In the microelectronics industry, most of the dimensional metrology relies on critical dimension (CD) estimation. These measurements are mainly performed by critical dimension scanning electron microscopy, because it is a very fast, mainly nondestructive method and enables direct measurements on wafers. To measure CDs, the distance is estimated between the edges of the observed pattern on an SEM image. As the CD becomes smaller and smaller, the needs for more reliable metrology techniques emerge. In order to obtain more meaningful and reproducible CD measurements regardless of the pattern type (line, space, contact, hole, etc.), one needs to perform a CD measurement at a known and constant height due to a methodology that determines the topographic shape of the pattern from SEM images. An SEM capable of bending the electron beam (up to 12 deg in our case) allows images to be caught at different angles, giving access to more information. From the analysis of such images, pattern height and sidewall angles can be determined using geometric considerations. Understanding interaction between three-dimensional (3-D) shapes, pattern materials, and the electron beam becomes essential to correlate topography information. A preliminary work based on Monte–Carlo simulations was conducted using JMONSEL, a software developed by the National Institute of Standards and Technology. With this analysis, it is possible to determine theoretical trends for different topographies and beam tilt conditions. Due to the effects highlighted by simulations, the processing of the tilted beam SEM images will be presented, as well as the method used to create a mathematical model allowing topographic reconstruction from these images. Finally some reconstruction using this model will be shown and compared to reference measurements. The overall flow used to process images is presented. First, images are transformed into grayscale profiles. After a smoothing procedure, positional descriptors are computed for specific profile derivatives values. Then, from these descriptors coming from two images of the same pattern taken at different tilt angles, we use a low-complexity linear model in order to obtain the geometrical parameters of the structure. This model is created and initially calibrated using JMONSEL simulations and then recalibrated on real silicon patterns. We demonstrate that the use of real SEM images coming from real silicon patterns with our model leads to results that are coherent with conventional 3-D measurements techniques taken as reference. Moreover, we are able to make reliable reconstructions on patterns of various heights with a single calibrated model. Our batch of experiment shows a three-sigma standard deviation of 10 nm on the estimated height for heights ranging from 50 nm to more than 200 nm. Based on simulations, we are able to reconstruct the corner rounding (CR) from SEM images. However, because our wafer has no CR variability, measurements still need to be assessed on real wafer.
In order to obtain more meaningful and reproducible CD measurements regardless of the pattern type (line, space, contact, hole . . . ), one needs to perform a CD measurement at a known and constant height thanks to a methodology that determines the topographic shape of the pattern from SEM images. A SEM capable of bending the electron beam (up to 12° in our case) allows to catch images at different angles, giving access to more information. From the analysis of such images, pattern height and sidewall angles can be consequently determined using geometric considerations.1
Understanding interactions between 3D shapes, pattern's material and the electron beam, becomes essential to correlate topography information. A preliminary work based on Monte-Carlo simulations was conducted using JMONSEL, a software developed by the NIST.
Thanks to this analysis, it is possible to determine theoretical trends for different topographies and beam tilt conditions. Thanks to the effects highlighted by simulations, the processing of the tilted beam SEM images will be presented, as well as the method used to create a mathematical model allowing topographic reconstruction from these images. Finally some reconstruction using this model will be shown and compare to reference measurements.
The overall flow used to process images is presented. First, images are transformed into grayscale profiles in order to process them. After a smoothing procedure, positional descriptors are computed for specific profile derivatives values. Then, from these descriptors coming from two images of the same pattern taken at different tilt angles, we use a low-complexity linear model in order to obtain the geometrical parameters of the structure. This model is created and calibrated thanks to JMONSEL simulations and then re-calibrated on real silicon patterns.
We demonstrate that the use of real SEM images coming from real silicon patterns with our model leads to results that are coherent with conventional 3D measurements techniques taken as reference. Moreover, we are able to make reliable reconstructions on patterns of various heights with a single calibrated model. Our batch of experiment shows a 3-sigma standard deviation of 13% on the estimated height.
We also show, thanks to simulations, that we are able to reconstruct the corners rounding (CR) from SEM images. However, because our wafer do not present a variability, the CR measurements still need to be assessed.
Even if the dimensions to consider are higher than in advanced IC nodes, microlenses are sensitive to process variability during lithography and reflow. A good control of the microlens dimensions is key to optimize the process and thus the performance of the final product.
The purpose of this paper is to apply SEM contour metrology [1, 2, 3, 4] to microlenses in order to develop a relevant monitoring methodology and to propose new metrics to engineers to evaluate their process or optimize the design of the microlens arrays.
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