Corrosion behavior of ductile and austempered ductile cast iron in 0.01M and 0.05M NaCl Environments.

Ojo Jeremiah Akinribide, Samuel Olukayode Akinwamide, Olawale Olarewaju Ajibola, Babatunde Abiodun Obadele, Samuel Oloruntoba oluwagbenga Olusunle, Peter Apata Olubambi

Research output: Contribution to journalConference articlepeer-review

14 Citations (Scopus)

Abstract

In this investigation, the corrosion performance of ductile iron (DI) and austempered ductile cast iron (ADI) used in the production of engine sleeve was considered. The significant concentration of sodium chloride (0.01 M and 0.05 M) was utilized to analyse corrosion behaviour of both alloyed materials in the two environments. The microstructural images of the two distinct materials in each condition were resolved and diverse stages developed are mainly (carbides and the martensitic stage). Additionally, in Comparism with the DI and ADI not subjected to any condition, the consumption rate of DI was higher than that of ADI. The SEM was used to affirm the uniqueness of each phase. The two imperative components, for example, Cl- and Fe were assessed by SEM-EDS examination. The samples subjected to these conditions were appeared to have comparable corrosion attack. The nearness of delamination of oxide layers and oxidation was essential to each sample attempted under the 0.05 NaCl. As a result of silicon content, the DI indicates more oxidation at the surface accessible to the conditions. Thus, releases an impression of being the materials with the most raised corrosion resistance as a result of more broad scope of passive layers.

Original languageEnglish
Pages (from-to)167-172
Number of pages6
JournalProcedia Manufacturing
Volume30
DOIs
Publication statusPublished - 2019
Event14th Global Congress on Manufacturing and Management, GCMM 2018 - Brisbane, Australia
Duration: 5 Dec 20187 Dec 2018

Keywords

  • Austempered ductile iron
  • Chronopotentiometry
  • Ductile iron
  • Ferrite
  • Pearlite
  • Potentiodynamic

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Artificial Intelligence

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