A Novel Analytic Approach to Model Line Edge Roughness using Stochastic   Exposure Distribution in Electron-beam Lithography
  The line edge roughness (LER) becomes a issue of e-beam lithography when feature size is reduced into nanometers. Therefore, minimizing the LER is a important method to increase the density of circuit patterns. One of the possible ways is through simulation. The stochastic exposure distributions in the resist is generated by the Monte Carlo simulation. In addition a resist development simulation needs to be carried out. Although there are several ways to simulate or estimate LER but none of them can reveal as much the inner relationship between LER and different parameters as theocratical analysing methods can do. In this paper, a new approach to analytically derive the LER based on the statistical exposure, is described. Our approach is based on analytic model of stochastic exposure distribution, deriving standard deviation of exposure and analyzing the variance of edge location after development. Even though it may not be a complete modeling of LER, it can still show some strong relationship between LER and some inner parameters. 
Rui Guo and Soo-Young Lee
cond-mat.mes-hall