Thermal conductivity of irregularly shaped nanoparticles from equilibrium molecular dynamics

The computation of thermal conductivity for finite nanoparticulate systems, particularly those of irregular shapes, poses significant challenges. The nonequilibrium molecular dynamics (NEMD) methods has been extensively utilized in numerous prior studies for the computation of thermal conductivity of nanoparticles. One of our recent works (Donget al2021Phys. Rev.B103035417) proposed that equilibrium molecular dynamics (EMD) methods can be used for the simulation of thermal conductivity of finite-scale systems and demonstrated their equivalence to NEMD methods. In this study, we investigated the application of the (EMD) approach for the computation of thermal conductivity in zero-dimensional nanoparticles. In our initial step, we merged both methodologies to substantiate the equivalence in thermal conductivity calculation for cube and cylinder nanoparticles. After filtering the data, we confirmed the usefulness of EMD for evaluating the thermal conductivity of zero-dimensional materials. The NEMD method faces challenges in accurately predicting thermal conductivity in nanoparticle systems with a varying cross-sectional area along the transport direction, whereas EMD methods can be utilized to estimate thermal conductivity when the volume is known. In a subsequent study, we used the state-of-the-art machine learning potential to calculate the thermal conductivity of spherical nanoparticles and compared the results with those obtained using the classical Tersoff potential. Ultimately, we predicted the thermal conductivity of nanoparticles with various geometries in all directions. Our findings collectively demonstrate the simplicity and effectiveness of employing EMD methods for calculating thermal conductivity in nanoparticle systems, thereby opening up new avenues for investigating thermal transport properties in particle systems as well as nanopders.