论文标题
部分可观测时空混沌系统的无模型预测
Softened sp2-sp3 bonding network leads to strong anharmonicity and weak hydrodynamics in graphene+
论文作者
论文摘要
储层计算是预测湍流的有力工具,其简单的架构具有处理大型系统的计算效率。然而,其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间,然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用,该系统模拟了湍流的若干特征。我们表明,使用径向基函数作为非线性投影器,即使只有部分观测并且不知道控制方程,也能稳健地捕捉复杂的系统非线性。最后,我们表明,当测量稀疏、不完整且带有噪声,甚至控制方程变得不准确时,我们的网络仍然可以产生相当准确的预测,从而为实际湍流系统的无模型预测铺平了道路。
Graphene+, a novel carbon monolayer with sp2-sp3 hybridization, is recently reported to exhibit graphene-like Dirac properties and unprecedented out-of-plane half-auxetic behavior [Yu et al, Cell Reports Physical Science, 3 100790 (2022)]. Herein, from comprehensively state-of-the-art first-principles studies, we report the exceptional lattice thermal transport properties of graphene+ driven by the unique sp2-sp3 crystal configuration. At room temperature, the thermal conductivity of graphene+ is calculated to be ~170 W/mK, which is much lower than that of graphene (~3170 W/mK) Despite the buckling structure, weak phonon scattering phase space is trapped in graphene+. Thus, the reduction in thermal conductivity magnitude stems from soft bonding due to the unique sp2-sp3 crystal configuration. Soft bonding suppresses the vibrations of acoustic phonons, which leads to strong anharmonicity and weak phonon hydrodynamics. Further, lower group velocity, relaxation time and smaller phonon mean free path emerge in graphene+, and the significantly decreased thermal conductivity is achieved. Our study provides fundamental physical insights into the thermal transport properties of graphene+, and it serves as an ideal model to study atomic bonding versus thermal transport properties due to weak scattering phase space.