Detection of resist residue and organic contamination after photo resist strip and wafer clean early in the high K/metal
gate (HK/MG) manufacturing process flow is critical as it has been known to significantly impact yield. This residue,
when exposed to subsequent thermal process steps, transforms into solid hard spot(s), and can then be detected by a
wafer inspection tool, but unfortunately it is too late to take corrective action. A unique process control solution to detect
the presence of residues was developed using advanced analysis of an optical scattering inspection of a litho checkerboard pattern. The presence of residue was then validated with film thickness measurements.
In the early development stage of 32nm processes, identifying and isolating systematic defects
is critical to understanding the issues related to design and process interactions. Conventional
inspection methodologies using random review sampling on large defect populations do not provide
the information required to take accurate and quick corrective action. This paper demonstrates the
successful identification and isolation of systematic defects using a novel methodology that
combines Design Based Binning (DBB) and inline Defect Organizer (iDO). This new method of
integrating design and defect data produced actionable inspection data, resulting in fewer mask
revisions and reduced device development time.
We proposed a novel method (DBB: Designed Based Binning) by using design and defect inspection information to
detect marginal design features. This method was used to identify a pattern failure problem (hammer head) which
occurred during production early ramp (65 nm device). The traditional approach could not detect this hammerhead
problem due to the intermittent nature and low defect count. This problem was identified by DBB methodology which
showed problem root cause as a combination of lithography process conditions drift and marginal OPC issues.
This use case proved that by using DBB to identify weak pattern features, it provides a common platform for designer,
OPC and process engineer to communicate and identify design related problems faster. This method has helped
integration engineer shorten process development time, supported product engineer to ramp new product faster and
enabled defect engineer to detect excursion earlier. Overall, advanced manufacturing fab will achieve higher yield by
adopting this.
Increasing inspection sensitivity may be necessary for capturing the smaller defects of interest (DOI)
dictated by reduced minimum design features. Unfortunately, higher inspection sensitivity can result in a
greater percentage of non-DOI or nuisance defect types during inline monitoring in a mass production
environment. Due to the time and effort required, review sampling is usually limited to 50 to 100 defects
per wafer. Determining how to select and identify critical defect types under very low sampling rate
conditions, so that more yield-relevant defect Paretos can be created after SEM review, has become very
important. By associating GDS clip (design layout) information with every defect, and including defect
attributes such as size and brightness, a new methodology called Defect Criticality Index (DCI) has
demonstrated improved DOI sampling rates.
As design rules continue to shrink beyond the lithography wavelength, pattern printability becomes a significant
challenge in fabrication for 45nm and beyond. Model-based OPC and DRC checkers have been deployed using
metrology data such as CD to fine-tune the model, and to predict and identify potential structures that may fail in a
manufacturing environment. For advanced technology nodes with tighter process windows, it is increasingly important
to validate the models with empirical data from both product and FEM wafers instead of relying solely on traditional
metrology and simulations. Furthermore, feeding the information back to designers can significantly reduce the
development efforts.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.