Development of a Thermal Conductivity Prediction Simulators Based on the Effects of Electron Conduction and Lattice Vibration

Estimation of the thermal conductivity for nano-materials based on quantum chemical methodologies provides important information for the development process of nano-scale devices, particularly those including impurities, defects, surfaces, and hetero-interfaces. Existing quantum mechanics-based methods for theoretically estimating the thermal conductivity of nano-materials are characterized by huge computational costs, which often prevent their applications to complex systems. Recently we have succeeded in the development of our original tight-binding quantum chemical molecular dynamics program “Colors”, which is able to realize calculations over 5000 times faster than conventional first principles molecular dynamics methods. Furthermore, based on a method that embeds “Colors” within a Monte Carlo paradigm we are able to compute values corresponding to carrier mobility, enabling thus the computation of electrical conductivity for different materials. Based on this system, in the present work, we describe a further development directed to the realization of two systems for thermal conductivity prediction. These systems of thermal conductivity prediction are based on two kinds of evaluation methods i) the estimation of the lattice vibration effect using classical molecular dynamics simulations and, ii) the conduction electron effect using the Wiedemann–Frantz law which is the basis of our recently proposed method for electrical conductivity prediction based on “Colors”. We have applied the methodology to evaluate the lattice vibration effect in amorphous SiO2, bolosilicate glass, cubic-ZrO2, and diamond while the electron conduction effect has been evaluated for metallic Ti, Sn.

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