[PPT] - Strengthening Mechanisms and Their Relative Contributions to the PowerPoint Presentation

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Strengthening Mechanisms and Their Relative Contributions to the Yield Strength of Microalloyed Steels

Junfang Lu 1, Oladipo Omotoso 2,

J. Barry Wiskel 3, Douglas G. Ivey 3 & Hani Henein 3

1 Enbridge Pipelines Inc., Edmonton, Alberta 2 Suncor Energy Centre, Calgary, Alberta 3 Dept. Chemical/Materials Engineering, University of Alberta, Edmonton, Alberta

July 10, 2013

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SLIDE 2

http://geology.com/world/canada-satellite-image.shtml http://centennial.eas.ualberta.ca

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University of Alberta Facts

105 years old
~39,000 students
80% undergraduate students
20% graduate students
~3,200 academic staff
$1.7B Cdn Budget
$0.46M Cdn Research

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Outline

I. Introduction II. Objectives III. Experimental Methods IV. Tests and Results

Grain size measurement
Precipitate size, morphology and chemistry
ICP analysis of the supernatant
Rietveld refinement of XRD data
Effect of microalloying content, CT/ICT on the amount of nano-sized

precipitates

Strengthening contributions

V. Conclusions VI. Acknowledgements

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SLIDE 4

Thermomechanical controlled processing - to control microstructure evolution

Temperature, ºC Time

1400 1000 800 600 400 200 Accelerated Cooling Recrystallized Austenite

Tnr

Pancaked Austenite

Ar3

PF P BF (or AF) Ms PF – Polygonal Ferrite P – Pearlite BF – Bainitic Ferrite AF – Acicular Ferrite Finish Rolling Reheating Rough Rolling Coiling

A schematic CCT diagram for microalloyed linepipe steels (Ref: D. Qi, Patent)

Grain size effect
Solid solution strengthening
Precipitation strengthening

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SLIDE 5

Objectives

To understand the strengthening mechanisms of microalloyed steels I. To determine strengthening contribution due to grain size effect II. To determine strengthening contribution due to precipitation effect

To characterize precipitate size, morphology and chemistry
To quantify the amount of nano-sized precipitates
To understand the nano-sized precipitation as a function of steel

chemistry and processing histories

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SLIDE 6

Challenges associated with precipitate characterization

Fine sizes of precipitates
Wide particle size distribution
Low volume fraction
Precipitates have same crystal structure (NaCl-type), with

similar lattice parameters

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SLIDE 7

FRT* = normalized finish rolling temperature to that of X80-B4F steel CT/ICT* = normalized coiling/interrupted cooling temperature to that of X80-B4F steel ** = intended values For Grade 100 and X100 steels, steels were deformed by leveling or rolling at ICT temperature X100 steels are experimental, pilot scale steels

Chemical compositions & processing histories

Steel C (wt%) N (wt%) Si (wt%) Nb (wt%) Ti (wt%) Mo (wt%) V (wt%) FRT* CT/ICT* CR (ºC/s) X70-564 0.0398 0.0118 0.23 0.069 0.023 0.2 0.001 0.94 1.04 15** X80-A4B 0.035 0.0058 0.283 0.094 0.017 0.305 0.003 1.05 0.93 15** X80-B4F 0.052 0.0061 0.128 0.077 0.009 0.299 0.002 1.00 1.00 15** X80-462 0.03 0.0098 0.27 0.091 0.013 0.297 0.002 0.94 1.04 15** X80-A4F 0.052 0.0055 0.115 0.044 0.009 0.404 0.003 1.00 0.90 15** Grade 100 0.08 0.011 0.244 0.094 0.06 0.301 0.047 1.07 1.09 15** X100-2A 0.039 0.005 0.11 0.037 0.013 0.41 0.003 1.00** 0.71 35 X100-2B 0.065 0.0059 0.22 0.047 0.009 0.4 0.07 1.00** 0.64 34 X100-3C 0.064 0.0063 0.33 0.05 0.009 0.4 0.003 1.00** 0.80 19.1

Steel chemistry and normalized FRT and CT/ICT

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Experimental methods – combination of different techniques

Carbon replicas SEM/TEM Size; morphology; chemistry Steel Dissolve sample in solution Centrifuge, remove portion of liquid Centrifuge again Dilute solution Residues ICP analysis SEM/TEM XRD Mass balance

Solution Relative amounts of crystallographic phases

Rietveld refinement Steel SEM Grain size Precipitate Matrix dissolution Carbon replicas Steel TEM Precipitate distribution in matrix Thin foils Steel

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SLIDE 9

X70-564 X80- 462 Grade 100 X100- 3C

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SLIDE 10

Hall-Petch equation

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SLIDE 11

Grade 100 – thin foil

{111} {200} {220}

BF-TEM DF-TEM

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SLIDE 12

Grade 100 – carbon replica

{200} {111} {220}

Grade 100 100 200 300 2 4 6 8 10 12 14 16 18 20

Energy (keV) Intensity

C O Cu Nb Ti Fe Cu Cu Nb Nb Mo Mo Ti V

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SLIDE 13

Grade 100 – matrix dissolution

{111} {200} {220}

Matrix dissolution using HCl Matrix dissolution using 10% AA

(10% acetylacetone + 1% TMAC (tetramethylammonium chloride) + methanol)

Nb/Mo- rich

50 100 150 200 250 300 350 2 4 6 8 10 12 14 16 18 20 Energy (keV) Intensity Si Nb Ti Fe Cu Cu Nb Nb Kb1 Ca Mo Mo Fe V Ti Mo

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SLIDE 14

X100-3C – carbon replica

100 nm 20 nm

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SLIDE 15

Wt% of Nb - based on steel chemistry and ICP analysis

0.00 0.02 0.04 0.06 0.08 0.10 0.12

X70-564 X80-462 X80-A4B X80-B4F X80-A4F Grade100 X100-2A X100-2B X100-3C

wt% of Nb Steel

Nb amount in solid solution Nb amount in precipitate 15/29

SLIDE 16

Wt% of Mo - based on steel chemistry and ICP analysis

0.00 0.10 0.20 0.30 0.40 0.50

X70-564 X80-462 X80-A4B X80-B4F X80-A4F Grade100 X100-2A X100-2B X100-3C

wt% of Mo Steel

Mo amount in solid solution Mo amount in precipitate 16/29

SLIDE 17

Ti, Nb and V carbides, nitrides or carbonitrides have NaCl-type, fcc structure
Lattice parameters are similar, making it difficult to identify specific precipitates

XRD analysis of residues (preliminary analysis)

2000 4000 6000 8000 20 40 60 80 100 120

2θ Intensity (Counts)

Grade 100 X70-564 X80-462 X80-B4F

NbC-rich TiN-rich (111) (111) (200) (200) (220) (220) (311) (311) (400)

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SLIDE 18

yi: observed (and calculated) intensities at each step wi: weighting factor for each observation wa: relative weight fraction of phase a in a mixture of j phases SF: refined scale factor, which is proportional to the number of unit cells of phase a in the specimen M: mass of the molecular formula Z: number of formula units per unit cell V: volume of the unit cell

Rietveld refinement: Least squares profile fitting (minimization procedure)

To minimise a function S which represents the difference between y(calc) and y(obs)
Full pattern profile refinement
Simultaneous crystal structure refinement
Quantitative phase analysis

Rietveld refinement of XRD pattern

Minimum calc y

bs

y w S

i i i i

  

2

)) ( ) ( (





j j j a a a

MZV SF MZV SF w ) ( ) (

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SLIDE 19

90 85 80 75 70 65 60 55 50 45 40 35 9,000 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000

1,000

90 85 80 75 70 65 60 55 50 45 40 35 9,000 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000

1,000

Overall XRD pattern profile fitting

Rietveld refinement of XRD data (Grade 100)

90 85 80 75 70 65 60 55 50 45 40 35 9,000 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000

1,000
2,000

90 85 80 75 70 65 60 55 50 45 40 35 9,000 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000

1,000
2,000

Ti0.9Nb0.1N

90 85 80 75 70 65 60 55 50 45 40 35 9,000 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000

1,000
2,000

90 85 80 75 70 65 60 55 50 45 40 35 9,000 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000

1,000
2,000

90 85 80 75 70 65 60 55 50 45 40 35 9,000 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000

1,000
2,000

90 85 80 75 70 65 60 55 50 45 40 35 9,000 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000

1,000
2,000

Ti0.5Nb0.5C0.5N0.5 Nb0.7Ti0.3C0.5N0.5

90 85 80 75 70 65 60 55 50 45 40 35 9,000 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000

1,000
2,000

90 85 80 75 70 65 60 55 50 45 40 35 9,000 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000

1,000
2,000

Nb0.48Mo0.28Ti0.21V0.03C

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SLIDE 20

Precipitate information

Steel Precipitate chemistry Precipitate size (nm) X70-564 Nb0.52Ti0.43Mo0.05C0.5N0.5 Nb0.79Ti0.15Mo0.06C0.5N0.5 Nb0.58Mo0.42C 20-40 20-40 5 X80-A4B Ti0.52Ti0.48C0.5N0.5 Nb0.9Ti0.1C0.5N0.5 Nb0.68Mo0.32C 60-80 25-70 5 X80-B4F Ti0.72Nb0.28N Nb0.57Ti0.43C0.5N0.5 Nb0.92Ti0.08C0.5N0.5 Nb0.78Mo0.22C 80-100 85-135 40-100 4.5 X80-A4F Ti0.76Nb0.24N Ti0.51Nb0.49C0.5N0.5 Nb0.86Ti0.14C0.5N0.5 Nb0.74Mo0.26C 100-200 20-30 20-30 4 X80-462 Ti0.76Nb0.24N Ti0.55Nb0.45C0.5N0.5 Nb0.86Ti0.14C0.5N0.5 Nb0.8Mo0.2C 100-200 80-100 40-90 5

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SLIDE 21

Precipitate size and chemistry

Phases NbN NbC TiN TiC MoC VN VC Lattice parameter (nm) 0.43927 0.44698 0.42417 0.43274 0.428 0.41392 0.41820

Steel Precipitate chemistry Precipitate size (nm) Grade 100 Ti0.9Nb0.1N Ti0.77Nb0.23C0.5N0.5 Ti0.5Nb0.5C0.5N0.5 Nb0.7Ti0.3C0.5N0.5 Nb0.48Mo0.28Ti0.21V0.03C 500-3000 100-500 100-200 100-200 4.5 X100-2A Ti0.70Nb0.26Mo0.04C0.5N0.5 Ti0.54Nb0.41Mo0.05C0.5N0.5 30 20 X100-2B Ti0.66Nb0.29V0.05C0.5N0.5 Nb0.53Ti0.42V0.05C0.5N0.5 Nb0.85Ti0.13V0.02C 80 60 40 X100-3C Ti0.5Nb0.47Mo0.03C0.5N0.5 Nb0.67Ti0.3Mo0.03C0.5N0.5 40 20

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SLIDE 22

Effect of microalloying content on vol% of nano-precipitates

0.00% 0.05% 0.10% 0.15% 0.20% 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.1

Vol% of nano-precipitates in steel wt% of Nb in steel

X80-B4F X80-A4B X80-462 Grade100 X70-564 X80-A4F X100 22/29

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Effect of CT/ICT on vol% of nano-precipitates

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Superposition of strengthening mechanisms

2. Root mean square summation (Pythagorean superposition)

2 2 2 2 ppt ss gb i

        

3. Combination of linear and root mean square summation

ss i ppt gb

        

2 2

Linear superposition can be assumed to be valid

Structural scales are very different: σi (scale of atomic distances) and σgb (micron scale) Strengthening mechanisms are different: σss and σgb

Solute concentration is relatively low for microalloyed steels, does not change σppt mechanism
Strong synergism between grain boundary and particle hardening
1. Linear summation (overestimate σy because of synergy effect)

                     

 



4 2 / 1 2 / 1

10 * 125 . 6 ln 8 . 10 ) ( X X f C k d k MPa

i i y i ppt ss gb i y

     

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Comparison with yield strength of steels

300 400 500 600 700 800 900 300 400 500 600 700 800 900

Strength superposition (MPa) Yield strength - experimental (MPa)

Experimental yield strength Linear summation Combination of root mean square and linear summation Linear (Experimental yield strength)

X70 X80 X100-2B X100-3C Grade100 X100-2A 25/29

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Individual strengthening component – combination of root

mean square and linear summation

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% X70-564 X80-462 X80-A4B X80-B4F X80-A4F Grade100 X100-2A X100-2B X100-3C

Individual strengthening component Steel

σi Solid solution strengthening Precipitation strengthening Grain size strengthening 26/29

SLIDE 27

Conclusions

I. Grain size decreased with increasing grades of steels; behaviour followed Hall-Petch relationship – higher cooling rates and lower CT/ICT promoted grain refinement II. Matrix dissolution methods were effective in extracting sufficient amounts of precipitates for quantitative analysis III. Rietveld refinement of XRD data, combined with electron microscopy, was successfully used to identify and determine relative amounts of different precipitate phases IV. X70, X80 and Grade 100 steels had similar processing histories - higher microalloying content increased precipitation, leading to higher volume fractions and number densities of nano-precipitates

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SLIDE 28

Conclusions

V. For X100 steels, no nano-precipitates (≤5nm) were found - lack of fine precipitates was due to the low ICT temperature VI. Nb/Mo rich nano-precipitates (<5 nm) and solid solution strengthening were quantified in X70, X80 and Grade 100 steels and contributed significantly to the yield strength (about 40 to 50%)

VII. For all steels, grain refinement was a major contributor to

strengthening

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SLIDE 29

Acknowledgements

EVRAZ Inc. NA
Natural Sciences and Engineering Research Council (NSERC) of

Canada

Companhia Brasiliera de Metalurgia e Mineração (CBMM)
Beta Technology
Institute of Materials, Minerals and Mining (IOM3)
Naila Croft, Ben Micó and Geórgia Gomes Bemfica

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