Automatic statistical determination of dislocation density in production SOI substrates

Author

Allen, L.P. ; Genis, A. ; Jacobs, C. ; Allen, S.M. ; Snorrason, M. ; Zacharias, G.

Author_Institution

Ibis Technol. Corp., Danvers, MA, USA

fYear

1995

fDate

3-5 Oct 1995

Firstpage

32

Lastpage

33

Abstract

Summarizes a successful prototype demonstration of an automatic etch pit counting system which employs a neural network program for dislocation identification over a wide exponential range required for SOI material analysis. Overall results indicate that the automatic dislocation counting system is feasible to employ in SIMOX manufacturing. The neural network system exhibited sufficient capability for accurate dislocation density analysis of both standard and thin BOX SIMOX material, with clear recognition and classification of enhanced silicon defects

Keywords

SIMOX; dislocation density; dislocation etching; electronic engineering computing; elemental semiconductors; etching; neural nets; silicon; statistical analysis; BOX SIMOX material; SIMOX manufacturing; SOI material analysis; Si; automatic statistical determination; dislocation density; dislocation identification; enhanced silicon defects; etch pit counting system; neural network program; production SOI substrates; CMOS technology; Etching; Jacobian matrices; Low voltage; Neural networks; Production; Prototypes; Rivers; Silicon on insulator technology; Space technology;

fLanguage

English

Publisher

ieee

Conference_Titel

SOI Conference, 1995. Proceedings., 1995 IEEE International

Conference_Location

Tucson, AZ

Print_ISBN

0-7803-2547-8

Type

conf

DOI

10.1109/SOI.1995.526446

Filename

526446