Metrology of thin resist for high NA EUVL

Lorusso, Gian; Béral, Christophe; Bogdanowicz, Janusz; Simone, Danilo De; Hasan, Mahmudul; Jehoul, Christiane; Moussa, Alain; Saib, Mohamed; Zidan, Mohamed; Severi, Joren; Truffert, Vincent; Heuvel, Dieter Van den; Goldenshtein, Alex; Houchens, Kevin; Santoro, G; Fischer, Daniel; Muellender, Angelika; Hung, Jaclyn Y.; Koret, Roy; Turovets, Igor; Ausschnitt, Kit; Mack, Chris A.; Kondo, Tsuyoshi; Shohjoh, T.; Ikota, Masami; Charley, Anne-Laure; Leray, Philippe

doi:10.1117/12.2614046

Cited by 18 publications

(22 citation statements)

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“…It can be noted that image contrast varies among these samples, something we mainly ascribe to different secondary electron yield of each underlayer type. Within each thickness series, contrast also changes, although to a lesser extent than it has been reported in the case of thin photoresist films 10 . CAR patterning does not show any problem at the dose-to-size and best focus when used in conjunction with most of these underlayers.…”

Section: Resultsmentioning

confidence: 56%

“…Within each thickness series, contrast also changes, although to a lesser extent than it has been reported in the case of thin photoresist films. 10 CAR patterning does not show any problem at the dose-to-size and best focus when used in conjunction with most of these underlayers. One underlayer (H) showed mediocre adhesion and pattern collapse possibly due to mismatching surface energy with photoresist.…”

Section: Euv Lithography Performance On Scaled Underlayersmentioning

confidence: 91%

“…This problem is not specific to high-NA EUV: when pitch shrinks, aspect ratio of photoresist patterns increases which in turn leads to higher collapse probability during development and rinse 8 . To mitigate pattern collapse, photoresists for high-NA EUV will have to be thinner than those used today with detrimental consequences on the local critical dimension uniformity, line edge/width roughness (LER/LWR), process window, 9 and on signal-to-noise ratio of scanning electron microscopy (SEM) image acquisition 10 and data extraction 11 . Consequently, great effort is being put into investigating and predicting thin photoresist films performance ahead of high-NA EUV.…”

Section: Introductionmentioning

confidence: 99%

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Scaling and readiness of underlayers for high-numerical aperture extreme ultraviolet lithography

Fallica

Simone

Chen

et al. 2022

J. Micro/Nanopattern. Mats. Metro.

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.With the introduction of high-numerical aperture (NA) extreme ultraviolet (EUV) lithography, the thickness of layers in the lithographic stack will scale owing to reduced depth of focus and etch budget. The consequence of thinning down underlayers for EUV lithography has been scarcely investigated. In here, we assessed the readiness of nine state-of-the-art underlayers, spin-on and dry deposited, in thickness series down to 4 nm nominal. Preliminarily, the coating quality of these underlayers was evaluated. Thickness uniformity across 300 mm wafer ranged from about ±0.5 nm to < ± 0.05 nm depending on the coating technique employed. Surface roughness of the underlayers varied from as much as 0.63 nm to as low as 0.062 nm but was not impacted by thickness scaling. Film density and total surface energy varied by <10 % with thickness. EUV lithography of dense lines/spaces arrays of pitch 28 nm was carried out using a positive tone chemically amplified photoresist. Dose-to-size and exposure latitude changed by < ± 5 % when thickness of underlayer was decreased. Failure free process was at most 1 nm smaller for thinner underlayer than it was for the thinnest version of each type. The unbiased linewidth roughness increased consistently but limitedly (<5 % ) when thinner underlayers were used, mainly due to a reduction in the correlation length. By calculating the power spectral density of the blanket underlayer we can pinpoint this effect to a reduction of correlation length of the underlayer own surface roughness. Finally, Z-factor calculations demonstrated that overall photoresist performance depended more significantly on the specific underlayer type (±12.6 % ) than it did on underlayer thickness (±8 % ). All these results indicate that most of underlayers investigated had limited impact on the properties as well as the patterning performance when scaling in view of high NA EUV.

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Section: Resultsmentioning

confidence: 56%

Section: Euv Lithography Performance On Scaled Underlayersmentioning

confidence: 91%

Section: Introductionmentioning

confidence: 99%

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Scaling and readiness of underlayers for high-numerical aperture extreme ultraviolet lithography

Fallica

Simone

Chen

et al. 2022

J. Micro/Nanopattern. Mats. Metro.

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“…More specifically, the increased noise level of thin resist images has a direct impact on the unbiased Line Width Roughness (uLWR) measurement. 1 There are numerous noise sources in the SEM imaging process, arising from the multiple stages of signal generation and processing, and each of them contributes to the final captured image. These noise sources are characterized by their distinct physical nature and statistical aspects.…”

Section: Introductionmentioning

confidence: 99%

Extraction of roughness measurements from thin resists with low signal-to-noise-ratio (SNR) SEM images by applying deep learning denoiser

Zidan

Dey

Simone

et al. 2022

International Conference on Extreme Ultraviolet Lithography 2022

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Background: thin resists, below 30 nm, suffer from reduced imaging contrast and signal-to-noise ratio (SNR). This has an impact on the unbiased Line Width Roughness (uLWR) estimation, which becomes artificially low and hence is inaccurate when the SNR drops below certain limit, while reaching an accurate plateau value at higher SNR. Aim: improve the SNR of Scanning Electron Microscope (SEM) images in order to achieve a more reliable and robust roughness measurements on the thin resist, without having to increase the measurement electron dose. Approach: apply an unsupervised machine learning denoising algorithm to SEM raw images of thin resists on two different underlayers. The images were captured using different frame averaging (4, 8, 16, 32, and 64 frames). A systematic analysis is performed to compare the measurements before and after denoising. Results: after denoising, the SNR is improved, the mean CD stayed unchanged, and the roughness using smaller number of frames got closer to the accurate values, obtained using a larger number of frames. Conclusions: we have demonstrated that the use of a machine learning-based denoising algorithm enhances the SNR of SEM images without changing the mean CD and is beneficial for accurate and robust roughness measurements of thin resist.

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“…As we need to ensure pattern quality, resist metrology and failure analysis become challenging in the ultra-thin resist. In reference [2] the challenges associated with different metrology tools have been discussed. In this work, we will try to address the effect of Metal Oxide Resist (MOR) and Chemically Amplified Resist (CAR) thickness reduction on eP5 SEM image quality and programmed defect (PD) capture efficiency.…”

Section: Introductionmentioning

confidence: 99%

Influence of photoresist thinning and underlayer film on e-beam using eP5 for high-NA patterning

Hasan

Béral²,

Lorusso³

et al. 2022

International Conference on Extreme Ultraviolet Lithography 2022

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The introduction of Extreme Ultraviolet Lithography (EUVL) has been an extraordinary achievement in keeping Moore's law alive, as it minimizes the cost, time, and number of patterning steps required for device fabrication. However, as the advanced technology nodes require further scale down of the semiconductor devices, the current state-of-art EUVL tool, equipped with 0.33 Numerical Aperture (NA) and 13.5nm wavelength cannot print the features of interest with an acceptable yield. As a solution, a new generation of EUVL tool has been proposed (High-NA EUVL), having 0.55 NA and 8nm resolution. As a result of the increased NA, the depth of focus is reduced, thus thinner resist is required. Moreover, we need to restrict the aspect ratio of the features to avoid pattern collapse. For instance, resist thickness of approximately 30nm, which is typically used to print a 16nm half-pitch feature, cannot be applied to print an 8nm half-pitch feature, resist thickness must be lowered significantly to circumvent pattern collapse. However, the use of thin resist may have several negative effects on metrology and defect inspection. In this paper, we will discuss the influence of resist thickness and underlayer films on Scanning Electron Microscope (SEM) using ASML's eP5. For this study, we prepared a set of wafers with 16nm line-space (LS) patterns at different resist thicknesses using either Metal-Oxide Resist (MOR) or Chemically Amplified Resist (CAR). The case study compares both resist platforms on Spin on Glass (SoG) and Organic Underlayer (OUL).To conduct this study our BKM ADI eP5 SEM condition has been used.We observed that thinning down film thickness leads to deterioration of SEM image quality as well as loss of defect sensitivity during the inspection. In addition, varying the underlayers greatly affects both image quality and sensitivity. By decreasing the resist thickness, MOR and CAR were observed to behave in the same way, in terms of both image degradation and loss of sensitivity, although image quality did not degrade in the same way in the two cases.

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Metrology of thin resist for high NA EUVL

Cited by 18 publications

References 0 publications

Scaling and readiness of underlayers for high-numerical aperture extreme ultraviolet lithography

Scaling and readiness of underlayers for high-numerical aperture extreme ultraviolet lithography

Extraction of roughness measurements from thin resists with low signal-to-noise-ratio (SNR) SEM images by applying deep learning denoiser

Influence of photoresist thinning and underlayer film on e-beam using eP5 for high-NA patterning

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