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Title: Analysis of passivated A-286 stainless steel surfaces for mass spectrometer inlet systems by Auger electron and X-ray photoelectron spectroscopy and scanning electron microscopy

In this study, various commercially available surface treatments are being explored for use on stainless steel components in mass spectrometer inlet systems. Type A-286 stainless steel coupons, approximately 12.5 mm in diameter and 3 mm thick, were passivated with one of five different surface treatments; an untreated coupon served as a control. The surface and near-surface microstructure and chemistry of the coupons were investigated using sputter depth profiling using Auger electron spectroscopy, x-ray photoelectron spectroscopy, and scanning electron microscopy (SEM). All the surface treatments studied appeared to change the surface morphology dramatically, as evidenced by lack of tool marks on the treated samples in SEM images. In terms of the passivation treatment, Vendors A-D appeared to have oxide layers that were very similar in thickness to each other (0.7–0.9 nm thick), as well as to the untreated samples (the untreated sample oxide layers appeared to be somewhat larger). Vendor E’s silicon coating appears to be on the order of 200 nm thick.
Authors:
 [1] ;  [1] ;  [1]
  1. Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)
Publication Date:
OSTI Identifier:
1159175
Report Number(s):
SRNL-STI--2014-00038
Journal ID: ISSN 2192-9262
Grant/Contract Number:
AC09-08SR22470
Type:
Accepted Manuscript
Journal Name:
Metallography, Microstructure, and Analysis
Additional Journal Information:
Journal Volume: 3; Journal Issue: 4; Journal ID: ISSN 2192-9262
Publisher:
Springer
Research Org:
Savannah River Site (SRS), Aiken, SC (United States)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE Tritium; surface passivation; X-ray photoelectron spectroscopy (XPS); Auger electron spectroscopy (AES); scanning electron spectroscopy (SEM); sputter depth profile