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Comparison of simulation results to profilometer data for microcavities with initial photoresist opening d of 12.4 µm, 34 µm, and 52 µm. The whole threedimensional geometry is incorporated by considering axial symmetry.
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... the procedure described in section 3.3, we calibrated our pseudo-particle model to three microcavities with d of: 12.4 µm, 34 µm, and 52 µm. A visual comparison of the calibrated simulation to the profilometer data is summarized in figure 4. The final geometries of each of the three microcavities, obtained by the profilometer according to the procedure described in section 2.2, are the calibration targets for the residuals constructed according to (5). ...
Citations
... In the low-bias regime, a different set of challenges for accurately modeling the topography occurs. Recently, we have proposed a three-dimensional feature-scale simulation for low-bias SF 6 etching of Si [18] including a robust calibration procedure and applied it to the optimization of the fabrication of optical microcavity resonators. Nevertheless, this model involves a quantity which is not readily available: the sticking coefficient β, a measurement of the reaction probability between reactants and the surface. ...
... The parameters for the top-down model are obtained with an auto-matic calibration procedure previously developed by us [18] and presented in Table 2. For the strictly isotropic and bottom-up models, the same ER resist and second etch step ER Si are applied, however, each cavity requires a manually calibrated first step ER Si , presented in Table 3. ...
... The inclusion of different etch rates due to reactor loading was already shown to be necessary for reproducing the profiles of the twostep cavity etch [6,18], discussed in Section 3.1. In order to validate this approach more generally, we calibrate our simulation to results reported by Panduranga et al. [4]. ...
Low-bias etching of silicon (Si) using sulfur hexafluoride (SF6) plasma is a valuable tool in the manufacturing of electronic devices and micro electro-mechanical systems (MEMS). This kind of etching offers an almost isotropic etching behaviour, since the low voltage bias does not provide enough vertical acceleration and kinetic energy to the ions. Due to this near-isotropic behavior, the aforementioned plasma etching finds application as an alternative to wet etching in, e.g., MEMS and optical applications since it provides a cleaner and more precisely controllable process. However, the degree of isotropy and, consequently, the final surface profile remain difficult to control. In this work, we apply a three-dimensional feature-scale topography simulation to low-bias SF6 etching experiments in Si to aid in process development and to investigate the physical etching mechanisms which govern the final surface geometry. We achieve this by accurately reproducing three distinct experimental data sets and by discussing the meaning of the phenomenological model parameters involved in the topography simulation in detail. We show that our phenomenological top-down flux calculation approach more accurately reproduces the experimental results than conventional strictly isotropic and bottom-up approaches. The reactor loading effect is taken into account as a general reduction of the model etch rates, which is supported by comparing simulated to experimentally determined etch depths in different loading regimes. Our model is also able to accurately reproduce reported trench geometries for different mask openings and etch times using a single parameter set for a given reactor configuration. Hence, we propose that the model parameters, in particular the average effective sticking coefficient, can be taken as a proxy of the reactor configuration. We provide an empirical relationship linking the average sticking coefficient of a reactor recipe to a measurable degree of isotropy of etched geometries. This empirical relationship can be used in practice to (i) estimate the average effective sticking coefficient of independent experiments and to (ii) fine-tune the etched geometry.
... The level-set method [3] is well-suited for simulating fabrication processes of semiconductor devices in technology computer-aided design (TCAD) workflows [4][5][6][7][8][9]. Here, the wafer surface is described by a continuous function ϕ in the simulation domain Ω. ...
We present a feature detection method for adaptive grid refinement in hierarchical grids used in process technology computer-aided design topography simulations based on the local curvature of the wafer surface. The proposed feature detection method enables high-accuracy simulations whilst significantly reducing the run-time, because the grid is only refined in areas with high curvatures. We evaluate our feature detection method by simulating selective epitaxial growth of silicon-germanium fins in narrow oxide trenches. The performance and accuracy of the simulation is assessed by comparing the results to experimental data showing good agreement.
