2016Journal of Micro/Nanolithography MEMS and MOEMSRequires access

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

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

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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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What this paper is about

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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Available 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.

Key concepts: Dram, Dynamic random-access memory, Fabrication, Random access, Process (computing), Capacitor, Computer science, Interface (matter)

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