Achieving a sub-10 nm nanopore array in silicon by metal-assisted chemical etching and machine learning

Yun Chen; Yanhui Chen; Junyu Long; Dachuang Shi; Xin Chen; Maoxiang Hou; Jian Gao; Huilong Liu; Yunbo He; Bi Fan; Ching-Ping Wong; Ni Zhao

doi:10.1088/2631-7990/abff6a

Solid-state nanopores with controllable pore size and morphology have huge application potential. However, it has been very challenging to process sub-10 nm silicon nanopore arrays with high efficiency and high quality at low cost. In this study, a method combining metal-assisted chemical etching and machine learning is proposed to fabricate sub-10 nm nanopore arrays on silicon wafers with various dopant types and concentrations. Through a SVM algorithm, the relationship between the nanopore structures and the fabrication conditions, including the etching solution, etching time, dopant type, and concentration, was modeled and experimentally verified. Based on this, a processing parameter window for generating regular nanopore arrays on silicon wafers with variable doping types and concentrations was obtained. The proposed machine-learning-assisted etching method will provide a feasible and economical way to process high-quality silicon nanopores, nanostructures, and devices.

Achieving a sub-10 nm nanopore array in silicon by metal-assisted chemical etching and machine learning

1 State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment, School of Electromechnical Engineering, Guangdong University of Technology, Guangzhou 510006, People's Republic of China

2 School of Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong

3 Guangdong ADA Intelligent Equipment Ltd, Foshan 510006, People's Republic of China

4 Institute of Business Analysis and Supply Chain Management, College of Management, Shenzhen University, Shenzhen, People's Republic of China

5 School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, GA 30332, United States of America

Publish Date: 2021-05-24

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Reference (35)

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Achieving a sub-10 nm nanopore array in silicon by metal-assisted chemical etching and machine learning

doi: 10.1088/2631-7990/abff6a

Abstract

Keywords

通讯作者: 陈斌, bchen63@163.com

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