Stochastic simulation of pattern formation for chemically amplified resist in electron beam lithography

A molecular scale simulation of the pattern formation process for chemically amplified resist in electron beam lithography based on the stochastic approach is proposed. The initial resist structures are formed by the sequential bonding of the randomly selected monomers. The effects of electron exposure are introduced by the activation of the acid generator which randomly determined according to the absorbed energy distribution in the resist. The absorbed energy distribution is calculated using the Monte Carlo simulation of electron scattering. The effects of the post exposure bake are introduced by the acid diffusion and the polymer deprotection reactions. The fundamental properties, such as quencher concentration dependence, molecular weight dependence, and exposure condition effects on pattern profiles, are well reproduced by the simulation.

[1]  Y. Hirai,et al.  Stochastic simulation of the UV curing process in nanoimprint lithography: Pattern size and shape effects in sub-50 nm lithography , 2017 .

[2]  L. Pain,et al.  Study on line edge roughness for electron beam acceleration voltages from 50to5kV , 2009 .

[3]  C. Grant Willson,et al.  Acid catalyst mobility in resist resins , 2002 .

[4]  K. Murata,et al.  A Three-Dimensional Study of the Absorbed Energy Density in Electron-Resist Films on Substrates , 1978 .

[5]  G. P. Patsis.  Monte Carlo study of surface and line-width roughness of resist film surfaces during dissolution , 2005, Math. Comput. Simul..

[6]  Hiroo Kinoshita,et al.  Optimization of Photoacid Generator in Photoacid Generation-Bonded Resist , 2008 .

[7]  C. Willson,et al.  Chemical amplification in the design of dry developing resist materials , 1983 .

[8]  G. Wentzel.  Zwei Bemerkungen über die Zerstreuung korpuskularer Strahlen als Beugungserscheinung , 1926 .

[9]  Iwao Nishiyama,et al.  LER evaluation of molecular resist for EUV lithography , 2007 .

[10]  Evangelos Gogolides,et al.  Effects of model polymer chain architectures and molecular weight of conventional and chemically amplified photoresists on line-edge roughness. Stochastic simulations , 2006 .

[11]  T. Yamada,et al.  Line Edge Roughness of Developed Resist with Low-Dose Electron Beam Exposure , 2001, Digest of Papers. Microprocesses and Nanotechnology 2001. 2001 International Microprocesses and Nanotechnology Conference (IEEE Cat. No.01EX468).

[12]  B. P. Nigam,et al.  THEORY OF MULTIPLE SCATTERING: SECOND BORN APPROXIMATION AND CORRECTIONS TO MOLIERE'S WORK , 1959 .

[13]  Yoshihiko Hirai,et al.  Molecular Dynamics Study of Line Edge Roughness and the Proximity Effect in Electron Beam Lithography , 2015 .

[14]  Y. Hirai,et al.  Molecular simulation of pattern formation in electron beam lithography , 2013 .

[15]  Y. Hirai,et al.  Electron beam lithography simulation for sub-10 nm patterning , 2014 .

[16]  Material and process effects on line-edge-roughness of photoresists probed with a fast stochastic lithography simulator , 2005 .

[17]  George P. Patsis.  Stochastic simulation of thin photoresist film dissolution: a dynamic and a quasi-static dissolution algorithm for the simulation of surface and line-edge roughness formation , 2005 .

[18]  Ioannis Raptis,et al.  Detailed resist film modeling in stochastic lithography simulation for line-edge roughness quantification , 2010 .

[19]  Stochastic Simulation of Material and Process Effects on the Patterning of Complex Layouts , 2007 .

[20]  S. Tagawa,et al.  Simulation of amine concentration dependence on line edge roughness after development in electron beam lithography , 2008 .