We have developed a massive on-cell overlay metrology system based on Mueller matrix measurements. By integrating microscopic techniques into ellipsometry, we achieved high-throughput and extensive sampling coverage, with 1-shot/field per 1-field of view (FOV) measurement capability within a 34 x 34 mm2 FOV. Analyzing the off-diagonal components of the Mueller matrix allowed for on-cell overlay measurement across the wafer. This system provides measurement sensitivity comparable to e-beam-based technologies while offering high coverage, enabling precise reticle correction or high-order overlay correction in photolithography processes. This advancement represents a significant improvement in overlay metrology, offering both sensitivity and resolution for enhanced semiconductor manufacturing processes.
In this paper, we propose an unique metrology technique for the measurement of three-dimensional (3D) nanoscale structures of semiconductor devices, employing imaging-based massive Mueller-matrix spectroscopic ellipsometry (MMSE) with ultra-wide field of view (FOV) of 20×20 mm2. The proposed system enables rapid measurement of 10 million critical dimension (CD) values from all pixels in the image, while the conventional point-based metrology technique only measures a single CD value. We obtain Mueller matrix (MM) spectrum by manipulating wavelength and polarization states using a custom designed optical setup, and show that the proposed method characterizes complex 3D structures of the semiconductor device. We experimentally demonstrate CD measurement performance and consistency in the extremely large FOV, and suggest that the combination of MMSE and massive measurement capability can provide valuable insights: fingerprints originated from the manufacturing process, which are not easily obtained with conventional techniques.
In recent years, the overlay specifications of advanced semiconductor devices have become extremely stringent. This challenging situation becomes severe for every new generation of the device development. However, conventional overlay metrology systems have limited throughput due to their point-based nature. Here, we first demonstrate the novel imaging Mueller-matrix spectroscopic ellipsometry (MMSE) technique, which can measure the overlay error of all cell blocks on a device wafer with extremely high throughput, much faster than conventional point-based spectroscopic ellipsometry (SE) technologies. It provides the super large field of view (FOV) ~ 20 × 20 mm2 together with high sensitivity based on Mueller information, which will be truly innovated solution not only for the overlay metrology, but also for critical dimension (CD) measurement, eventually maximizing process control and productivity of advanced node.
KEYWORDS: Data modeling, Semiconducting wafers, Metrology, Image processing, General packet radio service, Visual process modeling, Sensors, Chemical mechanical planarization, RGB color model
Measuring the thickness of thin films on a wafer is one of the most important steps for the semiconductor manufacturing process. This paper proposes a vision-based methodology for estimating a film thickness profile of the wafer. The scalability and industrial applicability of obtaining film thickness for the wafer with a small computational cost are demonstrated. Experimental results and numerical simulations are designed for investigating the characteristics of estimated solutions based on multiple representative nonlinear regression methods. The regression models are trained with the training data which consists of image value and thickness value pairs where the thickness value is obtained from the physical metrology system. There is an inevitable trade-off between the accuracy and the computational time in the spectrum-based film thickness measurement system in general, but the performance of the proposed methodology satisfied both the accuracy and the estimation time to a moderate extent.
Lensfree digital holographic technique can become a powerful microscopic solution by adequately adapting a super resolution(SR) method together with an advanced phase retrieval algorithm. However, it comes at the cost of acquiring multiple images as well as processing large volume of data. Here, we present a multi-height based SR technique that can maximize the signal to noise ratio and the resolution, approximately 2.5 times over the actual pixel size of an image sensor, while minimizing computational cost by utilizing the much less set of the sub-pixel shifted images compared to the conventional SR methods.
We demonstrate a high resolution lens-free holographic microscopy in reflection geometry based on a pixel super resolution (SR) method. The lens-free microscopy uses a novel Michelson geometry suitable to image reflective samples with the large field of view, while the Fourier domain SR technique is applied to obtain the high resolution hologram, achieving the sub-pixel resolution of 1.2 μm in the USAF reflection target by utilizing the randomly shifted low resolution images. The proposed compact microscopy technique enables to provide high resolution amplitude and phase imaging, those are suitable for biology and semiconductor imaging applications.
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