Nonlinear flexoelectricity in extended thermodynamics

IF 2.2 3区 工程技术 Q2 MECHANICS
A. R. El-Dhaba, M. S. Abou-Dina, A. F. Ghaleb
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引用次数: 0

Abstract

A nonlinear phenomenological model of flexoelectricity in thermoelastic solids is presented within the frame of continuum mechanics and extended thermodynamics, incorporating the quasi-electrostatic approximation where the time derivative of the electric displacement vector can be neglected in Maxwell–Ampère’s law. An expression for the energy flux is proposed, including many internal variables. An advantage of the proposed model is that it presents a unified approach to study several thermo-electromechanical couplings, including electrostriction, piezoelectricity, dependence of entropy and spontaneous polarization on flexoelectricity, among others. The model may be of interest in revealing the effects of such couplings on the properties of polarizable media, in particular ferroelectrics, when simple boundary conditions prevail. For a fully dynamic description of flexoelectricity, Hamilton’s principle and the variational principle for external forces should be used instead.

扩展热力学中的非线性柔电性
在连续介质力学和扩展热力学的框架内,提出了热弹性固体中柔性电的非线性现象学模型,并结合了准静电近似,即在麦克斯韦-安培定律中可以忽略电位移矢量的时间导数。提出的能量通量表达式包括许多内部变量。所提模型的一个优点是,它提出了一种统一的方法来研究几种热机电耦合,包括电致伸缩、压电、熵和自发极化对挠电的依赖性等。当边界条件简单时,该模型可能有助于揭示此类耦合对可极化介质(尤其是铁电体)特性的影响。若要对挠性电进行完全动态的描述,则应使用汉密尔顿原理和外力变分原理。
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来源期刊
CiteScore
4.40
自引率
10.70%
发文量
234
审稿时长
4-8 weeks
期刊介绍: Archive of Applied Mechanics serves as a platform to communicate original research of scholarly value in all branches of theoretical and applied mechanics, i.e., in solid and fluid mechanics, dynamics and vibrations. It focuses on continuum mechanics in general, structural mechanics, biomechanics, micro- and nano-mechanics as well as hydrodynamics. In particular, the following topics are emphasised: thermodynamics of materials, material modeling, multi-physics, mechanical properties of materials, homogenisation, phase transitions, fracture and damage mechanics, vibration, wave propagation experimental mechanics as well as machine learning techniques in the context of applied mechanics.
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