Prediction of etching results and etching stabilization by applying principal component regression to emission spectra during in-situ cleaning

A method to predict etching results by analyzing plasma emission spectra during in-situ cleaning was investigated, where the plasma emission spectra indicate the surface condition of etching reactor walls. Plasma-wall interaction was evaluated by using both principal component regression of plasma emission spectra and attenuated-total-reflection Fourier-transform infrared spectroscopy. We found that differences in the amount of silicon oxide deposition on the reactor wall affected radical composition in the plasma during in-situ cleaning and consequently affected the etching results. Etching result predictions using the plasma spectra corresponded very well to the etching result measurements, which are used to improve etching stability