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Dark-field optical fault inspection of ∼10 nm scale room-temperature silicon single-electron transistors.
He, Wenkun; Chu, Kai-Lin; Abualnaja, Faris; Jones, Mervyn; Durrani, Zahid.
Afiliação
  • He W; Department of Electrical and Electronic Engineering, Imperial College London, South Kensington, London SW7 2AZ, United Kingdom.
  • Chu KL; Department of Electrical and Electronic Engineering, Imperial College London, South Kensington, London SW7 2AZ, United Kingdom.
  • Abualnaja F; Department of Electrical and Electronic Engineering, Imperial College London, South Kensington, London SW7 2AZ, United Kingdom.
  • Jones M; Department of Electrical and Electronic Engineering, Imperial College London, South Kensington, London SW7 2AZ, United Kingdom.
  • Durrani Z; Department of Electrical and Electronic Engineering, Imperial College London, South Kensington, London SW7 2AZ, United Kingdom.
Nanotechnology ; 34(50)2023 Oct 09.
Article em En | MEDLINE | ID: mdl-37725966
Dark-field (DF) optical microscopy, combined with optical simulation based on modal diffraction theory for transverse electric polarized white light, is shown to provide non-invasive, sub-wavelength geometrical information for nanoscale etched device structures. Room temperature (RT) single electron transistors (SETs) in silicon, defined using etched ∼10 nm point-contacts (PCs) and in-plane side gates, are investigated to enable fabrication fault detection. Devices are inspected using scanning electron microscopy, bright-field (BF) and DF imaging. Compared to BF, DF imaging enhances contrast from edge diffraction by ×3.5. Sub-wavelength features in the RT SET structure lead to diffraction peaks in the DF intensity patterns, creating signatures for device geometry. These features are investigated using a DF line scan optical simulation approximation of the experimental results. Dark field imaging and simulation are applied to three types of structures, comprising successfully-fabricated, over-etched and interconnected PC/gate devices. Each structure can be identified via DF signatures, providing a non-invasive fault detection method to investigate etched nanodevice morphology.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article