论文标题
部分可观测时空混沌系统的无模型预测
Finite temperature dielectric properties of KTaO$_3$ from first principles and machine learning: Phonon spectra, Barrett law, strain engineering and electrostriction
论文作者
论文摘要
尽管在过去十年中取得了重要的突破，但固体依赖性特性的计算仍然是一项具有挑战性的任务，尤其是在结构相变的附近。我们表明，机器学习间的跨质量晶格动力学的组合可以有效地计算量子peraelectric Perovskite ktao $ _3 $的介电特性的温度依赖性，并且具有合理的精确度，超越了使用普通密度的功能功能的精确度。我们首先遵循这种初期的铁电材料中极性模式的强烈无声软化，以及由于温度和量子波动之间的相互作用而最终饱和的介电常数的差异。此外，我们预测在0 K和300 K处使用外延应变下的量子副膜状态的稳定性范围。
Despite important breakthroughs in the last decade, the calculation of temperature dependent properties of solids still remains a challenging task, especially in the vicinity of structural phase transitions. We show that the combination of machine-learning interatomic potentials with quantum self-consistent ab initio lattice dynamics allows to calculate efficiently the temperature dependence of dielectric properties of the quantum paraelectric perovskite KTaO$_3$, with a precision beyond what could be reasonably achieved using plain density functional theory. We first follow the strong anharmonic softening of the polar mode in this incipient ferroelectric material, and the resulting divergence of the dielectric constant that eventually saturates due to the interplay between temperature and quantum fluctuations. Further, we predict the stability range of the quantum paraelectric state under the application of epitaxial strain at 0 K and 300 K. Finally, we calculate the temperature dependence of electrostrictive tensors for this material and show that giant electrostriction in KTaO$_3$ is to be expected also at room temperature under the condition of strain engineering.
