OPC model accuracy of dry resist readiness for 0.55NA EUVL by using low-n bright field mask

As High Numerical Aperture Extreme Ultraviolet Lithography (0.55NA EUVL) gets ready to step in the integrated circuit manufacturing world, advanced materials and patterning becomes very critical in terms of resolution, roughness, defectivity and process window. Among various combinations of mask absorber materials, mask tones and processes, bright field masks with utilization of negative-tone metal oxide resists (MORs) have emerged as one of the most promising candidates for 0.55NA EUVL patterning. Therefore, in this paper, we investigate the optical proximity correction (OPC) model accuracy of the dry resist process using a bright field low-n attenuated phase-shift mask. The use case is conducted on imec N2 (pitch 28nm) metal design, with wafer exposure performed using the imec NXE:3400 scanner. Thousands of OPC-relevant features are selected, and all the SEM images (both after develop inspection and after etch inspection) are acquired using a HITACHI CDSEM. The capability and accuracy of machine learning-based OPC models for resist (N2R) and etch (N2E) are studied.