For full commercialization, extreme ultraviolet lithography (EUVL) technology requires the availability of EUV mask blanks that are free of defects. This remains one of the main impediments to the implementation of EUV at the 22 nm node and beyond. Consensus is building that a few small defects can be mitigated during mask patterning, but defects over 100 nm (SiO2 equivalent) in size are considered potential “killer” defects or defects large enough that the mask blank would not be usable. The current defect performance of the ion beam sputter deposition (IBD) tool will be discussed and the progress achieved to date in the reduction of large size defects will be summarized, including a description of the main sources of defects and their composition.
Defect classification and characterization on mask substrates and blanks can be used to the identify defect sources within the tool and process. Defect reduction has been achieved in SEMATECH’s EUV Mask Blank Development Center (MBDC), aided by successful classifications of defect populations. Failure analysis of EUV substrate and blank defects in the MBDC begins with automatic classification of defects detected by M1350 and M7360 Lasertec inspection tools. Two sets of defect images and classification emerge from the two detection tools. The M1350 provides a more variegated set of 13 defect class types, while the M7360 provides eight. During manual review of the classifications, the defect class sets for both tools are often collapsed to only two major classes of interests with respect to production and failure analysis: particles and pits. This leaves various other classes ignored before subsequent characterization steps like SEM classification and composition analysis. The usefulness of tracking and verifying more detailed classes of defect needs to be explored. SEM analysis can be used to validate the relative size comparison yielded from inspection data alone, beyond the calibrated comparison of inspection signals from well-understood polystyrene latex spheres. The accuracy of rule-based defect classification of inspection tool data must be quantified by statistical tracking and validation SEM analysis. Classification of false counts increases as sensitivity of detection tools are increased to ensure the capture of smallest defects. The validity of calling a defect “false” is usually a manual review of pixel images created on the detection tool.
Defect inspection of EUV substrates and mask blanks must be controlled consistently to ensure repeatable and accurate defect counts. Initial sensitivity must be maintained without producing false counts. Various constructed and native defect monitors are created on substrates to track inspection tool performance. Remedies are applied to an inspection tool when monitors go out of control.
With the insertion of extreme ultraviolet lithography (EUVL) for high volume manufacturing (HVM) expected in the next few years, it is necessary to examine the performance of low thermal expansion materials (LTEMs) and assess industry readiness of EUV substrates. Owing to the high cost of LTEM, most of the development work so far has been done on fused silica substrates. Especially in developing cleaning technology prior to multilayer deposition, fused silica substrates have been used extensively, and defect trends and champion blank data have been reported using multilayer deposition data on fused silica substrates. In this paper, the response of LTEMs to cleaning processes prior to multilayer deposition is discussed. Cleaning processes discussed in this paper are developed using fused silica substrates and applied on LTEM substrates. The defectivity and properties of LTEM to fused silica are compared. Using the dense scan feature of the substrate inspection tool capable of detecting defects down to 35 nm SiO<sub>2</sub> equivalent size and appropriate defect decoration techniques to decorate small defects on substrates to make them detectable, cleaning technologies that have the potential to meet high demands on LTEM for EUVL are developed and optimized.
EUVL requires high-yield, low defect density reflective mask blanks, a requirement which is considered one of the top two critical technology gaps for commercialization of the technology. At the SEMATECH Mask Blank Development Center (MBDC), research on defect reduction and yield improvement for EUV mask blanks is being pursued using the Veeco Nexus deposition tool. The defect performance of this tool is one of the factors limiting the availability of defect-free EUVL mask blanks. SEMATECH identified the key components in the ion beam deposition system that are
currently impeding the reduction of defect density and the yield of EUV mask blanks. SEMATECH improved the defect performance of the champion blank with 12 defects above 45 nm which is a 36% improvement from the data reported last year for the champion blank (19 defects above 45 nm). The yield analysis on high quality mask blanks from ion beam deposition system is also presented. Substrate quality is currently the biggest source of mask blank defects, while high yield also requires complete elimination of large size defects from deposition. A roadmap to meet the required defectivity specification for EUV mask blanks is presented.
Extreme ultraviolet lithography (EUVL) is the leading next-generation lithography (NGL) technology to succeed optical
lithography at the 22 nm node and beyond. EUVL requires a low defect density reflective mask blank, which is
considered to be one of the top two critical technology gaps for commercialization of the technology. At the
SEMATECH Mask Blank Development Center (MBDC), research on defect reduction in EUV mask blanks is being
pursued using the Veeco Nexus deposition tool. The defect performance of this tool is one of the factors limiting the
availability of defect-free EUVL mask blanks. SEMATECH identified the key components in the ion beam deposition
system that is currently impeding the reduction of defect density and the yield of EUV mask blanks. SEMATECH's
current research is focused on in-house tool components to reduce their contributions to mask blank defects.
SEMATECH is also working closely with the supplier to incorporate this learning into a next-generation deposition tool.
This paper will describe requirements for the next-generation tool that are essential to realize low defect density EUV
mask blanks. The goal of our work is to enable model-based predictions of defect performance and defect improvement
for targeted process improvement and component learning to feed into the new deposition tool design. This paper will
also highlight the defect reduction resulting from process improvements and the restrictions inherent in the current tool
geometry and components that are an impediment to meeting HVM quality EUV mask blanks will be outlined.
Without the ability to detect potential yield-limiting defects in-line, the yield learning cycle is severely crippled, compromising the financial success of chip makers. As design rules shrink, device yield is seriously affected by smaller size particle and patterned defects that were not important in the past. These mechanisms are becoming more difficult to detect with current defect detection tools and techniques. The optical defect inspection tools that are currently available do not adequately detect defects, while scanning electron microscope (SEM) based inspection tools are too slow. With each successive technology node, optical inspection becomes less capable relative to the previous technology. As sensitivity is increased to detect smaller defects, the nuisance defect rate increases commensurately. Line-edge roughness (LER) and subtle process variations are making it more difficult to detect defects of interest (DOI). Smaller defects mean smaller samples available for energy dispersive x-ray analysis (EDX), necessitating an improved or new methodology for elemental analysis. This paper reviews these and some other challenges facing defect metrology at the 45nm technology node and beyond. The challenges in areas of patterned and unpatterned wafer inspection, defect review, and defect characterization are outlined along with proposed solutions. It also provides an overview of several ongoing projects conducted at International SEMATECH Manufacturing Initiative (ISMI) to address these challenges.