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Effective filtration of chemical mechanical planarization slurries

Authors: R.K. Singh; C. Patel; G. Conner; T. Towle; R. Viscomi; M. Federau;

Effective filtration of chemical mechanical planarization slurries

Abstract

Low abrasive content and much smaller mean particles of silica, alumina and ceria abrasives in new generation chemical mechanical planarization (CMP) slurries demand much tighter retention of /spl ges/0.5 /spl mu/m and even smaller particles with least effect on the mean working particles. Current slurry manufacturing processes target 90% and higher reduction of cumulative large particle counts (LPCs) at /spl ges/0.56 or 1.01 /spl mu/m in a single pass. Filtration using graded density, multiple thin-layer, and pleated depth filter media or membranes can provide needed retention depending on the slurry characteristics. Efficient slurry filter design must consider slurry abrasive type and morphology, LPCs, mean particle size distribution (PSD), wt% solids, oxidizers, chemicals and organic additives, blending protocols, viscosity, abrasive settling rate, target retention level, pressure drop (/spl Delta/p) limits, flow rate stability and expected filter lifetime. Results of retention, flow rate and /spl Delta/p from filtration tests using 0.50 and 1.0 /spl mu/m nominal rating depth media samples show very different behavior in silica, alumina and ceria slurries, confirming that newer CMP slurries filter optimization still remains empirical in nature. This study shows that laboratory and field characterizations, and post-use filter analysis are useful in filter optimization. This study demonstrates that the filtration of newer CMP slurries is useful in managing large particles.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
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