CMP Slurry Abrasive Particle Agglomeration Modeling

  • Authors: J. M. Johnson, D. S. Boning
  • Sponsorship: SRC/SEMATECH Engineering Research Center for Environmentally Benign Semiconductor Manufacturing

In this work we propose a particle agglomeration model for CMP, to understand the creation and behavior of agglomerated slurry abrasive particles arising during the CMP process. These particles are accepted as a major cause of defectivity and poor consumable utility due to sedimentation [1] [2] [3] . We believe that the few slurry abrasive particle modeling attempts prior to this work have been focused on showing data-rich qualitative correlations [4] , empirically assumed relationships of those correlations on particle size distributions [5] , or quantitative correlations of purely mechanistic behavior of agglomerated particles, without considering chemical effects [2] [6] .

Our proposed model will provide both a qualitative and quantitative description of agglomeration in slurry abrasive particles during CMP that includes the chemical kinetics and mechanistic behaviors of both the slurry abrasive particles and the slurry electrolyte, enabling more accurate process control, increased consumable utility, and possible defectivity reduction. The proposed model considers the slurry composition as a colloidal suspension of charged colloidal silica in an electrically neutral aqueous electrolyte. First, we present a theoretical relationship between the measurable chemical parameters of the slurry’s aqueous electrolyte, the surface potential of the abrasive particles, and the corresponding zeta potential between the agglomerated abrasive particles is presented. Secondly, this zeta potential is used in a modified DVLO interaction potential model to determine the particle interaction potentials due to both the attractive van Der Waals forces and repulsive electrostatic interactions.  Finally, the total interaction potential created is then used to define a stability ratio for slow versus fast agglomeration and corresponding shear-induced agglomeration rate equations between particles; these are used in a discrete population balance framework to describe the final particle size distribution with respect to time and agglomerate composition.

The framework for this new agglomeration model is being further investigated and we are currently developing and conducting experimentation to validate our theoretical model.

  1. F.-C. Chang, S. Tanawade, and R. K. Singh, J. Electrochem. Soc., vol. 156, p. H39, 2009. [↩]
  2. R. Biswas, Y. Han, P. Karra, P. Sherman, and A. Chandra, J. Electrochem. Soc., vol. 155, pp. D534-D537, 2008. [↩] [↩]
  3. Moinpour, A. Tregub, A. Oehler, and K.Cadien, Mater. Res. Bulletin, 766, 2002. [↩]
  4. S. Ramarajan, Y. Li, M. Hariharaputhiran, Y.-S. Her, and S. V. Babu, Electrochem. Solid-State Lett., vol. 3, no. 5, pp. 232-234, 2000 [↩]
  5. A. R. Mazaheri and G. Ahmadi, J. Electrochem. Soc., vol. 150, pp. G233-G239, 2003. [↩]
  6. F.-C. Chang and R. K. Singh, J. Electrochem. Solid-State Lett., vol. 12, pp. H127-H130, 2009 [↩]

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