Paper
27 March 2014 Recent progress on multiple-patterning process
Author Affiliations +
Abstract
The optical projection technique with evolution of Exposure wave length (λ) and Numerical Aperture (NA) has been historically driven Photolithographic scaling. Although the delay of EUV tool for HVM has been concerned, scaling is going on steadily after limitation of 193nm-immersion technique. Double patterning process has been firstly adopted in 30nm node device of memory device, and evolved step by step from SADP, SAQP to SAOP [1][2][3]. Self-Aligned Multiple-Patterning (SAMP) with 193-immersion is getting most promising technology for further downwards scaling at the present. For the extension of 193-immersion, many solutions in mask and illumination area were suggested, and these are represented by SMO (Source and Mask Optimization) and linked to “Computational lithography”. Furthermore, the change of device layout design to 1D (Single directional) layout [4] is the solution to mitigate several process issues, which are represented by process variability, pattern fidelity and Edge placement error (EPE). This paper presents the results of observing pattern fidelity in the multiple patterning process from many aspects and the results of testing a technique for high-accuracy management of pattern fidelity in 1D layout.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hidetami Yaegashi, Kenichi Oyama, Arisa Hara, Sakurako Natori, Shohei Yamauchi, and Masatoshi Yamato "Recent progress on multiple-patterning process", Proc. SPIE 9051, Advances in Patterning Materials and Processes XXXI, 90510X (27 March 2014); https://doi.org/10.1117/12.2046135
Lens.org Logo
CITATIONS
Cited by 6 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Line edge roughness

Etching

Optical lithography

Photomasks

Photoresist processing

Lithography

Source mask optimization

Back to Top