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For multi-layered 2D materials, although its c-axis has a much lower thermal conductivity than the a-axis, its phonon mean free path has been confirmed to be very long, e.g., in the order of 100s nm at room temperature for multi-layered graphene. An anisotropic specific heat concept has been proposed in the past to explain this very long mean free path. This work carries out detailed atomistic modeling to quantify the anisotropic specific heat concept and reports the discovery of anisotropic temperatures in multi-layered 2D materials under ultrafast surface heating. Extremely fast c-phonon energy transport is discovered, and the non-Fourier effect is observed for both a-phonons and c-phonons. The energy coupling factor between these two modes of phonons is determined to be in the order of 1016 W K−1 m−3, with the specific number depending on the structure location. The anisotropic temperature concept is also quantitatively confirmed based on the lattice Boltzmann method simulation. The anisotropic temperature concept does not violate the physics that temperature is a scalar; rather, it is developed to distinguish the temperatures of phonons that travel in different directions. This concept is universally applicable to other 2D materials to describe the heat conduction in the in-plane and out-of-plane directions that feature different interatomic bonds. 

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features, such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, DP-range correction, DP long range, graphics processing unit support for customized operators, model compression, non-von Neumann molecular dynamics, and improved usability, including documentation, compiled binary packages, graphical user interfaces, and application programming interfaces. This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, this article presents a comprehensive procedure for conducting molecular dynamics as a representative application, benchmarks the accuracy and efficiency of different models, and discusses ongoing developments.