Measurement of Si trench depth and width critical dimensions (CDs) is an important aspect of shallow trench isolation (STI) process development. The ideal method of measurement is completely non-destructive and has high throughput. However, depth measurement using a Profiler involves contact or potential contact with the wafer surface, is generally not deemed a high throughput solution, and does not provide line width CD information. CD-SEM measurement, on the other hand, provides line width CDs and is faster than using a Profiler, but does not measure trench depth. It can also lead to localized damage and CD variation due to charging effects. Optical Digital Profilometry (ODP), also known as scatterometry, allows for a completely non-destructive, high throughput approach to collecting both CD and depth information. In this paper, we describe the application of ODP for STI process monitoring and compare this approach to older, more firmly entrenched techniques.
We studied gate line edge roughness (LER) and its effect on electrical characteristics of 50nm bulk MOSFETs. Using simulation, we studied the underlying mechanism of three significant LER effects on the electrical performance of advanced 50 nm gate length bulk devices. First, we found that off-state leakage current is much more sensitive than the on-state drive current to gate LER. Second, we found that high frequency LER can lead to a decrease in effective channel length by enhanced lateral diffusion of the self-aligned source/drain extension. Third, low frequency LER causes local CD variation simply due to the statistical variation of average CD in a finite width sample. We also show how device design parameters, such as halo implant dose, can be used to tradeoff LER sensitivity and device performance.
In this paper, we describe the application of the edge width measurement to the monitoring of contact hole openings in an attempt to evaluate its ultimate limitations due to tool resolution, measurement algorithm, and process sensitivity. Substantial variations in the top-down SEM image and waveform translated to smaller but still detectable variations in measured edge width using a max slope/linear regression algorithm. The images and waveforms indicate the top-down SEM resolution to be sufficient to detect process variations, but the measured results suggest optimization of the algorithms for this specific purpose will be necessary.
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