Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Chinese Optics Letters
  • Vol. 7,
  • Issue 4,
  • pp. 286-290
  • (2009)

Reverse current reduction of Ge photodiodes on Si without post-growth annealing

Not Accessible

Your library or personal account may give you access

Abstract

A new approach to reduce the reverse current of Ge pin photodiodes on Si is presented, in which an i-Si layer is inserted between Ge and top Si layers to reduce the electric field in the Ge layer. Without post-growth annealing, the reverse current density is reduced to ~10 mA/cm2 at -1 V, i.e., over one order of magnitude lower than that of the reference photodiode without i-Si layer. However, the responsivity of the photodiodes is not severely compromised. This lowered-reverse-current is explained by band-pinning at the i-Si/i-Ge interface. Barrier lowering mechanism induced by E-field is also discussed. The presented "non-thermal" approach to reduce reverse current should accelerate electronics-photonics convergence by using Ge on the Si complementary metal oxide semiconductor (CMOS) platform.

© 2009 Chinese Optics Letters

PDF Article
More Like This
Low-power and high-detectivity Ge photodiodes by in-situ heavy As doping during Ge-on-Si seed layer growth

Yiding Lin, Kwang Hong Lee, Bongkwon Son, and Chuan Seng Tan
Opt. Express 29(3) 2940-2952 (2021)

Ge/Si heterojunction photodiodes fabricated by low temperature wafer bonding

Farzan Gity, Aidan Daly, Bradley Snyder, Frank H. Peters, John Hayes, Cindy Colinge, Alan P. Morrison, and Brian Corbett
Opt. Express 21(14) 17309-17314 (2013)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.