Thermal conductivity calculation based on Green–Kubo formula using ANN potential for β-Ag2Se. (April 2022)

• Record Type: Journal Article
• Authors: Takeshita, Yusuke; Shimamura, Kohei; Fukushima, Shogo; Koura, Akihide; Shimojo, Fuyuki
• Is Part Of: Journal of physics and chemistry of solids. Volume 163(2022)
• Publication Date: 2022-04
• Subjects: Artificial neural network (ANN) potential -- Thermal conductivity -- Green–Kubo method -- First-principles molecular dynamics (FPMD) -- Behler–Parrinello symmetry function; Solids -- Periodicals; Solides -- Périodiques; Solids; Periodicals; 530.41
• DOI: 10.1016/j.jpcs.2022.110580
• Languages: English
• ISSNs: 0022-3697

Abstract

Abstract: For calculating thermal conductivity (TC) of the nonsuperionic β -Ag2 Se, we used the computational framework that combined molecular dynamics simulations using interatomic potentials based on artificial neural networks (ANN potential) and the Green–Kubo formula. The ANN potential trained on first-principles molecular dynamics (FPMD) data. Despite the framework being essentially based on one developed in our previous study in which an empirical interatomic potential was employed for the superionic alpha phase to obtain the training data, it worked well in the current study based on the FPMD simulations for the beta phase. The estimated value was consistent with the extremely low experimental lattice TC of ∼0.3 Wm −1 K −1 . This result demonstrates the effectiveness of our framework for estimating TC.