journal article·2018-02

Spatially resolved localization and characterization of trapped hydrogen in zero to three dimensional defects inside ferritic steel

Waldemar Krieger, Sergiy V. Merzlikin, Asif Bashir, Agnieszka Szczepaniak, Hauke Springer, Michael Rohwerder

Acta Materialia· Volume 144
Publisher page

Abstract

Abstract In this work, localized hydrogen (H) detection measurements were conducted on a model ferritic (Fe 5 wt.-% Ni) steel which enables a systematic study of 0- (vacancies), 1- (dislocations), 2- (grain boundaries) and 3- (inclusions) dimensional defects, induced by varying mechanical and thermal treatments, without changing the chemical composition of the material. Spatially resolved detection with Scanning Kelvin Probe Force Microscopy (SKPFM) as an electrochemical technique with a resolution on a nanometric scale in combination with Thermal Desorption Spectroscopy (TDS) and microstructure characterization using electron microscopy indicated a domination of at least two trapping sites. Step by step the dominating H trapping sites were identified as dislocations and vacancies with estimated desorption energies of 29 ± 5 and 38 ± 5 kJ mol −1 . Furthermore, voids, inclusions and their interface to the matrix where found to be trapping sites binding low amounts of H, invisible for TDS measurements but detectible with SKPFM. Unexpectedly, no H was detected inside high angle grain boundaries. This study shows that dislocation and vacancies are the main trapping sites whereas vacancies getting increasingly important after cold rolling of steel rich of inclusions. Furthermore, the importance of using several techniques to understand the trapping behaviour of H even in simplified model alloys is underlined.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Hydrogen embrittlement and corrosion behaviors in metals · Corrosion Behavior and Inhibition · Microstructure and Mechanical Properties of Steels

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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