Atomistic simulations of thermal conductivity in GeTe nanowires


Yet another exploit for the machine learning-based interatomic potential we have developed in 2012 for the phase change material GeTe. In this paper, we have computed the thermal conductivity of GeTe nanowires (a key component of a rather fancy device architecture for non-volatile memories) by means of large scale molecular dynamics simulations – only possible thanks to the power of neural networks (and a tad bit of physical intuition, I should add). Some interesting trends emerged… have a look at the paper online or grab a .pdf.