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Integrated Experimental and Computational Study of Precipitation in Martensitic Steels
KTH, School of Industrial Engineering and Management (ITM), Materials Science and Engineering, Physical Metallurgy. KTH Royal Institute of Technology. (Unit of Structures)ORCID iD: 0000-0002-1029-233X
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Precipitation is a phase transformation process in metallic materials that significantlyaffects properties. The precipitation process that includes nucleation, growth andcoarsening of small particles can be tuned by alloying, deformation, thermal treatment.This opens opportunities for optimizing the properties of metallic materials bytailoring precipitation. An example of high-performance metallic materials withcontribution from precipitation is tempered martensitic steels. By means of highlydispersed nanoscale precipitates within the hierarchic martensitic microstructure,these steels achieve an excellent combination of ultra-high strength and hightoughness. With the objective of accelerating the development of these high-performance steels, an integrated computational materials engineering (ICME)approach, combining advanced characterization, physically based/semi-empiricalmodelling, theory and databases, is used in this thesis to develop computationallinkages from heat treatment to precipitation to strength.Two multicomponent steels, a Cu precipitation-hardened maraging stainless steel anda carbide-strengthened low alloy Cr – Mo – V martensitic steel, are studied in this thesisusing quantitative characterization and modelling. The results suggest that theprecipitation simulations using Langer-Schwartz-Kampmann-Wagner (LSKW)modelling have good agreements with the experiments and show promise for futurepredictive modelling to be used for materials design. The semi-empirical models forindividual strengthening mechanisms and an integration of the strengtheningmechanisms used in this work may also represent the trends in the yield strength offresh and tempered martensite, but it is difficult to predict the early yielding of freshmartensite and the correlation of hardness and strength. This indicates the need tofurther develop the models. Overall, this thesis shows that the ICME approach can beused to study and predict precipitation and precipitation-strengthening inmulticomponent steels. The applied approach differs from traditional trial-and-errortesting and has the potential to save time, money and resources in steel development.

Abstract [sv]

Utskiljning är en fasomvandlingsprocess i metalliska material som signifikantpåverkar egenskaperna. Utskiljningsprocessen som inkluderar kärnbildning, tillväxtoch förgrovning av små partiklar kan styras genom legeringstillsats, deformation,värmebehandling, etc. Detta öppnar möjligheter för att optimera metallernasegenskaper genom att kontrollera utskiljningarna. Ett exempel på envärmebehandlingsprocess som leder till utskiljningar är anlöpning av martensitiskastål. Under denna anlöpning kan stålen uppnå mycket god prestanda genom bildningav nanopartiklar i den hierarkiska martensitiska mikrostrukturen. Med målet attpåskynda utvecklingen av dessa högpresterande stål används ICME (IntegratedComputational Materials Engineering) som kombinerar avancerad karakterisering,fysikaliskt baserad modellering, teori och databaser för att relatera värmebehandlingtill utskiljning och slutligen egenskaperna hos stålet.Två högprestanda stål, ett Cu-utskiljningshärdat maråldrings stål och ett Cr/Mo/V-legerat kolstål med karbidutskiljningar, studeras i denna avhandling med hjälp avkvantitativ karakterisering och modellering. Resultaten visar att modelleringen medLSKW (Langer-Schwartz-Kampmann-Wagner) har god överenstämmelse medexperimenten och visar stor potential för prediktiv modellering. De fysikalisktbaserade modellerna för de individuella härdningsmekanismerna som används i dettaarbete kan också representera trenderna för stålens styrka, men det är svårt attprediktera utskiljningshärdningens effekt på styrkan som uppmätts via dragprov.Detta visar på behovet av att vidareutveckla modellerna. Sammantaget visar dennaavhandling att ICME-metodik kan användas för att studera och prediktera utskiljningoch utskiljningshärdning i kommersiella stål. Tillvägagångssättet som använts skiljersig från traditionell “trial-and-error” metodik och kan leda till besparingar av tid,pengar och resurser vid stålutveckling.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2019. , p. 47
Series
TRITA-ITM-AVL ; 2019:41
Keywords [en]
Precipitation; Martensite; Modelling; Thermodynamics; Mechanical Property; Transmission Electron Microscopy; Materials Design
National Category
Metallurgy and Metallic Materials
Research subject
Materials Science and Engineering
Identifiers
URN: urn:nbn:se:kth:diva-263977ISBN: 978-91-7873-381-1 (print)OAI: oai:DiVA.org:kth-263977DiVA, id: diva2:1371536
Public defence
2019-12-12, F3, Lindstedtsvägen 26, Stockholm, 10:00 (English)
Opponent
Supervisors
Available from: 2019-11-20 Created: 2019-11-20 Last updated: 2019-11-20Bibliographically approved
List of papers
1. Quantitative electron microscopy and physically based modelling of Cu precipitation in precipitation-hardening martensitic stainless steel 15-5 PH
Open this publication in new window or tab >>Quantitative electron microscopy and physically based modelling of Cu precipitation in precipitation-hardening martensitic stainless steel 15-5 PH
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2018 (English)In: Materials & design, ISSN 0264-1275, E-ISSN 1873-4197, Vol. 143, p. 141-149Article in journal (Refereed) Published
Abstract [en]

Precipitation-hardening martensitic stainless steels rely on very fine precipitates for optimal mechanical performance. These multicomponent alloys are prone to clustering and precipitation reactions during tempering, where Cu is one of the alloying elements added to stimulate precipitation. It is efficient to use an integrated computational materials engineering (ICME) approach to tailor alloying and heat treatment for design of these alloys. The most promising physically based modelling of precipitation for this purpose at present is Langer-Schwartz-Kampmann-Wagner (LSKW) modelling within the CALPHAD framework. This approach has been successful for model alloys, but reliable results for mulhcomponent stainless steels are less common. Hence, we combine quantitative transmission electron microscopy and LSKW modelling to investigate the tempering of a martensitic stainless steel 15-5 PH at 500 degrees C. The microstructural characterization shows that the Cu precipitation and growth occur in three stages: i) Cu BCC, n) Cu 9R, and iii) Cu FCC, during tempering up to 1000 h. The modelling predictions of size, volume fraction and number density of precipitates are in good agreement with the experimental results. Thus, the approach with a combination of quantitative electron microscopy and LSKW modelling using CALPHAD-type databases holds promise for further optimization of precipitation-hardening martensitic stainless steels.

Place, publisher, year, edition, pages
Elsevier, 2018
Keywords
Precipitation, Materials modelling, Precipitation-hardening stainless steel, Transmission electron microscopy, Tempering of martensite
National Category
Metallurgy and Metallic Materials
Identifiers
urn:nbn:se:kth:diva-224672 (URN)10.1016/j.matdes.2018.01.049 (DOI)000425879300016 ()2-s2.0-85041428510 (Scopus ID)
Funder
VINNOVA
Note

QC 20180323

Available from: 2018-03-23 Created: 2018-03-23 Last updated: 2019-11-20Bibliographically approved
2. Exploring the relationship between the microstructure and strength of fresh and tempered martensite in a maraging stainless steel Fe-15Cr-5Ni
Open this publication in new window or tab >>Exploring the relationship between the microstructure and strength of fresh and tempered martensite in a maraging stainless steel Fe-15Cr-5Ni
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2019 (English)In: Materials Science & Engineering: A, ISSN 0921-5093, E-ISSN 1873-4936, Vol. 745, p. 420-428, article id DELL AJ, 1985, METALLURGICAL TRANSACTIONS A-PHYSICAL METALLURGY AND MATERIALS SCIENCE, V16, P2131Article in journal (Refereed) Published
Abstract [en]

Hierarchical microstructure engineering is an efficient design path for ultra-high strength steels. An excellent example of this is maraging stainless steel, which achieves its high-performance by combining the hierarchic martensitic microstructure and nano-sized precipitates. Relating this complex microstructure with mechanical properties, e.g. strength, is not trivial. In the present work, we therefore explore the relationship between the hierarchic microstructure, evolving with the tempering of a Cu-containing maraging stainless steel 15-5 PH, and its strength. Comprehensive microstructure characterization, including the quantification of dislocation density, effective grain size, precipitates and retained austenite fraction is performed after quenching and tempering at 500 degrees C. The microstructure data is subsequently used as input for assessing the evolution of individual strength contributions and thus the increase in strength of tempered martensite contributed by Cu precipitation strengthening is evaluated. It is found that the Cu precipitation and dislocation annihilation are two major factors controlling the evolution of the yield strength of the tempered martensite. The Cu precipitation strengthening is also modelled using our previous Langer-Schwartz-Kampmann-Wagner model based predictions of the Cu precipitation, and modelled precipitation strengthening is compared with the evaluated Cu precipitation strengthening from the experiments. The work exemplifies the promising approach of combining physically based precipitation modelling and precipitation-strengthening modelling for alloy design and optimization. However, more work is needed to develop a generic predictive framework.

Place, publisher, year, edition, pages
ELSEVIER SCIENCE SA, 2019
Keywords
Mechanical properties, Modelling, Maraging stainless steel, Cu precipitation strengthening, Martensite
National Category
Metallurgy and Metallic Materials
Identifiers
urn:nbn:se:kth:diva-244522 (URN)10.1016/j.msea.2018.12.126 (DOI)000457819400045 ()2-s2.0-85059590155 (Scopus ID)
Note

QC 20190403

Available from: 2019-04-03 Created: 2019-04-03 Last updated: 2019-11-20Bibliographically approved

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