Downscaling of semiconductor fabrication technology nodes brought forth a need to reassess the accuracy of 3D metrology. Accuracy is defined relative to a reference tool measurement. The authors have studied the accuracy of 3D SEM measurement results for various feature geometries and materials, matching the results to Monte Carlo simulations. Analysis of the SEM images based on an analytical model was performed. Accuracy of 3D algorithm for nominal process window monitoring is shown.
Monitoring the critical dimension (CD) of integrated circuit features is important for the process control of wafer fabrication. To serve this purpose, a CD tool has to measure the CD precisely and accurately. Moreover, since in many cases there are a number of CD tools that perform the measurements, the CD result should be tool independent: the control limits are learned on one tool, and should be applicable to all. The shrink of the technology puts very tight limits on the total precision, which includes both the single tool precision and the tool-matching tolerance. In order to get the required performance, the image quality of the tool should be the best possible, yet the same on all tools. To maintain good image quality, it should be routinely tested. In this paper we present an automatic image quality utility (IQU) that allows the user to perform such tests and take corrective action without having prior image processing knowledge. Our IQU integrates three basic measures: Signal to Noise Ratio (SNR), Contrast to Noise Ratio (CNR) and Resolution. The SNR and CNR are calculated on images, grabbed from a calibration wafer in pre-defined areas. The resolution is calculated from an image of a specific resolution target, at high magnification.
To minimize the effect of noise, our resolution measurement is calculated in the spatial domain, using information from the edge areas only. The utility calculates the edge location and direction, extracts the waveforms in the x and y directions, and computes the spatial resolution. We discuss the capabilities of this utility, and its use in improving tool performance. We demonstrate that the IQU detects even very small image quality degradations. Using the IQU results, a corrective activity of resolution, astigmatism, probe-current change, loss of detection efficiency or other can be made.
The IQU was developed and tested and is currently embedded on the VeritySEM SW.