Visualizing laser ablation using plasma imaging and deep learning

Abstract

High power laser ablation can lead to the creation of plasma and the emission of bright light, which can prevent the direct observation of the workpiece. Alternative techniques for enabling the visualization of the sample during laser machining are therefore of interest. Here, we show that the plasma created during laser ablation, when viewed perpendicular to the sample surface, contains information regarding the appearance of the sample. Specifically, we show that deep learning can predict the 2D appearance of the sample, directly from 2D projected images of the plasma produced during single pulse femtosecond laser ablation. In addition, this approach also enables the identification of the pulse energy of the most recent laser pulse used to machine the sample. This work could have applications across laser materials processing in research and industry, in cases where there is a requirement for real-time visualization of the sample surface during laser ablation.