Trench and hole patterning with EUV resists using dual frequency capacitively coupled plasma (CCP)

沟槽 极紫外光刻 抵抗 等离子体刻蚀 等离子体 材料科学 光电子学 极端紫外线 纳米技术 半导体器件制造 蚀刻(微加工) 光学 物理 薄脆饼 激光器 图层(电子) 量子力学
作者
Yannick Feurprier,Katie Lutker-Lee,Vinayak Rastogi,Hiroie Matsumoto,Yuki Chiba,Andrew J. Metz,Kaushik Kumar,Genevieve Beique,Andre Labonte,Catherine B. Labelle,Yann Mignot,Bassem Hamieh,John Arnold
出处
期刊:Proceedings of SPIE 被引量:6
标识
DOI:10.1117/12.2086519
摘要

Patterning at 10 nm and sub-10 nm technology nodes is one of the key challenges for the semiconductor industry. Several patterning techniques are under investigation to enable the aggressive pitch requirements demanded by the logic technologies. EUV based patterning is being considered as a serious candidate for the sub-10nm nodes. As has been widely published, a new technology like EUV has its share of challenges. One of the main concerns with EUV resists is that it tends to have a lower etch selectivity and worse LER/LWR than traditional 193nm resists. Consequently the characteristics of the dry etching process play an increasingly important role in defining the outcome of the patterning process. In this paper, we will demonstrate the role of the dual-frequency Capacitively Coupled Plasma (CCP) in the EUV patterning process with regards to improving LER/LWR, resist selectivity and CD tunability for holes and line patterns. One of the key knobs utilized here to improve LER and LWR, involves superimposing a negative DC voltage in RF plasma at one of the electrodes. The emission of ballistic electrons, in concert with the plasma chemistry, has shown to improve LER and LWR. Results from this study along with traditional plasma curing methods will be presented. In addition to this challenge, it is important to understand the parameters needed to influence CD tunability and improve resist selectivity. Data will be presented from a systematic study that shows the role of various plasma etch parameters that influence the key patterning metrics of CD, resist selectivity and LER/LWR. This work was performed by the Research Alliance Teams at various IBM Research and Development Facilities.
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