Atmospheric-Pressure Plasma-Enhanced Spatial ALD of SiO2 Studied by Gas-Phase Infrared and Optical Emission Spectroscopy.
M A MioneVincent VandalonAlfredo MameliWilhelmus Erwin M M KesselsF RoozeboomPublished in: The journal of physical chemistry. C, Nanomaterials and interfaces (2021)
An atmospheric-pressure plasma-enhanced spatial atomic layer deposition (PE-s-ALD) process for SiO2 using bisdiethylaminosilane (BDEAS, SiH2[NEt2]2) and O2 plasma is reported along with an investigation of its underlying growth mechanism. Within the temperature range of 100-250 °C, the process demonstrates self-limiting growth with a growth per cycle (GPC) between 0.12 and 0.14 nm and SiO2 films exhibiting material properties on par with those reported for low-pressure PEALD. Gas-phase infrared spectroscopy on the reactant exhaust gases and optical emission spectroscopy (OES) on the plasma region are used to identify the species that are involved in the ALD process. Based on the identified species, we propose a reaction mechanism where BDEAS molecules adsorb on -OH surface sites through the exchange of one of the amine ligands upon desorption of diethylamine (DEA). The remaining amine ligand is removed through combustion reactions activated by the O2 plasma species leading to the release of H2O, CO2, and CO in addition to products such as N2O, NO2, and CH-containing species. These volatile species can undergo further gas-phase reactions in the plasma as indicated by the observation of OH*, CN*, and NH* excited fragments in OES. Furthermore, the infrared analysis of the precursor exhaust gas indicated the release of CO2 during precursor adsorption. Moreover, this analysis has allowed the quantification of the precursor depletion yielding values between 10 and 50% depending on the processing parameters. Besides providing insights into the chemistry of atmospheric-pressure PE-s-ALD of SiO2, our results demonstrate that infrared spectroscopy performed on exhaust gases is a valuable approach to quantify relevant process parameters, which can ultimately help evaluate and improve process performance.