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Characterisation of a novel reverse-biased PPD CMOS image sensor

Stefanov, Konstantin; Clarke, Andrew; Ivory, James and Holland, Andrew (2017). Characterisation of a novel reverse-biased PPD CMOS image sensor. Journal of Instrumentation, 12(11), article no. C11009.

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A new pinned photodiode (PPD) CMOS image sensor (CIS) has been developed and characterised. The sensor can be fully depleted by means of reverse bias applied to the substrate, and the principle of operation is applicable to very thick sensitive volumes. Additional n-type implants under the pixel p-wells, called Deep Depletion Extension (DDE), have been added in order to eliminate the large parasitic substrate current that would otherwise be present in a normal device. The first prototype has been manufactured on a 18 μm thick, 1000 Ω .cm epitaxial silicon wafers using 180 nm PPD image sensor process at TowerJazz Semiconductor. The chip contains arrays of 10 μm and 5.4 μm pixels, with variations of the shape, size and the depth of the DDE implant. Back-side illuminated (BSI) devices were manufactured in collaboration with Teledyne e2v, and characterised together with the front-side illuminated (FSI) variants. The presented results show that the devices could be reverse-biased without parasitic leakage currents, in good agreement with simulations. The new 10 μm pixels in both BSI and FSI variants exhibit nearly identical photo response to the reference non-modified pixels, as characterised with the photon transfer curve. Different techniques were used to measure the depletion depth in FSI and BSI chips, and the results are consistent with the expected full depletion.

Item Type: Journal Item
Copyright Holders: 2017 IOP Publishing Ltd and Sissa Medialab
ISSN: 1748-0221
Extra Information: 11 p.
Keywords: ultraviolet photon detectors; visible photon detectors; infra-red photon detectors; detector modelling and simulations; CMOS image sensor; pinned photodiode (PPD); depletion depth; reverse bias
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Physical Sciences
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Electronic Imaging (CEI)
Item ID: 52481
Depositing User: Konstantin Stefanov
Date Deposited: 27 Nov 2017 11:01
Last Modified: 02 May 2019 02:53
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