Metallurgy – Steelmaking & Casting: Inclusion Evolution & Characterization

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Thursday, 22 October 2020 • 9–11 a.m. EDT
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PRESENTATIONS

Improved Accuracy in Inclusion Microanalysis

Petrus C. Pistorius, Carnegie Mellon University
Automated analysis of microinclusions (by scanning electron microscopy (SEM) and energy-dispersive x-ray (EDX) microanalysis) is an important practical tool for tracking steel quality and detecting process upsets. Accurate inclusion analysis relies on the detection of inclusions in the steel sample and on reliable EDX analysis. Microinclusions are similar in size to the "interaction volume" that is affected by the electron beam, and from which the characteristic x-rays are generated — with practical effects that include non-detection of smaller inclusions and distortion of the EDX analysis. The presentation will give practical guidance on quantifying spatial resolution, setting consistent image contrast and minimizing matrix effects in microanalysis. In addition to understanding what the SEM can detect and analyze, thermodynamic and kinetic analysis also helps to test the veracity of inclusion-analysis results. Examples that will be shown include analysis of magnesium-bearing oxides and sulfides in advanced high-strength steel and distinguishing between titanium oxide and nitride in interstitial-free steel.

Evaluation of the Iron Content in Non-Metallic Inclusions in Steel for (Sub)-Microscopic Steel Cleanness Description

Alexander Mayerhofer, Montanuniversität Leoben

Increasing customer demands for higher steel quality will require improved (sub-)micro cleanness descriptions in the near future. Due to the challenging analysis of matrix elements in non-metallic inclusions, the iron content of particles was often neglected in chemical evaluations up until now. Starting to close this gap of information, a systematic approach was developed, including statistic particle prediction, sample production on a laboratory scale and subsequent analysis evaluating the iron content in particles (<1 µm) by scanning electron microscopy/energy-dispersive x-ray spectroscopy measurements. This enables a detailed (sub-)micro cleanness description for steels ensuring the determination of correct compositions and an improved understanding of particle morphology for the smallest sizes.

Peritectic Behavior Detection in the Fe-C-Mn-Al-Si Steel System Using Fiber Optic Temperature Mapping

Damilola Balogun, Missouri University of Science and Technology
Mohammad Roman, Missouri University of Science and Technology

Peritectic behavior is often avoided through chemistry adjustment to avoid surface defects and breakouts in continuous casting. However, the combined effects of C, Mn, Al and Si on the boundaries for peritectic behavior are still disputed. A controlled solidification experiment was developed to characterize the effects of composition on the uniformity of shell growth during solidification using a copper chill mold with an embedded fiber optic temperature sensor. The spatially distributed sensor employs optical frequency domain reflectometry to measure temperatures with a 0.6 mm spatial resolution and a 20-ms measurement period to map closely spaced temperature features caused by the peritectic reaction.

MODERATOR

Chad Cathcart, Stelco Inc.

ORGANIZED BY

AIST’s Metallurgy – Steelmaking and Casting Technology Committee