Development of 3D Monte Carlo simulations for predicting multilayer geometry of pit-type EUV defects

Autor: Toh-Ming Lu, Ranganath Teki, Robert F. Spivey
Rok vydání: 2013
Předmět:
Zdroj: Extreme Ultraviolet (EUV) Lithography IV.
ISSN: 0277-786X
DOI: 10.1117/12.2011156
Popis: The EUV community has come to the conclusion that completely eliminating EUV mask defects will be nearly impossible in the near future. Instead the industry trend is to develop high performance optical simulations of the multilayer coating in order to compensate for the defects during manufacturing. In order for these simulations to be accurate the full multilayer structure of the EUV defect should be known. Currently there is no usable 3D method of simulating pit-type defects as they are relaxed during the energetic deposition of the Mo/Si multilayer. Current approximations used to model the defect's propagation are poor and have many shortcomings. Monte Carlo simulations of thin film growth are explored for this usage. They are validated using experimental data of a STEM cross section of a multilayer pit-type defect. Monte Carlo methods allow a full 3D representation of the system and have the advantage of great flexibility in deposition conditions and flux distributions. The Solid-on-Solid aggregation model is used to deposit particles onto initial substrate defects; this model does not allow overhanging particles, which replicates the smooth growth of ion-beam deposition well. Surface diffusion is simulated using Boltzmann statistics with activation energies of diffusion biased by local geometry. The growths are compared by observing the aspect ratio of the defect as a function of film thickness; the aspect ratio is defined as the depth of the defect divided by its full width at half maximum. Good fitting is observed for initial defect templates created from atomic force microscopy scans of observed initial defects. More rigorous tests of accuracy are also performed by comparing simulation predictions to AFM scans of the ending multilayer.
Databáze: OpenAIRE