Automated Identification and Characterization of Secondary & Tertiary gamma' Precipitates in Nickel-Based Superalloys (PREPRINT)

Abstract

The use of different electron loss edges in energy filtered transmission electron microscopy (EFTEM) has allowed researchers to capture images of the morphology and size of precipitates in nickel-based superalloys. In this work, we discuss a computational methodology for automated detection of secondary and tertiary gamma' precipitates in EFTEM images. The optimum parameters for the automated region growing technique were identified using a combination of visual inspection and intensity information from the EFTEM images. The microstructural statistics obtained from the segmented gamma' precipitates agreed with those of the manually segmented precipitates. Then, automated segmented precipitates are used to extract microstructural information about the distributions of equivalent diameters of 656 tertiary precipitates along with the distances to the nearest secondary precipitates. The significance of this technique is its ability to automate segmentation of precipitates in a reproducible manner for acquiring microstructural statistics that relate to both processing and properties.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2010
Accession Number
ADA522026

Entities

People

  • G. B. Viswanathan
  • J. S. Tiley
  • M. A. Tschopp

Organizations

  • Mississippi State University

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Computer Vision
  • Detection
  • Diagnostic Imaging
  • Diameters
  • Electron Microscopy
  • Electrons
  • Identification
  • Image Processing
  • Materials
  • Materials Science
  • Microscopy
  • Statistics
  • Transmission Electron Microscopy
  • United States
  • Visual Inspection

Readers

  • Artificial Intelligence
  • Image Processing and Computer Vision.
  • Materials Science (Mechanical Engineering).

Technology Areas

  • Microelectronics