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Yubai Shi

Publications and source records attributed to Yubai Shi.

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Intrinsic structure of relaxor ferroelectrics from first principles

We develop FIRE-Swap, a first-principles framework for sampling intrinsic compositional structures in complex perovskites with machine-learning interatomic potentials (MLIPs). Using both dedicated and universal MLIPs, we study the relaxor lead magnesium niobate (PMN) and the solid solutions lead zirconate titanate (PZT) and lead strontium titanate (PST). Across MLIP models and exchange-correlation approximations, FIRE-Swap robustly predicts a rock-salt-like chemical order in PMN, which is absent in PZT and PST with the same mixing ratio, consistent with experiments. We further identify in PMN a distinct Nb-cluster morphology. Interconnected, non-coarsened polar nanoregions are found within Nb clusters, providing a mesoscale basis for understanding relaxor ferroelectricity.

cond-mat.mtrl-sci

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

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

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

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