Ion Diffusion in Chemically Amplified Resists

Coarse-Grained Modeling of EUV Patterning Process Reflecting Photochemical Reactions and Chain Conformations

Enabling extreme ultraviolet lithography (EUVL) as a viable and efficient sub-10 nm patterning tool requires addressing the critical issue of reducing line edge roughness (LER). Stochastic effects from random and local variability in photon distribution and photochemical reactions have been considered the primary cause of LER. However, polymer chain conformation has recently attracted attention as an additional factor influencing LER, necessitating detailed computational studies with explicit chain representation and photon distribution to overcome the existing approach based on continuum models and random variables. We developed a coarse-grained molecular simulation model for an EUV patterning process to investigate the effect of chain conformation variation and stochastic effects via photon shot noise and acid diffusion on the roughness of the pattern. Our molecular simulation demonstrated that final LER is most sensitive to the variation in photon distributions, while material distributions and acid diffusion rate also impact LER; thus, the intrinsic limit of LER is expected even at extremely suppressed stochastic effects. Furthermore, we proposed and tested a novel approach to improve the roughness by controlling the initial polymer chain orientation.

Accelerated Diffusion Following Deprotection in Chemically Amplified Resists

Polymeric chemically amplified resists (CARs) are critical materials for high-throughput lithographic processes. A photoactivated acid-anion catalyst changes the polymer's solubility via a deprotection reaction, which enables pattern development through selective dissolution. To capture observed reaction kinetics, reaction-diffusion models employ a catalyst diffusivity that is accelerated by reaction. However, the microscopic origin and factors contributing to this phenomena remain unclear. Herein, we employ detailed atomistic molecular dynamics simulations to examine the impact of protecting group removal and material relaxation on catalyst mobility. We report data on polymer density, catalyst dispersion, excess free volume, and segmental dynamics with increasing time/extent of deprotection. We then propose simple kinetic Monte Carlo algorithms that can describe both molecular dynamics simulations of deprotection reactions and experimental data.