STOCHASTIC DEFECT DETECTION FOR MONTE-CARLO FEATURE PROFILE MODEL * MIPSE Graduate Symposium 2015 Chad Huard and Mark Kushner University of Michigan, Dept.

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STOCHASTIC DEFECT DETECTION FOR MONTE-CARLO FEATURE PROFILE MODEL * MIPSE Graduate Symposium 2015 Chad Huard and Mark Kushner University of Michigan, Dept. of Electrical Engineering * Work supported by Lam Research Corporation MIPSE_2015

IMPORTANCE OF PLASMA ETCHING University of Michigan Institute for Plasma Science & Engr.  Reactive ion etching in plasma has become indispensable for semiconductor fabrication processes  Each successive technology node puts greater demands on etch techniques in terms of resolution and fidelity MIPSE_ nm 2 nd Gen. [1] S. Natarajan et al., 2014 IEEE International Electron Devices Meeting, 2014, pp –3.7.3.

CHALLENGES IN MODELING University of Michigan Institute for Plasma Science & Engr.  High quality simulation techniques are required that can be used to investigate the physics at work in modern etch processes on technologically relevant scales MIPSE_2015 [1] R. L. Bates, M. J. Goeckner, and L. J. Overzet, J. Vac. Sci. Technol. A Vacuum, Surfaces, Film., vol. 32, no. 5, p , [2] K. J. Kanarik, T. Lill, E. a. Hudson, S. Sriraman, S. Tan, J. Marks, V. Vahedi, and R. a. Gottscho, J. Vac. Sci. Technol. A Vacuum, Surfaces, Film., vol. 33, no. 2, p , Aspect Ratio Dependent Etch-rate Atomic Layer Etching

INTEGRATED MODEL HIRERARCHY University of Michigan Institute for Plasma Science & Engr. MIPSE_2015  Integrated modeling of reactor level plasma physics, sheath dynamics and etch feature evolution is essential to understand the dependency of etch features on process conditions  Our model uses independent modules which exchange information on process dependent time/length scales to simulate the physics at these vastly different scales

MONTE CARLO FEATURE PROFILE MODEL University of Michigan Institute for Plasma Science & Engr. MIPSE_2015  Profile geometry is defined on a structured grid  Pseudo-particles are launched with fluxes, energy and angular distributions derived from HPEM data  Particles are tracked through space until they react with the profile  Typical reactions:  Deposition A(s) + B(g)  A(s) + B(s)  Reflection A(s) + B(g)  A(s) + B(g)  Reaction A(s) + B(g)  C(s) + D(g)  All particles, including reaction products, are tracked until they are consumed or leave the simulation domain  Changes made to the profile by particle reactions are tracked as the simulation output Deposition Reflection Reaction

STOCHASTIC DEFECTS University of Michigan Institute for Plasma Science & Engr. MIPSE_2015  Due to stochastic nature of the Monte Carlo technique, unphysical defects can appear in the etch profile  Clusters of solid cells which have become detached from the main profile can appear during simulation  To avoid these unphysical defects affecting the results of the simulation they must be searched for and resolved separately from the main etch simulation  Two ways to resolve:  Delete orphaned clusters when detected  Drop clusters to surface of profile, as by gravity

HOSHEN-KOPELMAN (HK) ALGORITHM University of Michigan Institute for Plasma Science & Engr. MIPSE_2015  Originally conceived to study percolation problems  Algorithm finds ‘clusters’ of connected cells and gives each cluster a unique label  Any two cells that have the same label are connected by a path through other cells with the same label, and any two cells with different labels have no such path between them [1] J. Hoshen and R. Kopelman, Phys. Rev. B, vol. 14, no. 8, pp. 3438–3445, Oct [2] C. Joas, “Introduction to the Hoshen-Kopelman algorithm and its application to nodal domain statistics,” in Weizmann Institute, Nodal Week, 2006.

HK PSEUDOCODE University of Michigan Institute for Plasma Science & Engr. MIPSE_2015 [1] J. Hoshen and R. Kopelman, Phys. Rev. B, vol. 14, no. 8, pp. 3438–3445, Oct [2] C. Joas, “Introduction to the Hoshen-Kopelman algorithm and its application to nodal domain statistics,” in Weizmann Institute, Nodal Week, Find(x): while L(x)!=x x=L(x) return(x) Union(x,y): L(x)=Find(y)

HK ALGORITHM FLOW University of Michigan Institute for Plasma Science & Engr. MIPSE_2015 [1] J. Hoshen and R. Kopelman, Phys. Rev. B, vol. 14, no. 8, pp. 3438–3445, Oct [2] C. Joas, “Introduction to the Hoshen-Kopelman algorithm and its application to nodal domain statistics,” in Weizmann Institute, Nodal Week,  HK algorithm requires two passes through system to accurately label all clusters

HK IMPLEMENTATION IN MCFPM University of Michigan Institute for Plasma Science & Engr. MIPSE_2015  In MCFPM the HK algorithm is adopted to identify and label clusters of solid materials  If solid profile is completely connected there will be only one single cluster with only one label  Clusters comprised of fewer than N min cells are considered orphaned and dropped or deleted  HK algorithm is very computationally efficient and robust in this application Clusters of solid cells: Cells are colored by cluster label using the HK algorithm as implemented in MCFPM

EXAMPLE: SI ETCHING IN CL 2 PLASMA University of Michigan Institute for Plasma Science & Engr. MIPSE_2015  Silicon etching in Ar/Cl 2 plasma  Main etch mechanism:  Surface chlorination:  Si (s) + Cl (g) → SiCl (s)  SiCl (s) + Cl (g) → SiCl 2(s)  SiCl 2(s) + Cl (g) → SiCl 3(s)  SiCl 3(s) + Cl (g) → SiCl 4(g) (low rate)  Ion assisted etching:  SiCl x(s) + M → SiCl x(g) + M  Where M is an energetic ion  Sputter rate increases with chlorine coordination and ion energy  Other reactions considered:  Direct sputtering of Si  Re-deposition of etch products  Sputtering / re-deposition of polymer resist (PR)  Ion energy and angular distributions at etch surface

EFFECT ON POLYMER REDEPOSITION University of Michigan Institute for Plasma Science & Engr. MIPSE_2015  Not using a drop routine leaves a cloud of resist cells floating above the main profile  Delete shows very little re-deposited PR  Drop shows significant “micro-masking” effect [A] Etch profile with no drop routine [B] Etch profile with clusters deleted [C] Etch profile with clusters dropped

EFFECT ON ETCH RATE University of Michigan Institute for Plasma Science & Engr. MIPSE_2015  Choosing to delete orphaned clusters increases etch rate  Dropping orphaned clusters to surface slows etch rate slightly  These results are expected due to the relatively low sputtering rate for photoresist in this reaction mechanism  This result, along with unit tests, provides verification of the HK technique as implemented in MCFPM [A] Etch profiles with no drop routine [B] Etch profiles with orphaned clusters deleted [C] Etch profiles with orphaned clusters dropped

University of Michigan Institute for Plasma Science & Engr.  Accurate etch profile simulation is essential to modern semiconductor technology  MCFPM provides 2d and 3d etch simulation integrated with reactor simulation through HPEM  Stochastic appearance of orphaned clusters of solid cells can effect etch simulation  Hoshen-Kopelman algorithm provides an efficient method to search for orphaned clusters  Choice of how to handle orphaned clusters can effect simulated profile  In case of etching of Si in Ar/Cl 2 plasma:  Deleting orphans increases etch rate  Dropping orphans results in increased micro-masking  Other systems may have different dependencies, and require flexible solution CONCLUDING REMARKS MIPSE_2015