A Graph Dynamical neural network approach for decoding dynamical states in ferroelectrics.

Dhakane, Abhijeet; Xie, Tian; Yılmaz, Dündar E.; Duin, Adri van; Sumpter, Bobby G.; Ganesh, Panchapakesan

doi:10.1016/j.cartre.2023.100264

Cited by 3 publications

(1 citation statement)

References 40 publications

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“…1e provides a vertical PFM phase image overall the morphology of the (100) plane. The ferroelectric domains manifest as spike-like patterns that reflect distinct polarization orientations 30 . The PFM amplitude images acquired simultaneously are shown in Supplementary Fig.…”

Section: Resultsmentioning

confidence: 99%

Molecular ferroelectric with low-magnetic-field magnetoelectricity at room temperature

Hu,

Yang,

Zhang

et al. 2024

Nat Commun

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Magnetoelectric materials, which encompass coupled magnetic and electric polarizabilities within a single phase, hold great promises for magnetic controlled electronic components or electric-field controlled spintronics. However, the realization of ideal magnetoelectric materials remains tough due to the inborn competion between ferroelectricity and magnetism in both levels of symmetry and electronic structure. Herein, we introduce a methodology for constructing single phase paramagnetic ferroelectric molecule [TMCM][FeCl4], which shows low-magnetic-field magnetoelectricity at room temperature. By applying a low magnetic field (≤1 kOe), the halogen Cl‧‧‧Cl distance and the volume of [FeCl4]− anions could be manipulated. This structural change causes a characteristic magnetostriction hysteresis, resulting in a substantial deformation of ~10−4 along the a-axis under an in-plane magnetic field of 2 kOe. The magnetostrictive effect is further qualitatively simulated by density functional theory calculations. Furthermore, this mechanical deformation significantly dampens the ferroelectric polarization by directly influencing the overall dipole configuration. As a result, it induces a remarkable α31 component (~89 mV Oe−1 cm−1) of the magnetoelectric tensor. And the magnetoelectric coupling, characterized by the change of polarization, reaches ~12% under 40 kOe magnetic field. Our results exemplify a design methodology that enables the creation of room-temperature magnetoelectrics by leveraging the potent effects of magnetostriction.

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Section: Resultsmentioning

confidence: 99%

Molecular ferroelectric with low-magnetic-field magnetoelectricity at room temperature

Hu,

Yang,

Zhang

et al. 2024

Nat Commun

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Asymmetric Domain Nucleation from Dislocation Core in Barium Titanate: Molecular Dynamics Simulation Using Machine‐Learning Potential through Active Learning

Deguchi,

Kobayashi,

Azuma

et al. 2023

Physica Rapid Research Ltrs

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Barium titanate (BaTiO3) is a ferroelectric material without toxic elements, whose ferroelectric properties such as permittivity, coercive field, and spontaneous polarization are affected by the nucleation of domains of reversed polarization and the motion of domain walls. Dislocations can act as obstacles to domain‐wall migration or as active sites for domain nucleation. Thus, studies are conducted on the utilization of dislocations to improve the ferroelectric properties of BaTiO3. However, the atomistic mechanism of domain nucleation around the dislocation core is still unclear. In this article, a machine learning (ML) potential is developed to study the influence of dislocations on domain nucleation. The potential is trained using an active‐learning approach to ensure accuracy in the bulk properties of the ferroelectric and paraelectric phases, as well as in the dislocation core structures in BaTiO3. Molecular dynamics simulations using the ML potential show that the influence of dislocations on polarization reversal depends on the directional relationship between the external electric field and the dislocation. Furthermore, strong local polarizations exist surrounding the dislocation core, owing to vacancies in the core. These polarizations can act as both domain nucleation sites and obstacles for domain migration when ordered along the dislocation line.

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Advancing wastewater treatment from cadmium contamination via functionalized graphene nanosheets

Khalajiolyaie,

Jian

2024

Journal of Water Process Engineering

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A Graph Dynamical neural network approach for decoding dynamical states in ferroelectrics.

Cited by 3 publications

References 40 publications

Molecular ferroelectric with low-magnetic-field magnetoelectricity at room temperature

Molecular ferroelectric with low-magnetic-field magnetoelectricity at room temperature

Asymmetric Domain Nucleation from Dislocation Core in Barium Titanate: Molecular Dynamics Simulation Using Machine‐Learning Potential through Active Learning

Advancing wastewater treatment from cadmium contamination via functionalized graphene nanosheets

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