Virtual fabrication using directed self-assembly for process optimization in a 14-nm dynamic random access memory

Mattan Kamon; Mustafa B. Akbulut; Yiguang Yan; Daniel Faken; Andras Pap; Vasanth Allampalli; Ken Greiner; David M. Fried

doi:10.1117/1.JMM.15.3.031605

13 September 2016 Virtual fabrication using directed self-assembly for process optimization in a 14-nm dynamic random access memory

Mattan Kamon, Mustafa B. Akbulut, Yiguang Yan, Daniel Faken, Andras Pap, Vasanth Allampalli, Ken Greiner, David M. Fried

Author Affiliations +

Journal of Micro/Nanolithography, MEMS, and MOEMS, Vol. 15, Issue 3, 031605 (September 2016). https://doi.org/10.1117/1.JMM.15.3.031605

Abstract

For directed self-assembly (DSA) to be deployed in advanced semiconductor technologies, it must reliably integrate into a full process flow. We present a methodology for using virtual fabrication software, including predictive DSA process models, to develop and analyze the replacement of self-aligned quadruple patterning with Liu–Nealey chemoepitaxy on a 14-nm dynamic random access memory (DRAM) process. To quantify the impact of this module replacement, we investigated a key process yield metric for DRAM, interface area between the capacitor contacts and transistor source/drain. Additionally, we demonstrate virtual fabrication of the DRAM cell’s hexagonally packed capacitors patterned with an array of diblock copolymer cylinders in place of fourfold litho-etch (LE⁴) patterning.

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Mattan Kamon, Mustafa B. Akbulut, Yiguang Yan, Daniel Faken, Andras Pap, Vasanth Allampalli, Ken Greiner, and David M. Fried "Virtual fabrication using directed self-assembly for process optimization in a 14-nm dynamic random access memory," Journal of Micro/Nanolithography, MEMS, and MOEMS 15(3), 031605 (13 September 2016). https://doi.org/10.1117/1.JMM.15.3.031605

Published: 13 September 2016

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