Exploration of the mechanical properties of carbon-incorporated amorphous silica using a universal neural network potential

C-incorporated amorphous silica (a-SiOC) is expected to be a significant dielectric film for miniaturized semiconductor devices. However, information on the relationship among its composition, atomic structures, and material properties remains insufficient. This study investigated the dependence of the elastic modulus on the C content in a-SiOC, employing a universal neural network interatomic potential to realize a high-accuracy and high-speed simulation of multicomponent systems. The relationship between elastic modulus and atomic network structures was explored by fabricating 480 amorphous structures through the melt-quenching method without predetermined structure assumptions. The bulk modulus increased from 45 to 60 GPa by incorporating 10% C atoms under O-poor conditions and 20% C atoms under O-rich conditions, respectively. This result is attributed to the formation of denser crosslinking atomic network structures. In particular, the C atoms bonded with the Si atoms with higher coordination under O-poor conditions, whereas they tend to bond with O atoms under O-rich conditions, breaking the SiO2 network. Large C clusters precipitated as the C fraction was increased under O-rich conditions. Gas molecules, such as CO and CO2, were also generated. These results are consistent with reported ab initio calculation results of the formation energies of C defects and gas molecules in SiO2. The findings suggest that realizing O-poor conditions during deposition is crucial for fabricating stronger dielectric films. Therefore, this work contributes to understanding the fabrication of stronger dielectric films and elucidating the underlying mechanism of C cluster formation.