Affiliations 

  • 1 Department of Electronic and Electrical Engineering, University of Sheffield, Sheffield, S1 3JD, UK
  • 2 Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA, 22904, USA
  • 3 Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH, 43210, USA
  • 4 California NanoSystems Institute, University of California, Los Angeles, CA, 90095, USA
  • 5 Faculty of Engineering, Multimedia University, 63100, Cyberjaya, Malaysia
  • 6 Department of Electronic and Electrical Engineering, University of Sheffield, Sheffield, S1 3JD, UK. j.p.david@sheffield.ac.uk
Sci Rep, 2023 Jun 19;13(1):9936.
PMID: 37336988 DOI: 10.1038/s41598-023-36744-7

Abstract

Al0.85Ga0.15As0.56Sb0.44 has recently attracted significant research interest as a material for 1550 nm low-noise short-wave infrared (SWIR) avalanche photodiodes (APDs) due to the very wide ratio between its electron and hole ionization coefficients. This work reports new experimental excess noise data for thick Al0.85Ga0.15As0.56Sb0.44 PIN and NIP structures, measuring low noise at significantly higher multiplication values than previously reported (F = 2.2 at M = 38). These results disagree with the classical McIntyre excess noise theory, which overestimates the expected noise based on the ionization coefficients reported for this alloy. Even the addition of 'dead space' effects cannot account for these discrepancies. The only way to explain the low excess noise observed is to conclude that the spatial probability distributions for impact ionization of electrons and holes in this material follows a Weibull-Fréchet distribution function even at relatively low electric-fields. Knowledge of the ionization coefficients alone is no longer sufficient to predict the excess noise properties of this material system and consequently the electric-field dependent electron and hole ionization probability distributions are extracted for this alloy.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.