Data for "Quantum-corrected thickness-dependent thermal conductivity in amorphous silicon predicted by machine learning molecular dynamics simulations"

This is the data set for the preprint arXiv:2206.07605 [cond-mat.mtrl-sci], obtained by the GPUMD code. Here are 6 directories.<br> 1). NEMD<br> 2). NEPpotential<br> 3). PDOS<br> 4). kappa-quenchRate<br> 5). kappa-size<br> 6). kappa-temperature<br> <br> 1). NEMD directory contains calculations of ballistic conductance using NEMD method, where 6 independent cycles are run to average. 2). NEPpotential directory is the trained NEP potential. 3). PDOS directory contains phonon density of states of a-Si samples generated by the quench rate of 10^{11} K/s. 4). kappa-quenchRate directory contains HNEMD calculations of a-Si samples which are prepared using melt-quench temperature protocols with the quench rates covering from 10^{11} to 5x10^{12} K/s. In each case, 3 independent cycles are run. 5). kappa-size directory contains HNEMD calculations based on different supercells. 6 independent cycles are run. 6). kappa-temperature directory contains HNEMD calculations of a-Si samples which are prepared for different targeted temperatures using slow quench rate of 10^{11} K/s.