As design rule continues to shrink, microlithography is becoming more challenging and the photomasks
need to comply with high scanner laser energy, low CDU, and ever more aggressive RETs. This
give rise to numerous challenges in the semiconductor wafer fabrication plants. Some of these
challenges being contamination (mainly haze and particles), mask pattern degradation (MoSi oxidation,
chrome migration, etc.) and pellicle degradation. Fabs are constantly working to establish an efficient
methodology to manage these challenges mainly using mask inspection, wafer inspection, SEM review
and CD SEMs. Aerial technology offers a unique opportunity to address the above mask related
challenges using one tool. The Applied Materials Aera3TM system has the inherent ability to inspect for
defects (haze, particles, etc.), and track mask degradation (e.g. CDU). This paper focuses on haze
monitoring, which is still a significant challenge in semiconductor manufacturing, and mask
degradation effects that are starting to emerge as the next challenge for high volume semiconductor
manufacturers. The paper describes Aerial inspector (Aera3) early haze methodology and mask
degradation tracking related to high volume manufacturing. These will be demonstrated on memory
products.
At the end of the paper we take a brief look on subsequent work currently conducted on the more
general issue of photo mask degradation monitoring by means of an Aerial inspector.
Monitoring and controlling of haze defect is becoming important more than ever before [1]. Regular and frequent mask
inspection is expected to reduce the risk of defect print on wafer [2]. However, such frequent inspection requires longer
inspection time and additional cost, which should lead to worsening of productivity.
It is known that haze defect grows from non-killer defect at its infant stage to killer defect as time advances. And such
haze growth process is dependent on the haze size in its infant stage, location of haze generation and such. If the haze
inspection procedure were customized in a most suited way to optimally monitor the growth characteristics of haze, the
inspection throughput would become higher without sacrificing the performance and reliability of mask inspection itself.
For such a purpose, we have studied an effective haze monitoring method that ensures both sensitivity and throughput
high enough. We will show that a variable scan method using a DUV mask inspection tool is quite effective in cutting
down inspection time and cost.
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