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Red-Enhanced Photon Detection Module Featuring a 32 × 1 Single-Photon Avalanche Diode Array.
Ceccarelli, Francesco; Gulinatti, Angelo; Labanca, Ivan; Ghioni, Massimo; Rech, Ivan.
Afiliação
  • Ceccarelli F; Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy.
  • Gulinatti A; Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy.
  • Labanca I; Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy.
  • Ghioni M; Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy.
  • Rech I; Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy.
IEEE Photonics Technol Lett ; 30(6): 557-560, 2018 Mar 15.
Article em En | MEDLINE | ID: mdl-29581700
ABSTRACT
In this letter, the development and the experimental characterization of a new photon detection module, based on a 32×1 red-enhanced single-photon avalanche diode (RE-SPAD) array, are presented. A custom-developed technology has been exploited to design a detector having large-area pixels (50-µm diameter) with optimized performance. With an excess bias voltage Voυ = 15 V, a photon detection efficiency as high as 57% at 600 nm (33% at 800 nm) is achieved, along with dark count rate in the kHz range and optical crosstalk probability as low as 0.29%. The remarkable detection efficiency of the RE-SPAD array makes the module particularly suitable for all applications where high detection efficiency in the red/near-infrared range is mandatory. As an example, the performance of the array module is demonstrated to match the demanding requirements of multispot single-molecule fluorescence spectroscopy.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article