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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http://centennial.eas.ualberta.ca 2/29

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

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

3/29

Thermomechanical controlled processing - to control microstructure evolution Te

mp

era

ture

, º

C

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

4/29

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

5/29

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

6/29

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

7/29

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

8/29

X70-564 X80- 462

Grade 100 X100- 3C 9/29

Hall-Petch equation

10/29

Grade 100 – thin foil

{111}

{200}

{220}

BF-TEM DF-TEM

11/29

Grade 100 – carbon replica

{200}

{111} {220}

Grade 100

0

100

200

300

0 2 4 6 8 10 12 14 16 18 20

Energy (keV)

Inte

nsi

ty

C

O

Cu

Nb

Ti

Fe

Cu

Cu Nb

Nb Mo

Mo

Ti V

12/29

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

0

50

100

150

200

250

300

350

0 2 4 6 8 10 12 14 16 18 20

Energy (keV)

Inte

nsi

ty

Si

Nb

Ti

Fe

Cu

Cu

Nb

Nb

Kb1

Ca

Mo

Mo Fe V

Ti

Mo

13/29

X100-3C – carbon replica

100 nm

20 nm 14/29

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

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

• 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)

0

2000

4000

6000

8000

20 40 60 80 100 120

2θ

Inte

nsit

y (

Co

un

ts)

Grade 100

X70-564

X80-462

X80-B4F

NbC-rich

TiN-rich

(111)

(111)

(200)

(200) (220)

(220) (311)

(311) (400)

17/29

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

MinimumcalcyobsywS ii

i

i 2))()((

j

jj

aaa

MZVSF

MZVSFw

)(

)(

18/29

908580757065605550454035

9,000

8,000

7,000

6,000

5,000

4,000

3,000

2,000

1,000

0

-1,000

908580757065605550454035

9,000

8,000

7,000

6,000

5,000

4,000

3,000

2,000

1,000

0

-1,000

Overall XRD pattern profile fitting

Rietveld refinement of XRD data (Grade 100)

908580757065605550454035

9,000

8,000

7,000

6,000

5,000

4,000

3,000

2,000

1,000

0

-1,000

-2,000

908580757065605550454035

9,000

8,000

7,000

6,000

5,000

4,000

3,000

2,000

1,000

0

-1,000

-2,000

Ti0.9Nb0.1N

908580757065605550454035

9,000

8,000

7,000

6,000

5,000

4,000

3,000

2,000

1,000

0

-1,000

-2,000

908580757065605550454035

9,000

8,000

7,000

6,000

5,000

4,000

3,000

2,000

1,000

0

-1,000

-2,000

908580757065605550454035

9,000

8,000

7,000

6,000

5,000

4,000

3,000

2,000

1,000

0

-1,000

-2,000

908580757065605550454035

9,000

8,000

7,000

6,000

5,000

4,000

3,000

2,000

1,000

0

-1,000

-2,000

Ti0.5Nb0.5C0.5N0.5

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

908580757065605550454035

9,000

8,000

7,000

6,000

5,000

4,000

3,000

2,000

1,000

0

-1,000

-2,000

908580757065605550454035

9,000

8,000

7,000

6,000

5,000

4,000

3,000

2,000

1,000

0

-1,000

-2,000

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

19/29

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 20/29

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

21/29

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

Vo

l% o

f n

an

o-p

recip

itate

s i

n s

teel

wt% of Nb in steel

X80-B4F

X80-A4B

X80-462

Grade100

X70-564

X80-A4F

X100

22/29

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

23/29

Superposition of strengthening mechanisms

2. Root mean square summation (Pythagorean superposition)

2222

pptssgbi

3. Combination of linear and root mean square summation

ssipptgb 22

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

2/12/1

10*125.6ln

8.10)(

X

X

fCkdkMPa iiyipptssgbiy

24/29

Comparison with yield strength of steels

300

400

500

600

700

800

900

300 400 500 600 700 800 900

Str

en

gth

su

perp

osit

ion

(M

Pa)

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

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

Ind

ivid

ual

str

en

gth

en

ing

co

mp

on

en

t

Steel

σi Solid solution strengthening Precipitation strengthening Grain size strengthening26/29

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

27/29

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

28/29

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

29/29