NXE pellicle: offering a EUV pellicle solution to the industry

Brouns, Derk; Bendiksen, Aage; Broman, Par; Casimiri, Eric; Colsters, Paul; Delmastro, Peter; Graaf, Dennis de; Janssen, Pieter; Kerkhof, Mark van de; Kramer, R.P.; Kruizinga, Matthias; Kuntzel, Henk; Meulen, Frits van der; Ockwell, David; Makk, Péter; Smith, Daniel; Verbrugge, Beatrijs; Weg, David van de; Wiley, James N.; Wojewoda, Noelie; Zoldesi, Carmen; Zwol, Pieter van

doi:10.1117/12.2221909

Cited by 22 publications

(15 citation statements)

References 1 publication

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“…In this way, for instance, the very small particles are of minor importance for the pellicle layer above the UV mask, and only if the bigger particles are present, cleaning action needs to be taken. In the absence of the pellicle, on the contrary, one should take care only about the small contamination landing on the mask [33]. The quantitative description of the surface, provided by the surface scanner in this regard becomes very crucial.…”

Section: Benefit Of the Centroids Re-assignmentmentioning

confidence: 99%

Machine learning techniques applied for the detection of nanoparticles on surfaces using coherent Fourier scatterometry

Kolenov

Pereira²

2020

Opt. Express

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We present an efficient machine learning framework for detection and classification of nanoparticles on surfaces that are detected in the far-field with coherent Fourier scatterometry (CFS). We study silicon wafers contaminated with spherical polystyrene (PSL) nanoparticles (with diameters down to λ/8). Starting from the raw data, the proposed framework does the pre-processing and particle search. Further, the unsupervised clustering algorithms, such as K-means and DBSCAN, are customized to be used to define the groups of signals that are attributed to a single scatterer. Finally, the particle count versus particle size histogram is generated. The challenging cases of the high density of scatterers, noise and drift in the dataset are treated. We take advantage of the prior information on the size of the scatterers to minimize the false-detections and as a consequence, provide higher discrimination ability and more accurate particle counting. Numerical and real experiments are conducted to demonstrate the performance of the proposed search and cluster-assessment techniques. Our results illustrate that the proposed algorithm can detect surface contaminants correctly and effectively.

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Section: Benefit Of the Centroids Re-assignmentmentioning

confidence: 99%

Machine learning techniques applied for the detection of nanoparticles on surfaces using coherent Fourier scatterometry

Kolenov

Pereira²

2020

Opt. Express

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“…This regime of reticle particle contamination control (also called 'reticle defectivity') is beyond any other industrial application, and therefore is a key aspect of scanner system design 6 . The industry is pursuing a dual-path approach to reticle defectivity: advanced particle contamination control to ensure near-zero particles reaching the critical mask surface, and EUV-compatible pellicles 9 . The choice between these approaches balances costs versus risks and will depend on details of the device layer, the pellicle transmission and the defectivity performance 7 , and whether mitigations can be found in imaging 'tricks' 8 .…”

Section: Introductionmentioning

confidence: 99%

“…The choice between these approaches balances costs versus risks and will depend on details of the device layer, the pellicle transmission and the defectivity performance 7 , and whether mitigations can be found in imaging 'tricks' 8 . Pellicles are extremely thin freestanding films at a stand-off distance of a few mm from the reticle surface, which will keep any impinging particles out of focus so they will not image onto the wafer, as shown in figure 1; this allows for even >10 m-sized particles to be acceptable for wafer imaging 9 . However, in EUV, pellicles come at a cost of transmission, system productivity and system complexity 10 .…”

Section: Introductionmentioning

confidence: 99%

EUV pellicle scanner integration for N2 nodes and beyond

Kerkhof¹,

Klein

Seoane

et al. 2023

Optical and EUV Nanolithography XXXVI

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EUV lithography has been adopted worldwide for High-Volume Manufacturing (HVM) of sub-10nm node semiconductors. To support HVM, EUV pellicles were introduced by ASML in 2016. More recently, several novel pellicle materials have been developed to offer higher transmission and support higher source powers. The current focus is on two classes of pellicles to support the upcoming NXE:3800 and the associated N2 node, and beyond: Si-based composites and CNT-based pellicles. In this paper, we will give an overview of scanner integration results of current EUV pellicles, both Si-based composites and CNT-based pellicles. This overview will cover high-level aspects of transmission, imaging, robustness and lifetime; as well as underlying contributors such as EUV-uniformity, EUV-reflectivity, flare and DUV-reflectivity. Reviewing achieved performance will illustrate the suitability of these materials to support advanced nodes in production. Additionally, the anticipated future performance of EUV pellicles when used with increasing EUV source powers and high-NA scanners will be provided.

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“…Although the use of EUV pellicle is required to protect the mask and prevent external contaminants from printing on the wafer, the thickness and material of the pellicles are limited to ensure strong absorption in most materials, 88% EUV transmittance, and 0.04% reflectivity. 1,2,3 Therefore, it is essential to use pellicles with very high transmittance of several tens of nm and very thin thickness, which are 10 times thinner than those for the ArF process. Due to these structural features, pellicles can be easily damaged, deformed, or destroyed by various internal and external factors such as heat, stress, gravity, and external particle defects.…”

Section: Introductionmentioning

confidence: 99%

Estimation of mechanical stability of EUV pellicle by the collision of the particle defect

Kang

Choi

et al. 2022

International Conference on Extreme Ultraviolet Lithography 2022

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The pellicle prevents image errors due to contaminated particles in the EUV mask and protects the mask for a stable process. However, the lifetime of the pellicle could be shortened due to deformation and destruction caused by the collision of the particle defects in the chamber. Therefore, in order to increase the lifetime of the pellicle, it is required to develop an optimal pellicle material and structure that is resistant to deformation and destruction and has excellent mechanical stability. Accordingly, it is necessary to know the deformation caused by the particle collision and estimate the lifetime of the pellicles with different mechanical stability. In this study, we simulate the collision of particle defects for the pellicle and compare the mechanical stability depending on the single-layer pellicle materials.

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NXE pellicle: offering a EUV pellicle solution to the industry

Cited by 22 publications

References 1 publication

Machine learning techniques applied for the detection of nanoparticles on surfaces using coherent Fourier scatterometry

Machine learning techniques applied for the detection of nanoparticles on surfaces using coherent Fourier scatterometry

EUV pellicle scanner integration for N2 nodes and beyond

Estimation of mechanical stability of EUV pellicle by the collision of the particle defect

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