arXiv subjects

Ri He

Publications and source records attributed to Ri He.

At least 19 recordsLinked to original sources

arXiv2026

Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics

Ferroelectric materials with switchable spontaneous polarization underpin non-volatile memories, transistors, sensors, and emerging neuromorphic chips. Their performance and stability are governed by polarization dynamics and domain kinetics, making a microscopic understanding of these processes and precise atomic level control of polarization domains key challenges for next-generation ferroelectric electronics. Due to the limitations of the characterization technology with atomic level in experiment, high precision atomic simulations become important. First principles calculations are inherently limited in accessible length and time scales, making it difficult to capture the complex features of dynamic processes. Machine learning molecular dynamics (MLMD) offers a compelling solution by encoding quantum-mechanical accuracy into force fields, thereby enabling large scale dynamic simulations with near first-principles fidelity. This Perspective highlights the advantages of MLMD for simulating polarization switching, domain nucleation and migration, topological polar textures and curvature-driven ferroelectric phenomena, while providing a systematic overview of recent progress in these areas. We further discuss methodological challenges that limit predictive capability, including long range electrostatics, coupled lattice-spin degrees of freedom in multiferroics, and data efficient pre-training of large atomistic models. Corresponding advances in long range aware force fields, spin dependent machine learning models, and large scale pretraining are expected to move MLMD toward a genuinely predictive framework for the design of ferroelectric and multiferroic materials.

cond-mat.mtrl-sci↗

arXiv2025

Superconducting Diode Effect in Gradiently Strained Nb0.5Ti0.5N Films

The superconducting diode effect (SDE), combining superconductivity with diode-like nonreciprocal current flow, recently emerges as an ideal candidate for zero-dissipation electronic circuits. Such technologically advantageous diodes are achieved by intricate material engineering to disrupt inversion symmetry, which leads to the production challenges as well as a limited pool of viable materials. Here we exploit the gradient interfacial strain to experimentally induce the SDE in Nb0.5Ti0.5N (NTN) films grown on MgO substrates. Additionally, the SDE is tunable with an in-plane magnetic field and can be further enhanced by introducing an interfacial anisotropic pinning potential. Our findings establish interfacial strain gradient as a versatile tool for creating and enhancing tunable SDE.

cond-mat.supr-con↗

arXiv2025

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

The metal-insulator transition (MIT) in rare-earth nickelates exemplifies the intricate coupling between lattice dynamics and electronic effects. This strong interplay makes it challenging to disentangle their individual roles in driving the transition in RNiO3. Here, we isolate the structure response from electronic effect by employing molecular dynamics (MD) simulations based on a machine-learned interatomic potential. Taking SmNiO3 as a prototypical system, our simulations show that the structural phase transition is intrinsically temperature-driven and occurs spontaneously via collective lattice distortions. The simulated critical temperature is 340 K and can be further tuned by pressure. These findings provide atomistic insights into the understanding of structural evolution in triggering the phase transition and hence the MIT in RNiO3.

cond-mat.mtrl-sci↗

arXiv2025

Undamped Soliton-like Domain Wall Motion in Sliding Ferroelectrics

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.

cond-mat.mtrl-sci↗

arXiv2024

Domain-Pair Intertwined Topological Domain Structure in Elemental Bi Monolayer

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{\deg} 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{\deg} 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{\deg} domain walls form local domain pairs, with the 90{\deg} domain walls emerge between different domain pairs. This multi-domain maintains a stable topological structure within the strain range ({\epsilon}_x = 0 to 4.70%) and exhibits rich domain wall reactions under further applied strain. Our findings provide insights into the charged 180{\deg} domain walls and the related topological domain structures, enabling new opportunities for applications in electronic and nano-electronic devices.

cond-mat.mtrl-sci↗

arXiv2024

Spontaneous curvature in two-dimensional van der Waals heterostructures

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.

cond-mat.mtrl-sci↗

arXiv2024

Sliding Flexoelectricity in Two-Dimensional van der Waals Systems

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.

cond-mat.mtrl-sci↗

arXiv2024

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

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.

cond-mat.mtrl-sci↗

arXiv2024

Giant third-order nonlinear Hall effect in misfit layer compound (SnS)${1.17}$(NbS$_2$)$_3$

Nonlinear Hall effect (NLHE) holds immense significance in recognizing the band geometry and its potential applications in current rectification. Recent discoveries have expanded the study from second-order to third-order nonlinear Hall effect (THE), which is governed by an intrinsic band geometric quantity called the Berry Connection Polarizability (BCP) tensor. Here we demonstrate a giant THE in a misfit layer compound, (SnS)${1.17}$(NbS$_2$)$_3$. While the THE is prohibited in individual NbS$_2$ and SnS due to the constraints imposed by the crystal symmetry and their band structures, a remarkable THE emerges when a superlattice is formed by introducing a monolayer of SnS. The angular-dependent THE and its scaling relationship indicate that the phenomenon could be correlated to the band geometry modulation, concurrently with the symmetry breaking. The resulting strength of THE is orders of magnitude higher compared to recent studies. Our work illuminates the modulation of structural and electronic geometries for novel quantum phenomena through interface engineering.

cond-mat.mes-hall↗

arXiv2023

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

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.

cond-mat.mtrl-sci↗

arXiv2023

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

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.

cond-mat.mtrl-sci↗

arXiv2023

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

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.

cond-mat.mtrl-sci↗

arXiv2023

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

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.

cond-mat.mtrl-sci↗

arXiv2023

Atomistic simulations of thermodynamic properties of liquid gallium from first principles

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.

cond-mat.mtrl-sci↗

arXiv2023

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

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.

cond-mat.mtrl-sci↗

arXiv2023

Unconventional ferroelectric domain switching dynamics in CuInP2S6 from first principles

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.

cond-mat.mtrl-sci↗

arXiv2022

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

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 Moir\'e 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 Moir\'e structure, the ferroelectric transforms into a super-paraelectric since DWs move under ultralow electric fields.

cond-mat.mtrl-sci↗

arXiv2022

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

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.

cond-mat.mtrl-sci↗