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Fuzzy logic approaches to the analysis of HREM images of III–V compounds
Author(s) -
Hillebrand R.
Publication year - 1998
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1046/j.1365-2818.1998.2830831.x
Subject(s) - fuzzy logic , similarity (geometry) , interface (matter) , composition (language) , interpretation (philosophy) , image (mathematics) , enhanced data rates for gsm evolution , chemical composition , materials science , resolution (logic) , fuzzy inference , biological system , computer science , algorithm , artificial intelligence , chemistry , physics , molecule , adaptive neuro fuzzy inference system , thermodynamics , fuzzy control system , biology , linguistics , gibbs isotherm , philosophy , organic chemistry , programming language
It is known that high‐resolution electron microscopy (HREM) can provide quantitative information on the properties of crystalline materials. The HREM patterns of layered structures of III–V semiconductors vary with the chemical composition of the latter within the sublattices, which is also influenced by interdiffusion. Local variations of the crystal cell similarity are recorded for image analysis and compared with templates of known material composition. Of the advanced theories of data interpretation, the now well‐established fuzzy logic is highly suited for corresponding image processing techniques. Combining neighbouring image cell similarities, the underlying chemical composition is evaluated by applying fuzzy logic criteria of inference to masks of about 1 nm × 1 nm in size. The new approach can be used to localize regions of significant changes in composition, i.e. edge detection, and to determine the composition across the interface region. The methods introduced prove successfully applicable to simulated as well as to experimental images of AlAs/Al x Ga 1− x As. Similarity/composition relations of nonlinear as well as nonmonotonic characteristics are studied to establish an alternative fuzzy logic approach.