Accelerate the analysis and optimization of lamellar BCP process using machine learning.

摘要

This paper presents how to use machine learning to accelerate the development of lamellar block copolymer process. Thefirst part introduces an automated algorithm to measure lamellar CD-SEM images oriented to allow fast images screening,identify and select the most relevant chemical composition. The second part is the use of machine learning in the processdevelopment which is a data driven approach. This part is also divided in two sections, the first one for the prediction ofthe process, where having a set of experiments in a process window, a model is created so that the outcome from isestimated from different parameters. The second part is the estimation of the process window. These tools are oriented toassist process engineers in the process optimization which must be driven under expert supervision.