TY - BOOK

T1 - Enhanced Characterization of Non-Metallic Inclusions for (Sub) Micro Steel Cleanness Evaluations

AU - Mayerhofer, Alexander

N1 - embargoed until null

PY - 2021

Y1 - 2021

N2 - A central part of research and development in metallurgy are analyses of steels´ microstructure and containing phases. Due to ever-increasing demands on steel cleanness, the evaluation of endogenous and exogenous non-metallic phases with decreasing sizes is more and more important in research and industry. The current thesis deals with the limits and potentials of scanning electron microcopy and energy dispersive spectrometry (SEM/EDS) of non-metallic inclusions (NMI) to handle future demands on inclusion analytics. Comprehensive literature research of different approaches for steel cleanness evaluations and particle analysis reveals SEM/EDS as one of the most essential measurement systems for steel research and secondary metallurgical process development. Constantly improving image resolution and detectors’ accuracy enables a wide range of chemical and morphological information of non-metallic inclusions. A thesis’s main task is to develop sound guidelines for a standardized inclusion detection and instructions for interpreting manual and automated SEM/EDS measurements in steel cleanness demands. Besides the influence of fundamental physical phenomena on the result, data post-processing and interpretation limits are discussed. The Potentials of SEM/EDS analysis are elaborated and summarized, leading to different approaches, guidelines, and innovative evaluation methods. Electron interaction simulations are used to better understand X-ray interaction volumes in non-metallic inclusions. As one result a particle size-depending mathematical model of the theoretical information share of matrix and inclusion composition is established. Comparing simulation of performed analysis and measurements, the potential of digital approaches dealing with metallurgical research problems is shown. A guide to manual point measurements and methods of electrolytic and chemical extraction are described to optimize SEM/EDS analysis experimentally. With the correct application of the procedures shown, composition and morphology evaluations, including matrix element contents in particles down to 300 nm in size, can be realized. First non-metallic inclusion standard samples for metallurgical demands are produced. To determine the iron content falsification at automated inclusion analysis, reference and standard samples are correlated, resulting in 80 % Fe overestimation for 0.3 - 0.5 µm sized inclusions. Additionally, a mathematical correction of matrix interaction based on standard and reference samples has been developed to improve particle analysis’s general output and evaluate particles´ Fe contents at steel cleanness evaluations. Furthermore, in addition to a new morphological categorization method, a size-dependent and direction-independent cluster identification method is developed based on inclusions´ morphology and position data of automated measurements. This methodology of morphological particle evaluation and categorization can be applied to all inclusion classes of all product types. The work concludes with a guideline for proper correction, classification, and typification of typical non-metallic inclusions at steel cleanness evaluations. The particle categorization methodology, defined as objective as possible, can be used to develop, evaluate and interpret particle populations or detailed analyses of specific metallurgical issues. Finally, the application of data evaluation and interpretation is demonstrated using various industrial samples. The interpretable result of measurements is optimized and improved by enhanced data correction and evaluation. The potential of properly evaluated automated analyses is shown and discussed. By basic treatment of SEM/EDS - analytics in metallurgical applications, further knowledge is generated leading to an essential work for future research projects and industry developments.

AB - A central part of research and development in metallurgy are analyses of steels´ microstructure and containing phases. Due to ever-increasing demands on steel cleanness, the evaluation of endogenous and exogenous non-metallic phases with decreasing sizes is more and more important in research and industry. The current thesis deals with the limits and potentials of scanning electron microcopy and energy dispersive spectrometry (SEM/EDS) of non-metallic inclusions (NMI) to handle future demands on inclusion analytics. Comprehensive literature research of different approaches for steel cleanness evaluations and particle analysis reveals SEM/EDS as one of the most essential measurement systems for steel research and secondary metallurgical process development. Constantly improving image resolution and detectors’ accuracy enables a wide range of chemical and morphological information of non-metallic inclusions. A thesis’s main task is to develop sound guidelines for a standardized inclusion detection and instructions for interpreting manual and automated SEM/EDS measurements in steel cleanness demands. Besides the influence of fundamental physical phenomena on the result, data post-processing and interpretation limits are discussed. The Potentials of SEM/EDS analysis are elaborated and summarized, leading to different approaches, guidelines, and innovative evaluation methods. Electron interaction simulations are used to better understand X-ray interaction volumes in non-metallic inclusions. As one result a particle size-depending mathematical model of the theoretical information share of matrix and inclusion composition is established. Comparing simulation of performed analysis and measurements, the potential of digital approaches dealing with metallurgical research problems is shown. A guide to manual point measurements and methods of electrolytic and chemical extraction are described to optimize SEM/EDS analysis experimentally. With the correct application of the procedures shown, composition and morphology evaluations, including matrix element contents in particles down to 300 nm in size, can be realized. First non-metallic inclusion standard samples for metallurgical demands are produced. To determine the iron content falsification at automated inclusion analysis, reference and standard samples are correlated, resulting in 80 % Fe overestimation for 0.3 - 0.5 µm sized inclusions. Additionally, a mathematical correction of matrix interaction based on standard and reference samples has been developed to improve particle analysis’s general output and evaluate particles´ Fe contents at steel cleanness evaluations. Furthermore, in addition to a new morphological categorization method, a size-dependent and direction-independent cluster identification method is developed based on inclusions´ morphology and position data of automated measurements. This methodology of morphological particle evaluation and categorization can be applied to all inclusion classes of all product types. The work concludes with a guideline for proper correction, classification, and typification of typical non-metallic inclusions at steel cleanness evaluations. The particle categorization methodology, defined as objective as possible, can be used to develop, evaluate and interpret particle populations or detailed analyses of specific metallurgical issues. Finally, the application of data evaluation and interpretation is demonstrated using various industrial samples. The interpretable result of measurements is optimized and improved by enhanced data correction and evaluation. The potential of properly evaluated automated analyses is shown and discussed. By basic treatment of SEM/EDS - analytics in metallurgical applications, further knowledge is generated leading to an essential work for future research projects and industry developments.

KW - SEM/EDS

KW - steel cleanness evaluation

KW - electron interaction

KW - interaction volume

KW - simulation

KW - manual SEM/EDS analysis

KW - automated SEM/EDS analysis

KW - X-ray interaction volume

KW - electrolytic extraction

KW - sequential chemical extraction

KW - twin jet-polishing

KW - inclusion standard production

KW - NMI standard

KW - Fe Quantification

KW - matrix interaction quantification

KW - sample selection

KW - thermodynamics

KW - kinetics

KW - (Fe

KW - Mn)Oxides

KW - oxide morphology

KW - Matrix Correction

KW - morphology categorization

KW - M-factor

KW - NMI spatial distribution

KW - feature evaluation

KW - correction

KW - classification

KW - typification

KW - iron correction

KW - cluster identification

KW - spatial distribution

KW - distance distribution

KW - influences on experiments

KW - phenomena EDS

KW - cutting position

KW - image

KW - artefacts

KW - composition evaluation

KW - Improvement Potentials

KW - inclusion formation

KW - simulated automated measurements

KW - homogenity

KW - heterogenity

KW - dissolution

KW - inclusion reference production

KW - NMI interpretation

KW - NMI evaluation

KW - data representation

KW - nichtmetallische Einschlüsse

KW - NME

KW - REM/EDX

KW - Reinheitsgrad

KW - Reinheitsgradbeurteilung

KW - Stähle

KW - Elektroneninteraktion

KW - Interaktionsvolumen

KW - Simulation

KW - manuelle REM/EDX-Analyse

KW - automatisierte REM/EDX analyse

KW - X-ray Interaktion

KW - chrakteristische Röntgenstrahlung

KW - elektrolytische Extraktion

KW - chemische extraktion

KW - sequentielle chemische Extraktion

KW - Einschluss-Standard Herstellung

KW - Einschluss Standard

KW - Standard

KW - Fe Quantifizierung

KW - Quantifizierung Matrixinteraktion

KW - Probenauswahl

KW - Thermodynamik

KW - Kinetik

KW - (Fe

KW - Mn)Oxide

KW - Oxidmorphology

KW - Einschlussformen

KW - Oxidformen

KW - Matrix Korrektur

KW - Morphologiekategorisierung

KW - M-Faktor

KW - räumliche Einschlussverteilung

KW - räumliche Verteilung

KW - Featureauswertung

KW - Einschlussauswertung

KW - Korrektur

KW - Klassifizierung

KW - Einschlussklassifizierung

KW - Typisierung

KW - Eisenkorrektur

KW - Clustererkennung

KW - Einschlusscluster

KW - Einschlussagglomerate

KW - Abstandsverteilung

KW - Einflüsse auf Experimente

KW - EDX Phänomene

KW - Schnittposition

KW - Bildaufnahme

KW - Artefakte

KW - Bestimmung der Zusammensetzung

KW - Verbesserungspotenziale

KW - Einschlussbildung

KW - simulierte automatisierte Messung

KW - Homogenität

KW - Heterogenität

KW - Auflösung

KW - Einschlussreferenzproben

KW - Interpretation

KW - Evaluierung

KW - Beurteilung

KW - Datendarstellung

M3 - Doctoral Thesis

ER -