Scatterometry and machine learning for in-die overlay solution

Yeh, FangJyun; Chouaib, Houssam

doi:10.1117/12.2657946

Cited by 5 publications

(5 citation statements)

References 7 publications

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“…Each critical parameter model will be optimized independently, suggesting its advantage in increasing the sensitivity which also reducing the correlation between different parameters of interest, thus providing more freedom of parameter selection compared to the conventional RCWA model with limited floating parameters. Detailed information on this approach applied to both logic and DRAM cases can be found elsewhere [15,16]. The overall workflow of a 3D flash memory channel hole metrology solution using a physics-based ML approach is displayed in Figure 3.…”

Section: Methodsmentioning

confidence: 99%

Leveraging x-ray scatterometry and machine learning to enable robust and high-throughput optical critical dimension metrology for advanced 3D flash memory contact hole profile

Chouaib,

Shi,

Chou

et al. 2024

Metrology, Inspection, and Process Control XXXVIII

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3D flash memory structures have been rapidly developed over the past decade to achieve a high density of stacked memory cells with periodic channel holes across the device. Small deviations of the hole shape can result in considerable variations in device performance and product yield. Understanding the behavior and performance of these high-aspect-ratio structures plays a vital role in such complex vertically stacked structures. Memory hole critical dimensions (CDs) serve as the key information to evaluate the performance of 3D flash memory devices, and these CDs are typically measured by rigorous coupled wave analysis (RCWA) based optical metrology that requires costly and destructive scanning electron microscopy (SEM) or transmission electron microscopy (TEM) reference.Here, we utilize critical dimension smallangle X-ray scatterometry (CD-SAXS) that provides reliable and nondestructive ground truth reference to extract a large amount of detailed hole shape information within a practical time scale compared to traditional lengthy TEM measurements. We leverage advanced data analytics and machine learning techniques to enable an optical critical dimension metrology solution along with the desired amount of reference from CD-SAXS measurements for the memory hole profile investigation. This proposed methodology opens up a new venue for a high-throughput, robust and accurate hole CD profile measurement for the fast-paced and high-volume 3D flash memory manufacturing technology.

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Section: Methodsmentioning

confidence: 99%

Leveraging x-ray scatterometry and machine learning to enable robust and high-throughput optical critical dimension metrology for advanced 3D flash memory contact hole profile

Chouaib,

Shi,

Chou

et al. 2024

Metrology, Inspection, and Process Control XXXVIII

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“…Taking advantage of the high throughput of the optical system and the sensitivity to the overlay structure of the Mueller signal, our solution fulfills two key requirements of the inline overlay control in the high-volume manufacturing (HVM) environment: high-frequency measurement and good stability. Figure 8 illustrates the inline wafer-to-wafer overlay measurement performance, and library quality KPI, CIndex [9]. From the chart, stable overlay measurement within +/-10% OPO without trending can be observed, and the CIndex also maintains a flat trend.…”

Section: Inline Wafer Measurement Robustnessmentioning

confidence: 99%

“…Spectroscopic ellipsometry (SE) has been recognized as a powerful tool for thin film and critical dimension (CD) measurement as a robust metrology solution in the semiconductor fabrication process due to its non-destructive and high throughput characteristics. Furthermore, as an optical solution, SE offers the advantages of relatively high throughput and precision vs. other overlay metrology solutions, such as CD-SEM [1][2][3][4][5][6][7][8][9]. The superior Mueller matrix technique in spectroscopic ellipsometry, implemented onKLA's advanced SpectraShape 11k metrology system, offers comprehensive structure information and sensitivity to structure asymmetry variation such as overlay and tilt.…”

Section: Introductionmentioning

confidence: 99%

Enable in-die overlay measurement on DRAM storage node by line scan self-calibration method

Yeh,

Tsai,

Lin

et al. 2024

Metrology, Inspection, and Process Control XXXVIII

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Semiconductor layer-to-layer overlay in manufacturing significantly impacts product quality and yield performance. Good control of device shifting also influences the spatial scale down for the nanoelectronics of memory applications. Advanced node DRAM semiconductor manufacturing requires a tighter in-die overlay budget.Typically, the inline overlay is measured by using a designed target in the scribe line. However, the difference between the metrology target and in-die device structure can lead to errors that can impact product quality and yield. This is especially true for complex structures such as the DRAM storage hole to landing pad overlay that cannot be well fabricated in the small target area. To meet the required tighter overlay control budget, the ability to measure in-die is essential.In this work, we introduce and demonstrate the line scan self-calibration solution for accurate and robust in-die overlay measurement of the storage node layer to the landing pad layer. Real spectra are collected by SpectraShape™ 11k dimensional metrology system where overlay splits are trained against the intended overlay and the SpectraShape 11k indevice overlay results are qualified by Set (designed overlay value from lithography), Get (overlay value measured by metrology tool) and TEM. Moreover, theoretical and experimental data show that the SpectraShape 11k Mueller elements are sensitive to tiny changes in the overlay parameters, which can enable robust, inline, high throughput overlay metrology. We demonstrate that the SpectraShape 11k successfully measures the in-die overlay of the complex storage hole to the landing pad structure with good accuracy and high throughput thereby contributing to improved process control and yield improvement.

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“…Furthermore, as an optical solution, SE offers the advantages of relatively high throughput and precision versus other overlay metrology solutions, such as CD-SEM. [8][9]. This work introduces a physical-based machine-learning algorithm [10][11][12] recipe that is capable of in-die overlay measurement by training both real spectra collected from SpectraShape 11k and theoretical spectra generated from the scatterometry model against the corresponding reference to predict the overlay value.…”

Section: Introductionmentioning

confidence: 99%

Optical in die NZO benefit for DRAM manufacturing

Yeh,

Tsai,

Chu

et al. 2024

Metrology, Inspection, and Process Control XXXVIII

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Today, with the accelerating complexity of nanoelectronics for memory applications, in-die overlay metrology has required much tighter control. A typical in-device overlay control strategy utilizes high-voltage SEM metrology across several key layers, but lot and wafer sampling is limited due to low system throughput. Our objective is to find a faster, more robust, and more efficient optical metrology solution that can produce the same in-die overlay results vs. SEM. In this work, we create a novel solution using the KLA SpectraShape™ 11k dimensional metrology system to demonstrate improved nonzero overlay (NZO) control that meets the tighter overlay budget requirement.We combined the spectroscopic Mueller matrix of SpectraShape 11k and the machine learning algorithm of TurboShape™ modeling software. Both real spectra collected by SpectraShape 11k and theoretical spectra generated from the scatterometry model are trained against their corresponding SEM reference and synthetic reference data respectively to predict the overlay value. Accurate and robust optical in-device overlay results are proven with a high correlation to the HV-SEM data. In addition, the SpectraShape 11k in-device overlay is equipped with a few key performance indicators (KPIs) including CIndex™ and CD profile, which are designed to flag process excursions in an HVM environment. Good agreement is observed between the KPIs and overlay delta to HV-SEM. Finally, the 4x-8x throughput advantage of optical metrology in-device overlay vs. SEM in-device overlay allows users to set more dense wafer measurements by lot or dense site measurements by wafer, enabling better lot-to-lot or wafer-to-wafer NZO control.

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Scatterometry and machine learning for in-die overlay solution

Cited by 5 publications

References 7 publications

Leveraging x-ray scatterometry and machine learning to enable robust and high-throughput optical critical dimension metrology for advanced 3D flash memory contact hole profile

Leveraging x-ray scatterometry and machine learning to enable robust and high-throughput optical critical dimension metrology for advanced 3D flash memory contact hole profile

Enable in-die overlay measurement on DRAM storage node by line scan self-calibration method

Optical in die NZO benefit for DRAM manufacturing

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