In modern DRAM processes, there are some critical layers that are particularly challenging for overlay (OVL) control. The conventional method of metrology target design for these challenging layers is to verify target performance using simulation based on the specific, final device process. After full simulations, target measurability issues can be encountered where the limited, available solutions (open hard mask, create topography, etc.) are costly and high risk. However, in DRAM new product R&D, there is always some tolerance for process tuning. The use of virtual Archer™ OVL measurements in metrology target design (MTD) can simulate metrology performance for these potential process splits, helping to find a good balance between process options and metrology performance. A significant improvement in target contrast for imaging-based overlay (IBO) is demonstrated by simulation on one of these challenging layers after process optimization as compared to the baseline (BSL) process. In this paper we will present the virtual MTD detailed flow and design considerations to achieve an optimized process and target design. The contrast of a key performance indicator (KPI) is improved by more than 30%, enabling OVL measurability of the challenging layer in new processes.
For today’s advanced processes, in order to achieve higher optical lithography resolution, some of the layers require extreme dipole illumination conditions. One example is the modern DRAM process, where numerous critical layers are patterned with extreme dipole scanner illumination. Conventional (both imaging-based and diffraction-based) overlay marks on such layers typically use horizontal or vertical lines that suffer from insufficient accuracy in overlay device tracking. The new Diagonal AIM (DAIM™) overlay mark mimics the actual device through the usage of tilted structures. Significant improvement in device overlay tracking was demonstrated using the DAIM overlay mark.
Shrinking on-product overlay (OPO) budgets in advanced technology nodes require more accurate overlay measurement and better measurement robustness to process variability. Pupil-based accuracy flags have been introduced to the scatterometry-based overlay (SCOL) system to evaluate the performance of a SCOL measurement setup. Wavelength Homing is a new robustness feature enabled by the continuous tunability of advanced SCOL systems using a supercontinuum laser light source in combination with a flexible bandpass filter. Inline process monitoring using accuracy flags allows for detection, quantification and correction of shifts in the optimal measurement wavelength. This work demonstrates the benefit of Wavelength Homing in overcoming overlay inaccuracy caused by process changes and restoring the OPO and residual levels in the original recipe.
As semiconductor technology nodes keep shrinking, ever-tightening on-product overlay (OPO) budgets coupled with continuous process development and improvement make it critical to have a robust and accurate metrology setup. Process monitoring and control is becoming increasingly important to achieve high yield production. In recently introduced advanced overlay (OVL) systems, a supercontinuum laser source is applied to facilitate the collection of overlay spectra to increase measurement stability. In this paper, an analysis methodology has been proposed to couple the measured overlay spectra with overlay simulation to extract exact process information from overlay spectra. This paper demonstrates the ability to use overlay spectra to capture and quantify process variation, which in turn can be used to calibrate the simulation stacks used to create the SCOL (scatterometry-based overlay) and AIM overlay metrology targets, and can be fed into the fab for process monitoring and improvement.
In this paper we discuss the mechanism by which process variations determine the overlay accuracy of optical metrology. We start by focusing on scatterometry, and showing that the underlying physics of this mechanism involves interference effects between cavity modes that travel between the upper and lower gratings in the scatterometry target. A direct result is the behavior of accuracy as a function of wavelength, and the existence of relatively well defined spectral regimes in which the overlay accuracy and process robustness degrades (`resonant regimes’). These resonances are separated by wavelength regions in which the overlay accuracy is better and independent of wavelength (we term these `flat regions’). The combination of flat and resonant regions forms a spectral signature which is unique to each overlay alignment and carries certain universal features with respect to different types of process variations. We term this signature the `landscape’, and discuss its universality. Next, we show how to characterize overlay performance with a finite set of metrics that are available on the fly, and that are derived from the angular behavior of the signal and the way it flags resonances. These metrics are used to guarantee the selection of accurate recipes and targets for the metrology tool, and for process control with the overlay tool. We end with comments on the similarity of imaging overlay to scatterometry overlay, and on the way that pupil overlay scatterometry and field overlay scatterometry differ from an accuracy perspective.
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