Fast Verification of Guide-Patterns for Directed Self-Assembly Lithography

Abstract

Guide-patterns (GPs) are critical to the construction of contacts and vias in directed self-assembly (DSA) lithography. Simulations can be used to verify GPs, but runtime is excessive. Instead, we categorize the shapes of GPs using a small number of geometric parameters. Then a verification function is built to predict whether a GP will produce the required contacts, as follows: a vector in parameter space is constructed to represent each GP in a test set; the acceptability of each GP is then assessed by DSA simulation, and each vector is tagged “good” or “bad” accordingly; next, the parameter space is deformed to convert a radial distribution into one in which the good and bad vectors can be separated by a hyper-plane, which finally becomes the verification function. We also show how to reduce the dimensionality of the parameter space by principal component analysis, and how to generalize the geometric description of GPs to allow different types of GP to be verified in a uniform fashion. The proposed GP verification is demonstrated in 10 nm technology.