With constant push for smaller and faster devices photo mask technology has become the most critical part of the entire integrated circuit (IC) production flow. Mask inspection and mask defect repair are increasingly important components of advanced photo mask technology. The low cost of mask manufacturing and the necessity of delivering photo masks to production floor in the shortest possible time require new photo mask specs and acceptance criteria. It is no longer economically viable to reject a photo mask because some mask anomalies were found, or repair all the defects detected by state of the art inspection tool. One should use a smart approach to separate tolerable mask anomalies from real mask defects that might negatively affect device yield. However, this is not a trivial task. With rising mask complexity (e.g., binary masks with aggressive optical proximity correction or phase-shifting masks (PSM)-attenuated and alternating) and inspection and metrology tools running out of steam, new technologies such as the AIMSTMand Virtual Stepper® system must be used to sort nuisance mask defects from real ones. This will help to reduce the number of required defect repairs and shorten mask
manufacturing cycle time. However, it is very difficult to utilize AIMS in the production environment because of its low operational speed; the Virtual Stepper software, in its turn, relies on mask data captured by inspection/metrology hardware. In the case of phase masks, such as Attenuated PSM (especially high transmission EAPSM) and Alternating PSM, inspection tools are not able to accurately retrieve optical properties of mask materials; as a result defect analysis is becoming very difficult and unreliable task. Very common types of PSM defects that occur during mask manufacturing and repair processes are the so-called distributed defects, such as gallium stains, riverbeds, pinhole clusters, and large chrome residuals (on
EAPSM). It is very difficult to get accurate information about the transmittance and phase of these defects at actinic wavelength using inspection and metrology tools. With a simulation study one can reconstruct such mask defects, and by varying defect phase and transmission one can learn about the impact of such mask defects on printed wafers. In addition, lithography simulation helps to better understand how mask defects behave under different lithography process conditions. In our previous research on photo mask distributed defects (this work was presented at 18th European mask conference, Munich 20021) we looked into several cases of distributed mask defects such as large chrome residuals and clustered pinholes on
EAPSM. We found a relationship between photo mask defect transmissivity and resulting printed wafer critical dimension
(CD) error.CD variations (systematic and random mask CD errors) across the photo mask represent a common type of yield killing distributed defects. Systematic errors can be analyzed and fixed by applying different corrective methods (e.g. LPC, OPC). The negative effect of random errors can be minimized by selecting the most robust manufacturing process, and by choosing optimal lithography options (RETs). In this paper we investigated randomly distributed CD errors. Monte Carlo simulation has been used to emulate large numbers (10000 - 40000) of mask random CD errors.