A novel accurate and robust technique in after-etch overlay metrology of 3D-NAND’s memory holes

In this work a novel machine learning algorithm is used to calculate the after etch overlay of the memory holes in a 3DNAND device based on OCD metrology by YieldStar S1375. It is shown that the method can distinguish the overlay signals from the process induced signals in the acquired pupil image and therefore, enables for an overlay metrology approach which is highly robust to process variations. This metrology data is used to characterize and correct the process induced intra-die stress and the DUV scanner application fingerprint.