An ab initio dataset of size-dependent effective thermal conductivity for advanced technology transistors

TL;DR

This paper provides an open dataset of size-dependent effective thermal conductivity for various semiconducting and metallic materials, derived from ab initio calculations, aiding thermal simulations in advanced transistor design.

Contribution

It introduces a comprehensive, openly accessible dataset of thermal conductivity at nanoscale sizes based on ab initio methods, improving accuracy over empirical models.

Findings

Thermal conductivity data for 12 materials across 5-50 nm sizes.

Normalized and absolute thermal conductivity values provided.

Dataset available at https://doi.org/10.57760/sciencedb.j00113.00154.

Abstract

As the size of transistors shrinks and power density increases, thermal simulation has become an indispensable part of the device design procedure. However, existing works for advanced technology transistors use simplified empirical models to calculate effective thermal conductivity in the simulations. In this work, we present a dataset of size-dependent effective thermal conductivity with electron and phonon properties extracted from ab initio computations. Absolute in-plane and cross-plane thermal conductivity data of eight semiconducting materials (Si, Ge, GaN, AlN, 4H-SiC, GaAs, InAs, BAs) and four metallic materials (Al, W, TiN, Ti) with the characteristic length ranging from 5 to 50 nanometers have been provided. Besides the absolute value, normalized effective thermal conductivity is also given, in case it needs to be used with updated bulk thermal conductivity in the future. The dataset presented in this paper are openly available at https://doi.org/10.57760/sciencedb.j00113.00154.