Photomask and Next-Generation Lithography Mask Technology XVII

A new inspection system with DUV laser beam and high NA optic for EUV mask has been developed to inspect defects
on EUV blank mask and defects by process and handling. The development of new reflective image and optics has
increased inspection speed on EUV mask before absorber etch and after absorber etch. Defect classification and
operation has increased the productivity of inspection and particle control on EUV mask process. With this new
inspection system, defects on blank mask, after resist develop and after etch processed mask were classified and
evaluated to install EUV mask process. And defect sensitivities according to various pattern size and process steps were
evaluated with required defect size of simulated printing effect on wafer. Designed defect pattern of 46nm node were
prepared. Blank masks from Hoya were used. Patterns were exposed using 50KeV electron beam writer. After resist
develop, patterns with program defect were inspected. After absorber etching, defects were inspected and evaluated.
According to sub film, inspection condition was optimized. Using simulation tool, defects printability were simulated
and compared with sensitivity of this inspection tool. Our results demonstrate that this inspection tool is very effective
to detect and identify defects and their sources on EUV mask process. In this paper, mask inspection performance of
high NA, DUV optic with short working distance was evaluated and described on programmed EUV mask.

EUV mask inspection tool using high NA DUV inspection tool

The mask inspection and defect classification is a crucial part of mask preparation technology and consumes a significant
amount of mask preparation time. As the patterns on a mask become smaller and more complex, the need for a highly
precise mask inspection system with high detection sensitivity becomes greater. However, due to the high sensitivity, in
addition to the detection of smaller defects on finer geometries, the inspection machine could report large number of
false defects. The total number of defects becomes significantly high and the manual classification of these defects,
where the operator should review each of the defects and classify them, may take huge amount of time. Apart from false
defects, many of the very small real defects may not print on the wafer and user needs to spend time on classifying them
as well. Also, sometimes, manual classification done by different operators may not be consistent. So, need for an
automatic, consistent and fast classification tool becomes more acute in more advanced nodes.
Automatic Defect Classification tool (NxADC) which is in advanced stage of development as part of NxDAT1, can
automatically classify defects accurately and consistently in very less amount of time, compared to a human operator.
Amongst the prospective defects as detected by the Mask Inspection System, NxADC identifies several types of false
defects such as false defects due to registration error, false defects due to problems with CCD, noise, etc. It is also able to
automatically classify real defects such as, pin-dot, pin-hole, clear extension, multiple-edges opaque, missing chrome,
chrome-over-MoSi, etc.
We faced a large set of algorithmic challenges during the course of the development of our NxADC tool. These include
selecting the appropriate image alignment algorithm to detect registration errors (especially when there are sub-pixel
registration errors or misalignment in repetitive patterns such as line space), differentiating noise from very small real
defects, registering grey level defect images with layout data base, automatically finding out maximum critical
dimension (CD) variation for defective patterns (where patterns could have Manhattan as well as all angle edges), etc.
This paper discusses about many such key issues and suggests strategies to address some of them based upon our
experience while developing the NxADC and evaluating it on production mask defects.

Key issues in automatic classification of defects in post-inspection review process of photomasks

Recently, extremely-high-quality-quartz substrates have been demanded for advancing ArF-lithography. HOYA has
developed a novel inspection method for interior defects as well as surface defects. The total internal reflection of the
substrate is employed to produce an ideal dark field illumination. The novel inspection method can detect a "nano-pit" of
12nm-EDS, the Equivalent of the Diameter of a Sphere (EDS). It will meet the sensitivity for 32nm node and beyond.
Moreover, a type of unique defect is detected, which induces Serious Transmittance Error for Arf-LiTHography. We call it
the "STEALTH" defect. It is a killer defect in wafer printing; but it cannot be detected with any conventional inspection in
the mask-making process so far.
In this paper, the performance of the novel inspection method for quartz substrates and the investigation of "STEALTH" are reported.

Novel glass inspection method for advanced photomask blanks

Sensitivity of newly developed photo mask inspection tool with reflective optic was evaluated for 45nm DRAM device.
To get the required defect sensitivity of mask, printability of mask defect on wafer were simulated using in house
simulation tool. Simulation results were compared with inspection results. Characteristic and sensitivity comparison
between conventional transmissive and reflective optic tools were evaluated for several types of mask layer of 45nm and
55nm DRAM according to pixel size of detector of inspection tools. This reflective optic with short working distance
was equivalent in sensitivity to transmissive optic tool. Mask for 45nm DRAM can be qualified by current status of the
art inspection tools.

Mask inspection method for 45nm node device

Advanced photomasks exploit complex patterns that show little resemblance to the target printed wafer pattern. The main mask pattern is modified by various OPC and SRAF features while further complexity is introduced as source-mask-optimization (SMO) technologies experience early adoption at leading manufacturers. The small size and irregularity of these features challenge the mask inspection process as well as the mask manufacturing process. The two major concerns for mask inspection and qualification efficacy of advanced masks are defect detection and photomask inspectability. Enhanced defect detection is critical for the overall mask manufacturing process qualification which entails characterization of the systematic deviations of the pattern. High resolution optical conditions are the optimal solution for manufacturing process qualification as well as a source of additional information for the mask qualification. Mask inspection using high resolution conditions operates on an optical image that differs from the aerial image. The high resolution image closely represents the mask plane pattern. Aerial imaging mode inspection conditions, where the optics of the inspection tool emulates the lithography manufacturing conditions in a scanner, are the most compatible imaging solution for photomask pattern development and hence mask inspectability. This is an optimal environment for performing mask printability characterization and qualification. In this paper we will compare the roles of aerial imaging and high resolution mask inspection in the mask house.

Photomask defect detection and inspection: aerial imaging and high resolution inspection strategies

As the photomask design rules continue to shrink towards 45nm and below, the defect classification criteria is
becoming more challenging to be set accurately. Pattern fidelity issues and masks defects that were once considered
insignificant or merely nuisances are now yield-limiting. On the other hand, there are still cases of small defects
captured during reticle inspection but will not print on the wafer. In addition, in a production setting environment it is
critical to ascertain quickly and efficiently the true lithographic effect of reticle defects in order to avoid yield and cycle
time impacts.
As a starting point, it is best to inspect the reticle at the highest sensitivity to find all defects and anomalies. From there,
fast and efficient means to sort and prioritize defects are necessary for inspection operators' and engineers' convenience.
Then, it is critical to model all the defects accurately for their lithographic impact. Finally, an accurate lithography-based
set of reticle defect disposition criteria can be developed for the manufacturing process flow.
The focus of this study is on contact or hole patterns since the issues regarding capture of defects on such patterns are
typically more complex than the ones on line and space patterns. The intent is to assess and devise defect disposition
criteria for contact hole layers utilizing KLA-Tencor's 5X6 DUV inspection system with both standard die-to-die and
Litho2 algorithms and the Automated Mask Defect Disposition (AMDD) system. AMDD lithographic printability
results will be compared to AIMS results and printed results on wafer.

DaeHo Hwang

Papers

Mask inspection method for 45nm node device

Photomask defect detection and inspection: aerial imaging and high resolution inspection strategies

Evaluation of litho printability of DRAM contact hole patterns with various programmed defects