong

Abstract: $LaH_{10}$, as a member of hydrogen-rich superconductors, has a superconducting critical temperature of 250 K at high pressures, which exhibits the possibility of solving the long-term goal of room temperature superconductivity. Considering the extreme pressure and low mass of hydrogen, the nuclear quantum effects in $LaH_{10}… ▽ More $LaH_{10}$, as a member of hydrogen-rich superconductors, has a superconducting critical temperature of 250 K at high pressures, which exhibits the possibility of solving the long-term goal of room temperature superconductivity. Considering the extreme pressure and low mass of hydrogen, the nuclear quantum effects in $LaH_{10}$ should be significant and have an impact on its various physical properties. Here, we adopt the method combines deep-potential (DP) and quantum thermal bath (QTB), which was verified to be able to account for quantum effects in high-accuracy large-scale molecular dynamics simulations. Our method can actually reproduce pressure-temperature phase diagrams of $LaH_{10}$ consistent with experimental and theoretical results. After incorporating quantum effects, the quantum fluctuation driven diffusion of proton is found even in the absence of thermal fluctuation near 0 K. The high mobility of proton is found to be compared to liquid, yet the structure of $LaH_{10}$ is still rigid. These results would greatly enrich our vision to study quantum behavior of hydrogen-rich superconductors. △ Less

Submitted 2 June, 2023; originally announced June 2023.

Comments: 7 pages, 6 figures

Unconventional ferroelectric domain switching dynamics in CuInP2S6 from first principles

Authors: Ri He, Hua Wang, Fucai Liu, Shi Liu, Houfang Liu, Zhicheng Zhong

Abstract: The switching dynamics of ferroelectric materials is a crucial intrinsic property which directly affects the operation and performance of ferroelectric devices. In conventional ferroelectric materials, the typical ferroelectric switching mechanism is governed by a universal process of domain wall motion. However, recent experiments indicate that Van der Waals ferroelectric CuInP2S6 possesses anoma… ▽ More The switching dynamics of ferroelectric materials is a crucial intrinsic property which directly affects the operation and performance of ferroelectric devices. In conventional ferroelectric materials, the typical ferroelectric switching mechanism is governed by a universal process of domain wall motion. However, recent experiments indicate that Van der Waals ferroelectric CuInP2S6 possesses anomalous polarization switching dynamics under an electric field. It is important to understand the switching dynamics, but it remains theoretically unexplored in CuInP2S6 due to the lack of description of its order-disorder phase transition characteristics by density functional theory. Here, we employ a machine-learning potential trained from the first principles density functional theory dataset to conduct the large-scale atomistic simulations of temperature-driven order-disorder ferroelectric phase transition in CuInP2S6. Most importantly, it is found that the electric field-driven polarization switching in CuInP2S6 is mediated by single Cu dipole flip, rather than conventional domain wall motion mechanism. This intrinsic unconventional switching behavior can be attributed to the competition between the energy barrier of domain wall motion and single dipole flip. △ Less

Submitted 14 May, 2023; originally announced May 2023.

A Perspective on Ferrons

Authors: G. E. W. Bauer, P. Tang, R. Iguchi, J. Xiao, K. Shen, Z. Zhong, T. Yu, S. M. Rezende, J. P. Heremans, K. Uchida

Abstract: The duality between electric and magnetic dipoles in electromagnetism only partly applies to condensed matter. In particular, the elementary excitations of the magnetic and ferroelectric orders, namely magnons and ferrons, respectively, have received asymmetric attention from the condensed matter community in the past. In this perspective, we introduce and summarize the current state of the buddin… ▽ More The duality between electric and magnetic dipoles in electromagnetism only partly applies to condensed matter. In particular, the elementary excitations of the magnetic and ferroelectric orders, namely magnons and ferrons, respectively, have received asymmetric attention from the condensed matter community in the past. In this perspective, we introduce and summarize the current state of the budding field of "ferronics" and speculate about its potential applications in thermal, information, and communication technology. △ Less

Submitted 24 February, 2023; originally announced February 2023.

Comments: To be published as invited "Perspective" in Physical Review Applied

Anomalous Nernst effect induced terahertz emission in a single ferromagnetic film

Authors: Zheng Feng, Wei Tan, Zuanming Jin, Yi-Jia Chen, Zhangfeng Zhong, Liang Zhang, Song Sun, Jin Tang, Yexing Jiang, Po-Hsun Wu, Jun Cheng, Bingfeng Miao, Haifeng Ding, Dacheng Wang, Yiming Zhu, Liang Guo, Sunmi Shin, Guohong Ma, Dazhi Hou, Ssu-Yen Huang

Abstract: By developing a bidirectional-pump terahertz (THz) emission spectroscopy, we reveal an anomalous Nernst effect (ANE) induced THz emission in a single ferromagnetic film. Based on the distinctive symmetry of the THz signals, ANE is unequivocally distinguished from the previously attributed ultrafast demagnetization and anomalous Hall effect mechanisms. A quantitative method is established to separa… ▽ More By developing a bidirectional-pump terahertz (THz) emission spectroscopy, we reveal an anomalous Nernst effect (ANE) induced THz emission in a single ferromagnetic film. Based on the distinctive symmetry of the THz signals, ANE is unequivocally distinguished from the previously attributed ultrafast demagnetization and anomalous Hall effect mechanisms. A quantitative method is established to separate the different contributions, demonstrating a significant ANE contribution that even overwhelms other competing mechanisms. Our work not only clarifies the origin of the ferromagnetic-based THz emission, but also offers a fertile platform for investigating the ultrafast magnetism and THz spintronics. △ Less

Submitted 16 June, 2023; v1 submitted 21 February, 2023; originally announced February 2023.

Ultrafast switching dynamics of the ferroelectric order in stacking-engineered ferroelectrics

Authors: Ri He, Bingwen Zhang, Hua Wang, Lei Li, Tang Ping, Gerrit Bauer, Zhicheng Zhong

Abstract: The recently discovered ferroelectricity of van der Waals bilayers offers an unconventional route to improve the performance of devices. Key parameters such as switching field and speed depend on the static and dynamic properties of domain walls (DWs). Here we theoretically explore the properties of textures in stacking-engineered ferroelectrics from first principles. Employing a machine-learning… ▽ More The recently discovered ferroelectricity of van der Waals bilayers offers an unconventional route to improve the performance of devices. Key parameters such as switching field and speed depend on the static and dynamic properties of domain walls (DWs). Here we theoretically explore the properties of textures in stacking-engineered ferroelectrics from first principles. Employing a machine-learning potential model, we present results of large-scale atomistic simulations of stacking DWs and Moiré structure of boron nitride bilayers. We predict that the competition between the switching barrier of stable ferroelectric states and the in-plane lattice distortion leads to a DW width of the order of ten nanometers. DWs motion reduces the critical ferroelectric switching field of a monodomain by two orders of magnitude, while high domain-wall velocities allow domain switching on a picosecond-timescale. The superior performance compared to conventional ferroelectrics (or ferromagnets) may enable ultrafast and power-saving non-volatile memories. By twisting the bilayer into a stacking Moiré structure, the ferroelectric transforms into a super-paraelectric since DWs move under ultralow electric fields. △ Less

Submitted 29 December, 2022; originally announced December 2022.

Elastic Valley Spin Controlled Chiral Coupling in Topological Valley Phononic Crystals

Authors: Jinfeng Zhao, Chenwen Yang, Weitao Yuan, Danmei Zhang, Yang Long, Yongdong Pan, Hong Chen, Zheng Zhong, Jie Ren

Abstract: Distinct from the phononic valley pseudo-spin, the real physical spin of elastic waves adds a novel tool-kit capable of envisaging the valley-spin physics of topological valley phononic crystals from a local viewpoint. Here, we report the observation of local elastic valley spin as well as the hidden elastic spin-valley locking mechanism overlooked before. We demonstrate that the selective one-way… ▽ More Distinct from the phononic valley pseudo-spin, the real physical spin of elastic waves adds a novel tool-kit capable of envisaging the valley-spin physics of topological valley phononic crystals from a local viewpoint. Here, we report the observation of local elastic valley spin as well as the hidden elastic spin-valley locking mechanism overlooked before. We demonstrate that the selective one-way routing of valley phonon states along the topological interface can be reversed by imposing the elastic spin meta-source at different interface locations with opposite valley-spin correspondence. We unveil the physical mechanism of selective directionality as the elastic spin controlled chiral coupling of valley phonon states, through both analytical theory and experimental measurement of the opposite local elastic spin density at different interface locations for different transport directions. The elastic spin of valley topological edge phonons can be extended to other topological states and offers new tool to explore topological metamaterials. △ Less

Submitted 24 November, 2022; originally announced November 2022.

Comments: 5 pages, 3 figures, of main text + supplementary 10 figures. To be published in Phys. Rev. Lett

Large-scale Atomistic Simulation of Quantum Effects in SrTiO$_3$ from First Principles

Authors: Hongyu Wu, Ri He, Yi Lu, Zhicheng Zhong

Abstract: Quantum effects of lattice vibration play a major role in many physical properties of condensed matter systems, including thermal properties such as specific heat, structural phase transition, as well as phenomena such as quantum crystal and quantum paraelectricity that are closely related to zero-point fluctuations. However, realizing atomistic simulations for realistic materials with a fully qua… ▽ More Quantum effects of lattice vibration play a major role in many physical properties of condensed matter systems, including thermal properties such as specific heat, structural phase transition, as well as phenomena such as quantum crystal and quantum paraelectricity that are closely related to zero-point fluctuations. However, realizing atomistic simulations for realistic materials with a fully quantum-mechanical description remains a great challenge. Here, we propose a first-principle strategy for large scale Molecular Dynamics simulation, where high accuracy force field obtained by Deep-Potential (DP) is combined with Quantum Thermal Bath (QTB) method to account for quantum effects. We demonstrate the power of this DP+QTB method using the archetypal example SrTiO$_3$, which exhibits several phenomena induced by quantum fluctuations, such as the suppressed structure phase transition temperature, the quantum paraelectric ground state at low temperature and the quantum critical behavior $1/T^2$ law of dielectric constant. Our DP+QTB strategy is efficient in simulating large scale system, and is first principle. More importantly, quantum effects of other systems could also be investigated as long as corresponding DP model is trained. This strategy would greatly enrich our vision and means to study quantum behavior of condensed matter physics. △ Less

Submitted 15 November, 2022; originally announced November 2022.

Comments: 8 pages, 6 figures

Hybrid nano-domain structures of organic-inorganic perovskites from molecule-cage coupling effects

Authors: Ping Tuo, Lei Li, Xiaoxu Wang, Bo Xu, Jianhui Chen, Zhicheng Zhong, Fu-Zhi Dai

Abstract: In hybrid perovskites, the organic molecules and inorganic frameworks exhibit distinct static and dynamic characteristics. Their coupling will lead to unprecedented phenomena, which have attracted wide research interests. In this paper, we employed Deep Potential molecular dynamics (DPMD), a large-scale MD simulation scheme with DFT accuracy, to study $\mathrm{FA/MAPbI_3}$ hybrid perovskites. A sp… ▽ More In hybrid perovskites, the organic molecules and inorganic frameworks exhibit distinct static and dynamic characteristics. Their coupling will lead to unprecedented phenomena, which have attracted wide research interests. In this paper, we employed Deep Potential molecular dynamics (DPMD), a large-scale MD simulation scheme with DFT accuracy, to study $\mathrm{FA/MAPbI_3}$ hybrid perovskites. A spontaneous hybrid nano-domain behavior, namely multiple molecular rotation nano-domains embedded into a single $\mathrm{[PbI_6]^{4-}}$ octahedra rotation domain, was firstly discovered at low temperatures. The behavior originates from the interplay between the long range order of molecular rotation and local lattice deformation, and clarifies the puzzling diffraction patterns of $\mathrm{FAPbI_3}$ at low temperatures. Our work provides new insights into the structural characteristics and stability of hybrid perovskite, as well as new ideas for the structural characterization of organic-inorganic coupled systems. △ Less

Submitted 27 September, 2022; v1 submitted 26 September, 2022; originally announced September 2022.

Large-scale atomistic simulation of dislocation core structure in face-centered cubic metal with Deep Potential method

Authors: Fenglin Deng, Hongyu Wu, Ri He, Peijun Yang, Zhicheng Zhong

Abstract: The core structure of dislocations is critical to their mobility, cross slip, and other plastic behaviors. Atomistic simulation of the core structure is limited by the size of first-principles density functional theory (DFT) calculation and the accuracy of classical molecular dynamics with empirical interatomic potentials. Here, we utilize a Deep Potential (DP) method learned from DFT calculations… ▽ More The core structure of dislocations is critical to their mobility, cross slip, and other plastic behaviors. Atomistic simulation of the core structure is limited by the size of first-principles density functional theory (DFT) calculation and the accuracy of classical molecular dynamics with empirical interatomic potentials. Here, we utilize a Deep Potential (DP) method learned from DFT calculations to investigate the dislocations of face-centered cubic copper on a large scale and obtain their core structures and energies. The validity of the DP description of the core structure and elastic strain from dislocation is confirmed by a fully discrete Peierls model. Moreover, the DP method can be further extended easily to dislocations with defects such as surface or vacancy, and our study will pave a way in the large-scale atomistic simulation of dislocation on the DFT level. △ Less

Submitted 11 September, 2022; originally announced September 2022.

Origin of negative thermal expansion and pressure induced amorphization in zirconium tungstate from machine-learning potential

Authors: Ri He, Hongyu Wu, Yi Lu, Zhicheng Zhong

Abstract: Understanding various macroscopic pressure-volume-temperature properties of materials on the atomistic level has always been an ambition for physicists and material scientists. Particularly, some materials such as zirconium tungstate (ZrW2O8), exhibit multiple exotic properties including negative thermal expansion (NTE) and pressure-induced amorphization (PIA). Here, using machine-learning based d… ▽ More Understanding various macroscopic pressure-volume-temperature properties of materials on the atomistic level has always been an ambition for physicists and material scientists. Particularly, some materials such as zirconium tungstate (ZrW2O8), exhibit multiple exotic properties including negative thermal expansion (NTE) and pressure-induced amorphization (PIA). Here, using machine-learning based deep potential, we trace both of the phenomena in ZrW2O8 back to a common atomistic origin, where the nonbridging O atoms play a critical role. We demonstrate that the nonbridging O atoms confer great flexibility to vibration of polyhedrons, and kinetically drive volume shrinking on heating, or NTE. In addition, beyond a certain critical pressure, we find that the migration of nonbridging O atoms leads to additional bond formation that lowers the potential energy, suggesting that the PIA is a potential-driven first-order phase transition. Most importantly, we identify a second critical pressure beyond which the amorphous phase of ZrW2O8 undergoes a hidden phase transition from a reversible phase to an irreversible one. △ Less

Submitted 4 August, 2022; originally announced August 2022.

Magnetism in doped infinite-layer NdNiO2 studied by combined density functional theory and dynamical mean-field theory

Authors: Dachuan Chen, Peiheng Jiang, Liang Si, Yi Lu, Zhicheng Zhong

Abstract: The recent observation of superconductivity in infinite-layer nickelates has brought intense debate on the established knowledge of unconventional superconductivity based on the cuprates. Despite many similarities, the nickelates differ from the cuprates in many characteristics, the most notable one among which is the magnetism. Instead of a canonical antiferromagnetic Mott insulator as the undope… ▽ More The recent observation of superconductivity in infinite-layer nickelates has brought intense debate on the established knowledge of unconventional superconductivity based on the cuprates. Despite many similarities, the nickelates differ from the cuprates in many characteristics, the most notable one among which is the magnetism. Instead of a canonical antiferromagnetic Mott insulator as the undoped cuprates, from which the superconductivity is generally believed to arise upon doping, the undoped nickelates show no sign of magnetic ordering in experiments. Through a combined density functional theory, dynamical mean-field theory, and model study, we show that although the increased energy splitting between O-$p$ orbital and Cu/Ni-$d$ orbital ($Δ_{dp}$) results in larger magnetic moment in nickelates, it also leads to stronger antiferromagnetism/ferromagnetism competition, and weaker magnetic exchange coupling. Meanwhile, the self-doping effect caused by Nd-$d$ orbital screens the magnetic moment of Ni. The Janus-faced effect of $Δ_{dp}$ and self-doping effect together give a systematic understanding of magnetic behavior in nickelates and explain recent experimental observations. △ Less

Submitted 10 July, 2022; v1 submitted 20 June, 2022; originally announced June 2022.

Comments: 10 pages, 9 figures

Journal ref: Phys. Rev. B.106,045105(2022)

Magnetic tuning of band topology evidenced by exotic quantum oscillations in the Dirac semimetal EuMnSb$_2$

Authors: Kan Zhao, Xuejiao Chen, Zhaosheng Wang, Jinyu Liu, Jiating Wu, Chuanying Xi, Xiaodong Lv, Lei Li, Zhicheng Zhong, Philipp Gegenwart

Abstract: Interplay between magnetism and electronic band topology is of central current interest in topological matter research. We use quantum oscillations as powerful tool to probe the evolution of band topology in the Dirac semimetal EuMnSb$_2$. The Eu local 4f magnetic moments display different antiferromagnetic states below 25 K and a field-polarized phase above 16 T. Upon cooling from 65 K into the f… ▽ More Interplay between magnetism and electronic band topology is of central current interest in topological matter research. We use quantum oscillations as powerful tool to probe the evolution of band topology in the Dirac semimetal EuMnSb$_2$. The Eu local 4f magnetic moments display different antiferromagnetic states below 25 K and a field-polarized phase above 16 T. Upon cooling from 65 K into the field-polarized state, an exotic temperature dependent shift of oscillation peaks arises, accompanied by the development of non-zero Berry phase and a huge unconventional splitting of the oscillations. Band-structure calculations confirm the change from trivial to non-trivial band topology induced by the ferromagnetic Eu state, classifying EuMnSb$_2$ as unique magnetic topological semimetal. △ Less

Submitted 12 February, 2023; v1 submitted 25 May, 2022; originally announced May 2022.

Comments: Spin degeneracy splitting of the Dirac band evidenced by high field SdH oscillations; Accepted for publication as Letter in PRB

Journal ref: Phys. Rev. B 107, L081112 (2023)

GPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations

Authors: Zheyong Fan, Yanzhou Wang, Penghua Ying, Keke Song, Junjie Wang, Yong Wang, Zezhu Zeng, Ke Xu, Eric Lindgren, J. Magnus Rahm, Alexander J. Gabourie, Jiahui Liu, Haikuan Dong, Jianyang Wu, Yue Chen, Zheng Zhong, Jian Sun, Paul Erhart, Yanjing Su, Tapio Ala-Nissila

Abstract: We present our latest advancements of machine-learned potentials (MLPs) based on the neuroevolution potential (NEP) framework introduced in [Fan et al., Phys. Rev. B 104, 104309 (2021)] and their implementation in the open-source package GPUMD. We increase the accuracy of NEP models both by improving the radial functions in the atomic-environment descriptor using a linear combination of Chebyshev… ▽ More We present our latest advancements of machine-learned potentials (MLPs) based on the neuroevolution potential (NEP) framework introduced in [Fan et al., Phys. Rev. B 104, 104309 (2021)] and their implementation in the open-source package GPUMD. We increase the accuracy of NEP models both by improving the radial functions in the atomic-environment descriptor using a linear combination of Chebyshev basis functions and by extending the angular descriptor with some four-body and five-body contributions as in the atomic cluster expansion approach. We also detail our efficient implementation of the NEP approach in graphics processing units as well as our workflow for the construction of NEP models, and we demonstrate their application in large-scale atomistic simulations. By comparing to state-of-the-art MLPs, we show that the NEP approach not only achieves above-average accuracy but also is far more computationally efficient. These results demonstrate that the GPUMD package is a promising tool for solving challenging problems requiring highly accurate, large-scale atomistic simulations. To enable the construction of MLPs using a minimal training set, we propose an active-learning scheme based on the latent space of a pre-trained NEP model. Finally, we introduce three separate Python packages, GPYUMD, CALORINE, and PYNEP, which enable the integration of GPUMD into Python workflows. △ Less

Submitted 29 June, 2022; v1 submitted 20 May, 2022; originally announced May 2022.

Comments: 29 pages, 15 figures, code and data available

Journal ref: Journal of Chemical Physics 157, 114801 (2022)

Pressure-induced ideal Weyl semimetal state in the layered antiferromagnet EuCd2As2

Authors: Zhenhai Yu1, Xuejiao Chen, Wei Xia, Ningning Wang, Xiaodong Lv, Xiaolei Liu, Hao Su, Zhongyang Li, Desheng Wu, Wei Wu, Ziyi Liu, Jinggeng Zhao, Mingtao Li, Shujia Li, Xin Li, Zhaohui Dong, Chunyin Zhou, Lili Zhang, Xia Wang, Na Yu, Zhiqiang Zou, Jianlin Luo, Jinguang Cheng, Lin Wang, Zhicheng Zhong , et al. (1 additional authors not shown)

Abstract: The rich nontrivial topological phases rooted in the interplay between magnetism and topology in the layered antiferromagnet EuCd2As2 have captured vast attention, especially the ideal Weyl semimetal state realized in the spin-polarized ferromagnetic (FM) structure driven by a moderate external magnetic field. In this work, combining high-pressure magnetotransport measurements, structure chracteri… ▽ More The rich nontrivial topological phases rooted in the interplay between magnetism and topology in the layered antiferromagnet EuCd2As2 have captured vast attention, especially the ideal Weyl semimetal state realized in the spin-polarized ferromagnetic (FM) structure driven by a moderate external magnetic field. In this work, combining high-pressure magnetotransport measurements, structure chracterizations and first principles calculations, we find that application of pressure can also realize the ideal Weyl state in EuCd2As2 through driving the in-plane antiferromagnetic state across an intermediate in-plane FM state then into the out-of-plane FM state. Our high-pressure angle dispersive X-ray diffraction and X-ray absorption near-edge spectroscopy measurements excluded structure transition and/or change of Eu2+ valence state as the sources for the magnetic phase transitions. Alternatively, the apparently reduced axial ratio (c/a) and compressed Eu-layer space distance should play important roles. Our result provides an alternative way to realize the ideal Weyl semimetal state in EuCd2As2 and would be instructive for the exploration of exotic topological properties in such layered magnetic topological phase with strongly competing magnetic exchanges by using high pressure. △ Less

Submitted 12 February, 2022; originally announced February 2022.

Comments: main text 16 pages,4 figures and SI 8 pages, 4 figures

Journal ref: Advanced Quantum Technologies 2023, 6: 2200128

Structural Phase Transitions in SrTiO3 from Deep Potential Molecular Dynamics

Authors: Ri He, Hongyu Wu, Linfeng Zhang, Xiaoxu Wang, Fangjia Fu, Shi Liu, Zhicheng Zhong

Abstract: Strontium titanate (SrTiO3) is regarded as an essential material for oxide electronics. One of its many remarkable features is subtle structural phase transition, driven by antiferrodistortive lattice mode, from a high-temperature cubic phase to a low-temperature tetragonal phase. Classical molecular dynamics (MD) simulation is an efficient technique to reveal atomistic features of phase transitio… ▽ More Strontium titanate (SrTiO3) is regarded as an essential material for oxide electronics. One of its many remarkable features is subtle structural phase transition, driven by antiferrodistortive lattice mode, from a high-temperature cubic phase to a low-temperature tetragonal phase. Classical molecular dynamics (MD) simulation is an efficient technique to reveal atomistic features of phase transition, but its application is often limited by the accuracy of empirical interatomic potentials. Here, we develop an accurate deep potential (DP) model of SrTiO3 based on a machine learning method using data from first-principles density functional theory (DFT) calculations. The DP model has DFT-level accuracy, capable of performing efficient MD simulations and accurate property predictions. Using the DP model, we investigate the temperature-driven cubic-to-tetragonal phase transition and construct the in-plane biaxial strain-temperature phase diagram of SrTiO3. The simulations demonstrate that strain-induced ferroelectric phase is characterized by two order parameters, ferroelectric distortion and antiferrodistortion, and the ferroelectric phase transition has both displacive and order-disorder characters. This works lays the foundation for the development of accurate DP models of other complex perovskite materials. △ Less

Submitted 18 January, 2022; originally announced January 2022.