Related papers: Heat flux for semi-local machine-learning potentia…
Two metals at different temperatures separated by large gaps exchange heat under the form of electromagnetic radiation. When the separation distance is reduced and they approach contact (nanometer and sub-nanometer gaps), electrons and…
The thermal conductivity of classical multi-component fluids is seemingly affected by the intrinsic arbitrariness in the definition of the atomic energies and it is ill-conditioned numerically, when evaluated from the Green-Kubo theory of…
We consider chains consisting of several identical subsystems weakly coupled by various types of next neighbor interactions. At both ends the chain is coupled to a respective heat bath with different temperature modeled by a Lindblad…
This work is devoted to the \textit{ab initio} calculation of transport and optical properties of aluminum. The calculation is based on the quantum molecular dynamics simulation, density functional theory and the Kubo-Greenwood formula.…
There has been an arising trend of adopting deep learning methods to study partial differential equations (PDEs). This article is to propose a Deep Learning Galerkin Method (DGM) for the closed-loop geothermal system, which is a new coupled…
We discuss the foundations and extend the range of applicability of the widely used Kubo-Greenwood formula (KGF) for the electronic conductivity. The conductivity is derived from the current density, and only the probability amplitude…
We propose a method for learning constraints represented as Gaussian processes (GPs) from locally-optimal demonstrations. Our approach uses the Karush-Kuhn-Tucker (KKT) optimality conditions to determine where on the demonstrations the…
We study the transport properties of a large class of locally confined Hamiltonian systems, in which neighboring particles interact through hard core elastic collisions. When these collisions become rare and the systems large, we derive a…
The heat flux autocorrelation functions of carbon nanotubes (CNTs) with different radius and lengths is calculated using equilibrium molecular dynamics. The thermal conductance of CNTs is also calculated using the Green-Kubo relation from…
Molecular dynamics simulations are used to model the thermal properties of a fluid containing solid nanoparticles (nanofluid). The flexibility of molecular simulation allows us to consider the effects of particle mass, particle-particle and…
We study classical heat conduction in a dissipative open system composed of interacting oscillators. By exactly solving a twisted Fokker-Planck equation which describes the full counting statistics of heat flux flowing through the system,…
We re-derive the expression for the heat current for a classical system subject to periodic boundary conditions and show that it can be written as a sum of two terms. The first term is a time derivative of the first moment of the system…
We present a framework for transfer learning based on modular variational Gaussian processes (GP). We develop a module-based method that having a dictionary of well fitted GPs, one could build ensemble GP models without revisiting any data.…
A new formula to calculate the transport coefficients of the causal dissipative hydrodynamics is derived by using the projection operator method (Mori-Zwanzig formalism) in [T. Koide, Phys. Rev. E75, 060103(R) (2007)]. This is an extension…
The GW approach produces highly accurate quasiparticle energies, but its application to large systems is computationally challenging, which can be largely attributed to the difficulty in computing the inverse dielectric matrix. To address…
The large number of possible structures of metal-organic frameworks (MOFs) and their limitless potential applications has motivated molecular modelers and researchers to develop methods and models to efficiently assess MOF performance. Some…
The synchronized molecular dynamics simulation via macroscopic heat and momentum transfer is proposed for the non-isothermal flow behaviors of complex fluids. In this method, the molecular dynamics simulations are assigned to small fluid…
It is shown that the hydrodynamic modes of a dilute granular gas of inelastic hard spheres can be identified, and calculated in the long wavelength limit. Assuming they dominate at long times, formal expressions for the Navier-Stokes…
Heatwaves are an important problem in cities, and climate change makes this problem more difficult. In this paper, we present a GPU-based deep learning framework for next-day prediction of urban thermal conditions and for heat risk…
Networks of interconnected resistors, springs and beams, or pores are standard models of studying scalar and vector transport processes in heterogeneous materials and media, such as fluid flow in porous media, and conduction, deformations,…