Etching of polysilicon in inductively coupled Cl2 and HBr discharges. II. Simulation of profile evolution using cellular representation of feature composition and Monte Carlo computation of flux and surface kinetics

Abstract

A Monte Carlo simulator was developed to simulate the profile evolution during the Cl etching of patterned polysilicon in high density plasma etchers. The simulator used Monte Carlo techniques to compute the transport and surface kinetics combined with a cellular representation of the feature. The Monte Carlo algorithm permitted the incorporation of all the dominant physical and chemical mechanisms of the etching process such as angle-dependent ion-enhanced etching, physical sputtering, ion scattering, surface recombination, plasma deposition, sidewall passivation, and line-of-sight redeposition without encountering numerical difficulties. The technique allows for the modification of surface kinetics rates based on the surface composition. Simultaneous composition-dependent etching and deposition could be handled easily. A modification of the cellular representation of the feature (similar to a string-and-node algorithm) was developed to determine neutral species interactions with the surface enabling accurate simulation of deposition processes. A surface normal calculation algorithm involving least-squares fitting of the surface was developed to handle specular ion scattering. A generalizable structure allowing the incorporation of all chemical and physical processes was developed to handle the compositional, energy, and angular dependent surface processes. Test cases were run to quantify the accuracy of the combined Monte Carlo and cellular algorithms.

Development of SF<inf>6</inf>/O<inf>2</inf>/Si plasma etching topography simulation model using new flux estimation method

“…The strong correlation to the O flow rate in the above equation is the same as that found in reference [3].…”

“…In the etching of Si with SF 6 and O 2 gases with a SiO 2 mask, SiO 2 etching is virtually regarded as an ion governing process since the surface is saturated with adsorbed F radicals making the surface coverage a constant value of unity [3]. In contrast, Si etching is greatly affected by the F concentration, and it can be considered that Si/SiO 2 etching selectivity reflects this difference.…”

Surface roughening and rippling during plasma etching of silicon: Numerical investigations and a comparison with experiments

“…The particles are assumed to move straight from the top of the simulation domain onto substrate surfaces and then into microstructures thereon, without collisions with other particles in vacuum, where their transport is calculated every movement of step L, taking into account geometrical shadowing effects of the structure; then, the particles are assumed to reach the surface if there is a Si atom in any of the 26 cells neighboring the cell which the particle concerned is in. The local surface normal and thus the local angle h of incidence on microstructural feature surfaces is calculated by using the extended four-point technique 40,42,46,48 for 5 Â 5 Â 5 neighboring cells (125 cells in total) at around the substrate surface cell that the particle reaches, as shown in Fig. 1; this is one of the key procedures in the cell-based simulations such as ASCeM, because the surface chemistry and kinetics calculations rely crucially on the local incidence angle h, as mentioned below.…”

Atomic-scale cellular model and profile simulation of poly-Si gate etching in high-density chlorine-based plasmas: Effects of passivation layer formation on evolution of feature profiles

“…The simulation model often took into account the deposition or redeposition of etch products SiCl 4 within the feature, deposition of etch byproducts SiCl 2 coming from the plasma, and surface oxidation, in addition to ion-enhanced etching; the string model 7,8 and the cell removal method [9][10][11] were then used along with Langmuir adsorption kinetics to represent the evolving interfaces through surface reactions. However, these simulations did not take into account synergistic effects of surface oxidation and deposition; moreover, the substrates were represented as a continuum with monolayer adsorption and reaction kinetics on surfaces, and so atomistic processes on nanometer scale were hard to be treated including surface reaction multilayers as well as passivation layers.…”