Defects are still one of the main challenges of extreme ultraviolet (EUV) mask blanks. In particular, a majority(~75%) of
substrate defects are nanometer size pits. These pits are usually created during final surface polishing of the synthetic,
quartz glass substrates. This study presents data that indicates cleaning may also induce pits in the substrate surface.
These pits are typically 20 nm and larger, and are contained in a circular area on the surface, which is scanned by a
megasonic nozzle during cleaning. Concentrated collapse of cavitation bubbles in the areas scanned by megasonic is
expected to be one of the main mechanisms of pit creation. The data indicates the existence of a hard surface layer with
an estimated thickness of approximately 30 to 60 nm, which is resistive to pit creation. After this layer is removed, the
number of pit defects present on the substrate increases dramatically with megasonic cleaning. It is also demonstrated
that, within the detection limits of the atomic force microscope (AFM), the size of a pit does not change due to cleaning.
Extreme ultraviolet lithography (EUVL) is a strong contender for the 32 nm generation and beyond. A defect-free mask
substrate is an absolute necessity for manufacturing EUV mask blanks. The mask blank substrates are, therefore,
cleaned with different cleaning processes to remove all defects down to 30 nm. However, cleaning suffers from the
defects added by various sources such as the fab environment, chemicals, ultra pure water, and the cleaning process
itself. The charge state of the substrate during and after cleaning also contributes to the number of adder defects on the
substrate. The zeta potentials on the substrate surface and the defect particles generated during the cleaning process
determine whether the particles get deposited on the surface. The zeta potential of particle or substrate surfaces depends
on the pH of the cleaning fluids. Therefore, in this work, pH-zeta potential maps are generated for quartz substrates
during the various steps of mask cleaning processes. The pH-zeta potential maps for defect particles commonly seen on
mask substrates are measured separately. The zeta potential maps of substrate and contaminant particle surfaces are
used to determine whether particles are attracted to or repulsed from the substrate. In practice, this technique is
especially powerful for deriving information about the origin of particles added during a cleaning process. For example,
for a known adder with a negative zeta potential, all cleaning steps with a positive zeta potential substrate could be the
source of added particles.
Extreme ultraviolet (EUV) substrates have stringent defect requirements. For the 32 nm node, all particles larger than 26
nm must be removed from the substrate. However, real defects are irregularly shaped and there is no clear dimension for
an irregular particle corresponding to 26 nm. Therefore, the sphere equivalent volume diameter (SEVD) for a native
defect is used. Using this definition and defect detection measurements, all particles larger than 20 nm must be removed
from the substrate. Atomic force microscopy (AFM) imaging and multiple cleaning cycles were used to examine the
removal of particles smaller than 50 nm SEVD. Removal of all particles larger than 30 nm was demonstrated. Particles
that required multiple cleaning processes for removal were found to be partially embedded. The best cleaning yield can
be obtained if the cleaning history of the substrate is known and one can choose the proper cleaning processes that will
remove the remaining particles without adding particles. Ag, Au, Al2O3, Fe2O3, and CuO particles from 30 nm to 200 nm
were deposited on quartz surface. It was shown that these deposited defects are much easier to remove than native
Extreme ultraviolet (EUV) mask blanks must have nearly zero defects larger than 30 nm. Mask blank defects are an accumulation of defects present on the substrate, defects added during the multilayer (ML) deposition process, and defects added by handling the mask blank. A majority of the detectable defects are already present on the substrate before the ML deposition. However, very few of the defects present on the substrate before the ML deposition are detectable. This raises the question of whether the substrate's surface condition contributes to the total number of defects on the mask blank. Here the results of investigations on the relation between the total number of defects on the multilayer and the substrate surface condition are presented. The final surface condition is determined by the mask cleaning process. Correlation studies between defect maps before and after multilayer deposition are presented, and the relation between final defect size on the multilayer and substrate are discussed. SEMATECH's Mask Blank Development Center (MBDC) has a unique capability to characterize the surface of EUV glass substrates by atomic force microscopy (AFM), scanning electron microscopy (SEM), surface energy measurement, and zeta potential metrology. A series of experiments were performed in which different cleaning processes were used to modify the substrate surface condition before multilayer deposition. The effect of the cleaning process on the number of pits and particles after ML deposition was examined. The results indicate that although there is a direct relationship between the number of defects remaining on the substrate and mask blank defects after multilayer deposition, the variation in the total number of defects on the mask blank mainly corresponds to pits and particles already present on the substrate before cleaning and are not the result of the cleaning processes that were used before multilayer deposition.
Extreme ultraviolet lithography (EUVL) is being considered as the enabler technology for the manufacturing of future
technology nodes (30 nm and beyond). EUV mask blanks are Bragg mirrors made of Mo and Si bilayers and tuned for
reflectivity at a wavelength λ ~13 nm. Implementation of EUVL requires that the mask blanks be free of defects at 30
nm or above. However, during the deposition of MoSi multilayers and later during the handling of blanks, defects are
added to the blank. Therefore, the cleaning of EUV mask blanks is a critical step in the manufacturing of future devices.
The particulate defects on the multilayer-coated mask blanks can either be embedded in or under the MoSi layers or
adhered to the top capping layer during the deposition process. The defects can also be added during the handling of
photomasks. Our previous studies have shown successful removal of the handling-related defects at SEMATECH's
Mask Blank Development Center (MBDC) in Albany, NY. However, cleaning embedded and adhered defects presents
new challenges. The cleaning method should not only be able to remove the particles, but also be compatible with the
mask blank materials. This precludes the use of any aggressive chemistry that may change the surface condition leading
to diminished mask blank reflectivity. The present work discusses the recent progress made at SEMATECH's MBDC in
cleaning backside Cr-coated mask blanks with a MoSi multilayer and a Si cap layer on the top surface. Here we present
our data that demonstrates successful removal of sub-100 nm particles added by the deposition process. Surface
morphology and defect composition on the surface of the MoSi multilayer are discussed. EUV reflectivity measurements
and atomic force microscopy (AFM) images of the mask blank before and after cleaning are presented. The present data
shows that no measurable damage to the EUV mask blank is caused by the cleaning processes developed at the MBDC.
Megasonic cleaning has been a traditional approach for the cleaning of photomasks. Its feasibility as a damage free approach to sub 50 nm particulate removal is under investigation for the cleaning of optical and EUV photomasks. Two major mechanisms are active in a megasonic system, namely, acoustic streaming and acoustic cavitation. Acoustic streaming is instrumental in contaminant removal via application of drag force and rolling of particles, while cavitation may dislodge particles by the release of large energy during cavity implosion or by acting as a secondary source of microstreaming. Often times, the structures (substrates with or without patterns) subjected to megasonic cleaning show evidence of damage. This is one of the impediments in the implementation of megasonic technology for 45 nm and future technology nodes. Prior work suggests that acoustic streaming does not lead to sufficiently strong forces to cause damage to the substrates or patterns. However, current knowledge of the effects of cavitation on cleaning and damage can be described, at best, as speculative. Recent experiments suggest existence of a cavity size and energy distributions in megasonic systems that may be responsible for cleaning and damage. In the current work, we develop a two-dimensional atomistic model to study such multibubble cavitation phenomena. The model consists of a Lennard-Jones liquid which is subjected to sinusoidal pressure changes leading to the formation of cavitation bubbles. The current work reports on the effects of pressure amplitude (megasonic power) and frequency on cavity size distributions in vaporous and gaseous cavitation. The findings of the work highlight the role of multibubble cavitation as cleaning and damage mechanism in megasonic cleaning.
Removal of nano-scale contaminant particles from the photomasks is of critical importance to the implementation of EUV lithography for 32nm node. Megasonic cleaning has traditionally been used for photomask cleaning and extensions to sub 50nm particulates removal is being considered as a pattern damage free cleaning approach. Several mechanisms for removal are believed to be active in megasonic cleaning systems, e.g., cavitation, and acoustic streaming (Eckart, Schlichting, and microstreaming). It is often difficult to separate the effects of these individual mechanisms on contamination removal in a conventional experimental setup. Therefore, a theoretical approach is undertaken in this work with a focus on determining the contribution of acoustic streaming in cleaning process. A continuum model is used to describe the interaction between megasonic waves and a substrate (fused silica) immersed in a fluid (water). The model accounts for the viscous nature of the fluid. We calculate the acoustic vibrational modes of the system. These in turn are used to determine the acoustic streaming forces that lead to Schlichting streaming in a narrow acoustic boundary layer at the substrate/fluid interface. These forces are subsequently used to estimate the streaming velocities that may in turn apply a pressure and drag force on the contaminant particles adhering to the substrate. These effects are calculated as a function of angle of incidence, frequency and intensity of the megasonic wave. The relevance of this study is then discussed in the context of the cleaning efficiency and pattern damage in competing megasonic cleaning technologies, such as immersion, and nozzle-based systems.
Prior interferometric fiber sensors and evanescent wave fiber sensors have proven useful in obtaining information about portions of the lifetime of a composite materials. The overall goal of this research is to develop an IR evanescent wave sensor system that can be used to monitor lifetime of a polymer matrix composite. In this regard, a single fused silica core fiber was placed across a miniature materials tester, while simultaneously having the fiber ends attached to an IR spectrometer. The fiber was strained in increments by the MINIMAT, while the IR spectrometer allowed simultaneous determination of the IR spectrum. An increase in baseline absorbance across the entire IR spectrum occurred as the strain increased. The increase in absorbance is relate to an increase in strain in the fiber. From regression analysis of independent measurements of fiber strain and absorbance, a strong relation between the change in absorbance and change in strain energy was found. Future work will involve incorporation of the strain sensing approach with evanescent wave chemical sensing to allow total lifetime monitoring of polymer matrix composites.