Roll-to-roll reactive ion etching of large-area nanostructure arrays in Si: Process development, characterization, and optimization

Author:

Ghaznavi Ziam12ORCID,Butcher Nicholas2ORCID,Djurdjanovic Dragan1ORCID,Sreenivasan S. V.1ORCID

Affiliation:

1. Walker Department of Mechanical Engineering, Cockrell School of Engineering, The University of Texas at Austin 1 , Austin, Texas 78712

2. Emerson and Renwick Ltd., Peel Bank Works 2 , Church, Accrington BB5 4EF, United Kingdom

Abstract

Roll-to-roll (R2R) nanofabrication processes are recognized as key enabling-technologies for many next-generation applications in flexible electronics, displays, energy generation, storage, as well as healthcare. However, R2R processing techniques reported in the literature currently lack a scalable method of performing high-throughput nanoscale pattern transfer of geometry requiring a high degree of fidelity in terms of critical dimension resolution, etch uniformity, and aspect ratio. Reactive ion etching (RIE) addresses the need for sub-10 nm pattern transfer with large-area uniformity in wafer-scale semiconductor manufacturing, but adapting plasma etch systems for use in R2R nanopatterning has proven to be nontrivial. Moreover, robust models for simulating R2R RIE do not exist, which is an obstacle to the creation of computational approaches to design, control, and scale-up of nanoscale R2R equipment and processes. To address these challenges, we demonstrate a process flow for fabricating Si nanopillar arrays utilizing a combination of nanoimprint lithography and RIE with all pattern transfer steps performed using a R2R plasma reactor system. Specifically discussed are process development details for etching imprint resist and Si including etch rates, cross-web etch uniformity, etch directionality, and etch selectivity at varying gas chemistries, powers, and pressures. 2k full-factorial Design of Experiments (DoEs) and ordinary least-squares regression analysis are also employed to study influence of process parameters on multiple outgoing etch quality characteristics and generate stochastic models of the R2R RIE pattern transfer process into Si. Utilizing these DOE-based models and desired targets for etch quality characteristics, we describe a bounded multivariate inverse-optimization scheme for automated etch process parameter tuning. The culmination of these efforts, to the best of the authors' knowledge, is the first reported RIE-based pattern transfer of 100 nm-scale features performed in continuous R2R fashion with control of feature geometry over large area. The methodology employed herein may be applied similarly to additional materials and geometries for future applications.

Funder

National Science Foundation

Cockrell School of Engineering, University of Texas at Austin

Cockrell Endowed Chair Funds

Publisher

American Vacuum Society

Subject

Materials Chemistry,Electrical and Electronic Engineering,Surfaces, Coatings and Films,Process Chemistry and Technology,Instrumentation,Electronic, Optical and Magnetic Materials

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