Machine Learning predicts printing parameters for multi-photon polymerization three-dimensional direct laser writing (3D-DLW) (Conference Presentation)

We are presenting a model for a quantitative description of the polymerization process in 3D-laser microfabrication. With aim to assist in estimating the necessary power threshold to obtain certain feature size, particularly the line characteristics, depending on the laser power and writing speed. The focal distribution as well as the photoresist is taken into account. We do not try to gain any chemical insight into the processes involved, and restrict us to a quantitative study of a multi-photon process. Machine learning is used to classify the input SEM images providing a look-up table as a custom field for optimized parameter selection.