1

A Synchrotron Tomographic Energy Dispersive Diffraction Imaging (TEDDI) study of

the aerospace alloy Ti 6246.

R J Cernik, C C T Hansson, C M Martin, M Preuss and M Attallah,

School of Materials, University of Manchester, Grosvenor St, M1 7HS

A M Korsunsky J P Belnoue and T S Jun

Department of Engineering, University of Oxford

P Barnes, S Jacques T Sochi and O Lazzari

Department of Chemistry, University College London, Gower Street.

ABSTRACT

A Titanium alloy sample (# 6246) containing a linear friction weld (LFW) has been imaged

non-destructively using Tomographic Energy Dispersive Diffraction Imaging (TEDDI). The

diffraction patterns measured at each point of the TEDDI image were able to identify the

material and phases present (5%). The image also showed the preferred orientation (PO) and

size-strain distribution present within the sample without the need for any further sample

preparation. The preferred orientation was observed in clusters with average dimensions very

similar to that of experimental spatial resolution (400 µm). The length scales and PO

distributions were consistent with Orientating Imaging Microscopy (OIM) measurements made

by Szczepanski et al. (2008) where the microstructure development was linked to the grain

growth of the parent material. The use of a high energy X-ray distribution (30-80 keV) in the

incident beam reduced systematic errors due to the source profile, sample and air absorption.

The TEDDI data from each voxel were reduced to an angle dispersive form and Rietveld

refined to a mean 2

of 1.4. The mean lattice parameter error (d/d) ranged from ~10-4

for the

highly crystalline regions to ~10-3

for regions of very strong PO and internal strain. The March-

Dollase PO errors refined to an average value of 2%. A 100% correlation between observed

fluorescence and diffraction peak broadening was observed providing further evidence for

vicinal strain broadening.

2

INTRODUCTION

Advanced Titanium alloys are widely used in the aerospace industry and are often selected for

aero engine components (Esslinger et al., 2003). Because these complex fabricated components

have to operate in a ‘fail safe’ environment there is a large and rapidly growing demand for

new, non-destructive, characterisation techniques to determine the microstructure-property

relations in these alloys. A great deal of effort is also expended studying phase transformations

during processing to optimise the metallic microstructures that possess suitable properties for

these high performance applications. High-energy synchrotron X-ray diffraction (Malinov et

al. 2002, Elmer et al. 2005, Bruneseaux et al. 2008), electrical resistivity (Malinov et al.,

2001, 2003, Bein and Bechet 1996, Teixeira et al. 2007 and Tarin et al. 2006a), differential

thermal analysis (Tarin et al. 2006b, dilatometry and calorimetry), and electron backscattered

diffraction (EBSD) (Bhattacharyya et al. 2003, Stanford and Bate 2004, Lee et al. 2007,

Venkatramani et al. 2007), have been used to study the phase transformations and the

associated microstructural development in Ti-alloys together, in some cases, with

thermodynamic calculations. This combined approach has proved successful in providing close

corroboration between theory and experiment and has directly helped to improve the material’s

performance. However the majority of the analytical techniques described above require

intensive sample preparation so it is highly desirable to develop an analytical technique that

can be used to study the ‘as manufactured’ object, complete with any residual stresses;

dislocations; faults or micro cracks that might have arisen during manufacture. There have

been a number of new and very promising non-destructive imaging methods published recently

which can deliver a three dimensional image combined with structural information. For

example the work of Marguilies et al (2001) utilises a small letter box shaped monochromatic

(50 keV) to illuminate a polycrystalline sample. The grains in the diffracting position produce

X-ray reflections on an area detector. The position of the reflections can be followed as a

3

function of applied stress and by scanning the sample through the beam an image of the whole

sample’s response to deformation can be mapped. Alternatively the approach of Larson et al

(2002) uses a polychromatic beam to produce many Laue reflections from the polycrystalline

sample. These patterns are separated out by a moving wire differential aperture that occludes

part of the diffracted beam allowing the deconvolution of individual reflections. Also Johnson

et al (2007) have been developing the idea of diffraction contrast tomography where the

intensity from a single reflection is diffracted out of the straight though beam. This information

is used in a large number of sections which can then be back projected to form a 3D image of

each grain. These studies have the advantage of high spatial resolution with implicit structural

information but are difficult to scale up and are relatively time consuming.

In this study we have applied the relatively new, non destructive, Tomographic Energy

Dispersive Diffraction Imaging (TEDDI, Hall et al., Harding et al. 1999, Tunna et al,. 2006,

Barnes et al. 2000, Cernik et al. 2008) to produce a three dimensional structural image of a

linear friction welded titanium alloy containing details of composition, size-strain and preferred

orientation. The TEDDI method is ideally suited to rapid studies of large samples but at lower

spatial resolution than the imaging techniques descried earlier. Previous trials (Middelkoop et

al. 2009, Cernik et al. 2007, Beale et al. 2007) on reactions within thick walled stainless steel

vessels, catalysis beds and industrial ceramics have shown structural properties and processing

details that could not have been revealed by standard X-ray imaging methods. TEDDI has

delivered in-situ images of complex systems but it is optimal to have a homogeneous

polycrystalline sample especially within the sampling, or gauge volume. This can often be a

problem with metallic samples where large grain sizes can lead to poor statistical averaging

and sometimes insurmountable preferred orientation problems. We have, to a certain extent,

overcome these problems by using a larger sampling volume than in previous studies. This has

4

reduced the spatial resolution that TEDDI is capable of delivering but has given acceptable

counting statistics in each voxel.

In the current paper we have chosen to study Ti6246 which is an alloy commonly encountered

in aerospace applications. It contains two crystallographic phases [, hexa body-

centred cubic] and has the composition Ti-6Al-2Sn-4Zr-6Mo where the numbers refer to the

wt% of each element with the remainder of the alloy composed of titanium. Recently, new

alloys with greater β-phase volume fraction (e.g. Ti-6246) than the workhorse Ti-alloy Ti-64

have been introduced in aero-engine components, due to their improved creep strength, heat-

treatment response, and relatively higher operating temperatures. Our understanding of the

microstructure property relationship in Ti-alloys is generally focused on the morphology and

crystallographic texture of the phase. However, with alloys such as Ti-6246, it has become

necessary to also provide an improved understanding of the role of the phase and how

deformation affects both phases. In addition, microstructural gradients as observed in welds

need to be characterised in order to identify possible issues of such regions.

In the present work, we have used TEDDI to non-destructively evaluate the distribution of

crystallographic lattice parameters; cell volumes; compositions, preferred orientation and phase

fractions through a Ti-6246 sample containing an LFW. As demonstrated previously (Attallah

et al. 2009), Ti-LFWs display a microstructural gradient across the weld line accompanied with

a steep residual stress profile. Another aim of this paper was to correlate the results from the

TEDDI analysis with the microstructural information obtained from EBSD studies on the same

material in order to determine its usefulness for imaging microstructural properties in advanced

lightweight metallic titanium alloys containing linear friction welds.

5

EXPERIMENTAL METHODS

Material

The titanium alloy used for this study was received in the form of a machined block, with a

nominal composition of Ti-6Al-2Sn-4Zr-6Mo, and oxygen content between 700-1200 ppm.

This alloy is normally forged in the β phase at 1213 ±15 K, followed by annealing at the α + β

phase field between 1175-1195 K for 1-2 hrs, and then aging at approximately~868 K for 8 hrs.

This treatment is aimed at creating a microstructure with coarse (primary) and fine (secondary)

α, further details on the β-forged processing route of this alloy can be found elsewhere

(Lutjering et al. 2007). This mixed phase microstructure provides the best compromise in

terms of good fatigue properties including crack propagation rates and strength.

TEDDI geometry

In order to image the microstructural variations within the Ti-6Al-2Sn-4Zr-6Mo alloy a

TEDDI system was constructed on station I15 of the DIAMOND light source, Chilton, Dicot,

UK. I15 is served by a mutipole wiggler with a peak design field of 3.5T although the

maximum field during this experiment was 1T which limited the higher energy X-ray output.

The insertion device has 24 poles with a period of 60mm and a maximum K value of 19.6

which delivers a white beam to the sample whose intensity varies as a function of energy

shown in figure 1. The energies that are of practical use for TEDDI depend on the sample size

and density. For our titanium alloy sample with dimensions of 1.8cm x 1.3cm x 2mm the

energy of the diffracted beams in transmission vary from approximately 30 keV up to 80 keV.

This useful energy range is shown in figure 1 where the incident intensity can be seen to vary

smoothly over one order of magnitude.

The intersection of the incident and diffracted beams necessary for the TEDDI geometry was

engineered by using an incident beam 200 x 200 µm (produced by closing up the incident

6

white beam slits) in association with a long thin diffracted beam collimator that defined the

required angular aperture of 0.04 to give the required energy resolution. This system defines a

single gauge volume so the three dimensionality of the final image has to be achieved by

scanning the sample in x, y and z. Finer spatial resolution scans are possible but are limited by

the practical count rate and the accumulation of a statistically significant or refineable

diffraction pattern. In practice this lower limit is of the order of 20 µm but the data collection

time rises in proportion to the number of steps. A promising, much faster, alternative approach

has been tested using pixellated detectors and multiple collimators (Cernik et al 2008) but this

is not yet suitable for applications where diffracted beams exceed 30 keV because of the lack

of availability of high quality heavy semiconductor detectors.

We constructed a tubular diffracted beam collimator housing 75 cm in length with a matching

pair of centre opening slits at either end. Given the relatively high energy range of the

diffracted beams there was no necessity to evacuate the tube to reduce air absorption. The slits

could be adjusted to give a variable aperture between 0.01 and 0.08. This angular aperture

was optimised to maximise the diffracted beam flux whilst preserving the energy resolution of

the single element cadmium zinc telluride detector supplied by Amtek Ltd quoted as 750 eV at

5.9 keV.

The sample was mounted on an x, y z translation stage with the largest face of the sample held

normal to the incident beam direction as shown in figure 2. The diffracted beam collimator was

placed at and angle of 7 (2θ) to the incident beam and was held constant for the duration of

the experiment. The time spent collecting data at each point was 10 seconds giving an overall

time for data collection of 13 hours per slice including a rather slow motor drive time. The

stage was moved in 400 µm increments in x, y and z. This spatial resolution is larger than that

used in previous TEDDI experiments but was found to give good counting statistics at each

7

voxel, even when large beta grains were diffracting. This lower resolution also allowed a full

section to be scanned in the time available. An energy dispersive diffraction pattern was

measured from each gauge volume defined by the intersection if the incident and diffracted

beams as the sample was scanned though the incident beam. Figure 2 shows the experimental

geometry in elevation view (top left) and in perspective below. The sample had been mounted

in Bakelite for preparation purposes; this was still clearly visible especially in the regions

surrounding the weld flash. The TEDDI image of the sample can be seen on the right hand side

of the optical micrograph.

Data processing

The colours on the TEDDI map represent the total count rate registered on the single element

CZT detector, although any other parameter returned from data analysis can be chosen for

display. The visualisation was produced by the Easy EDD program written by one of the

authors. The program has the capability to store and visualise a wide range of structural

parameters. In this case the total count rate integrated across all X-ray energies is being

displayed false coloured on a rainbow scale with red at the high count end. This display

method does not always provide the most insightful way of interpreting the scattering but is a

useful in determining the overall sample shape.

The energy dispersive diffraction data were used to refine a structural model using the TOPAS

Rietveld refinement program (Bruker AXS 2003). The data were transformed from the energy

dispersive form to an angle dispersive form by calibrating the energy of the observed peaks

with a radioactive source with a variable energy. The values of the d spacings for the observed

reflections were therefore known. A nominal wavelength of 1Å was used to reconstruct the

angle dispersive form which was easier to handle with the version of the program then

available to us. Known values for the crystal structures of the and phases were used as the

8

starting models Hull, 1921, Burgers and Jacobs 1936). The errors often associated with

Rietveld refinement of energy dispersive diffraction data such as sample absorption edges, air

pathways and detector responses were all minimised by the high energies of the diffracted

beams.

RESULTS

The full TEDDI image is shown again in figure 3 at a higher magnification. Each voxel

depicted is 400 µm by 400 µm. Several features are visible. There is a region of higher count

rate (dark red) along the weld line although there are other clearly observable high count

regions distributed apparently randomly across the slice. The raw count rate before processing

was therefore not very useful in interpreting crystallographic features. However the sample

shape is faithfully represented in the image the including Bakelite regions used for supporting

the sample, the Bakelite appears light yellow on the TEDDI image. We observed a mean

spatial grouping of the order of the voxel size between regions of strong and weaker scattering

on the TEDDI map. A very similar spatial variation was noticed with regard to areas with

different reflectivity on the optical micrograph. A closer inspection of the energy dispersive

diffraction patterns contained in each voxel shows three characteristic types (shown in figure

3). Figure 3(a) shows the diffraction pattern measured from the voxel indicated by the arrow.

This pattern contains eight fluorescence peaks up to a reconstructed angle of 20 2θ followed

by a series of strong narrow peaks corresponding to the and phases of Ti6246; the

fluorescence peaks are common to all spectra. The diffraction and fluorescence peaks are

narrow in contrast with those shown in figure 3(c), here a cluster of broad intense peaks are

observed. This spectral pattern is typical of those measured close to the weld region but are not

exclusively observed here. Figure 3(b) shows the diffraction pattern characteristic of Bakelite

which was used to support the sample during processing.

9

The energy dispersive diffraction patterns from every voxel were refined using the known

starting structures for the and phases of titanium. Neither the range nor the statistical

quality of the energy dispersive diffraction data were sufficient to refine atomic coordinates or

microstructural properties but the cell parameters, preferred orientation directions and trends in

particle size-strain as measured by peak widths could be determined in all cases. Figure 4

shows a selection of five diffraction patterns from separate voxels on the two lines 20 and 24

(shown in figure 3). The diffraction patterns were selected in the region close to the weld line

(indicated by the brackets in figure 3). In all cases both the and phases were present. This

was because the sampling gauge volume was larger than any contiguous structural regional

variation within the sample.

The variations in all the spectra labelled a,b,d or e are primarily due to preferred orientation

variations within the sample. This was modelled in each case with a very simple March-

Dollase function (Dollase 1986). The appearance of the diffraction pattern around the weld

(20c and 24c) line was different to that of the bulk being characterised by a very broad feature

that encompassed the (0 1 0), (0 0 2), (0 1 1) and (0 1 1) reflections. The results from the

Rietveld refinement of the data from the voxels shown in figure 4 are presented in tables 1 (for

line 20) and table 2 (for line 24). We observed non-systematic variations in lattice parameter

and volume of both phases across the sample; this was thought to be due, primarily, to the large

sampling volume and the real complex microstructure of the sample. The goodness of fit was

acceptable in all cases. With the exception of voxels in the vicinity of the weld line the ratio of

to was 25(2)%:75(2)% which is consistent with previous studies. The broad diffraction

features were not observed solely around the weld line. Nearly identical patterns were observed

in isolated regions within the bulk of the sample. These high count rate regions coincided in all

cases with a broadening of the fluorescence features discussed earlier. This is shown in more

detail in figure 5(a) where the Rietveld refinements from two voxels are overlaid. In one case

10

the peaks are very broad; in the other the peaks are relatively sharp. Lower down on the 2θ axis

from 8-20 eight fluorescence peaks can be observed. The energies of these peaks were

determined from an energy calibration of the detector using a variable energy radioactive

source. These are shown in more detail in figure 5(b) and correspond to (in ascending

energy/2) Pb L ; Zr K; Mo K and Zr K; Mo K; two Cd escape peaks and the K and

of Sn. All these elements are present in the sample with the exception of lead which forms part

of the shielding. The variation of the fluorescence peaks from three voxels is shown in figure

5(c), in each case the increase in the fluorescence line with is matched by an increase in the

diffraction width. The fluorescence peaks in Figure 5(c) were all taken from line 24 on figure

3, with line 1 being measured directly on the weld line; line 2 measured two voxels down and

line 3 being measured two voxels up from the weld line. The increased width of the

fluorescence lines were seen to be 100% correlated with increases in the width of the

diffraction peaks, not just for these three voxels but everywhere in the sample. It is well known

in the high pressure community that increasing pressure causes the ruby fluorescence

calibration lines to broaden, therefore increases in florescence line widths can correspond to

changes in internal stress. An attempt to quantify this was undertaken by Ma and Clarke (1993)

where a methodology was developed to determine internal stresses from optical fluorescence

lines using the theoretical development of piezo-spectroscopic coefficients. Our fluorescence

data are not of sufficient quality to undertake quantitative analysis but from a qualitative view

the fluorescence line broadening is a sensitive indication of the presence of internal stress

within the illuminated voxel indicating that there are vicinal regions where large internal strain

gradients are present not just at the LFW.

Figure 6 shows the Rietveld refined output from a typical voxel. The experimental points are

shown as circles. The total calculated fit is shown in red, the individual calculated components

from the and phases are shown in black and blue respectively and the individual peaks

11

have been indexed. The precision of the lattice parameters extracted from these data were d/d

~ 10-4

for and phases that did not show significant peak broadening. Where peak

broadening was observed (e.g. figure 4c line 20 or 24) the figure for d/d was closer to 10-3

.

This is shown in tables 1 and 2 for 5 voxel in and around the weld line one the two vertical

lines labelled 20 and 24 in figure 3. The average figure for goodness of fit (2) was 1.4

indicating that the structural model was an acceptable fit to the observed data in all cases. The

most significant structural parameter relating to the different appearance of the voxel to voxel

spectra was the preferred orientation parameter.

After refinement of the energy dispersive spectra any of the refined parameters can be selected

in Easy EDD for display. Figure 7 shows a preferred orientation map of the 110 phase

reflection across the sample. The false coloration refers to the intensity of the 110 peak. Blue or

black indicates the near absence of the peak due to preferred orientation, red colouration

indicated strong preferred orientation enhancement. Similar maps can be obtained for other

reflections. It can be seen that there is almost perfect alignment of this crystallographic

direction in the weld region. It is also clear that there are other regions in the material where

the preferred orientation direction is almost opposite to that in the weld region. These

variations are gain on the spatial scale of 1 or two voxel dimensions.

Conclusions

We have demonstrated that the TEDDI image faithfully reproduces the original shape of the

sample whilst giving structural information derived from the energy dispersive diffraction

pattern recorded at each voxel. The use of high energy X-rays on beamline I15 with a practical

minimum of circa 30 keV gives some advantages in the interpretation of the diffracted features.

This is because the limitations of energy dispersive diffraction for structural studies primarily

stem from a non uniform X-ray source profile and nonlinear absorption in the sample. Varying

12

lengths of flight paths can also create intensity measurement difficulties. These problems are

minimised when working at higher energies as the source profile is quite linear from 30 to 80

keV (see figure 1). There are no sample absorption edges within this range and air absorption

of the diffracted beams is minimal. The implication is that any features that vary from peak to

peak within the spectra from a particular voxel are due to genuine structural variations and the

accuracy with which the preferred orientation parameters can be determined is statistically

significant. For example in the voxel labelled 31802 in table 1 the March-Dollase parameters

for the [0 1 0] and [0 1 2] reflections were 0.14(6) and 0.339(8) respectively representing an

average error between 2 and 4 %. These uncertainties were seen to be typical of the whole slice

with the exception of the highly broadened peaks very close to the weld line where the

uncertainly was ten times larger. A control alumina sample was run in the same orientation as

the Ti6246 sample in order to check for any instrumental artefacts but the alumina spectra were

all found to be highly uniform. We conclude that the Rietveld refinements from all voxels

yielded statistically significant cell; preferred orientation and phase parameters but only

qualitative size-strain information as indicated by peak broadening.

The apparently random variation of clusters which show broad diffraction features away from

the LFW can be explained by a coincidence of the rather large size of the gauge volume and

the complex microstructure of Ti6246. Szczepanski et al. (2008) have determined from

orientation imaging microscopy (OIM) that there are regions within Ti6246 on the order of 300

to 500 µm of similarly orientated material. This is particularly evident from their figure 13

which illustrates the texture in a randomly selected region of material. They showed areas with

a high degree of preferred texture and proposed possible mechanisms for basal and prism slip

systems in the observed microstructure. They showed that these regions of preferred texture

corresponded to the beta-grain texture and morphology. They also showed that the length scale

13

of these textured regions was approximately the size of the prior beta grains indicating that

these textured regions were formed in the initial -processing steps. We therefore believe that

our TEDDI image has faithfully reflected the preferred orientation of metal grains that have

grown from the original texture. The resulting internal stresses built up from this growth

process have also been imaged although we require better quality data with higher counting

statistics and on a finer spatial scale to carry out any size-stain quantification. Depending upon

the statistical quality of the diffraction pattern in each voxel either quantitative or qualitative

data can be extracted. However it is always likely that external quantification of

microstructural features (such as grain sizes and internal stresses) will be required to

corroborate the TEDDI data.

A disadvantage of analysing metal materials with TEDDI is the need to illuminate a relatively

large voxel volume to ensue enough grains are in the diffraction position. This precludes a finer

step size but there are possibilities to overcome this difficulty using multiple detector arrays

that view the same voxel but from different angles. However this type of multi angle detector

array is not well suited to pixilation on a fine scale.

Despite these geometric difficulties we have demonstrated that TEDDI can image a 2D slice

through a 3D object non-destructively. This method is capable of being extended to higher

energies and can provide structural data at each voxel of a 3D image. We have used a single

CdZnTe detector and single collimator in this work so the experiment is scalable with suitable

area collimator and detector arrays. This will significantly speed up data collection which is

essential if TEDDI is to be used for processing monitoring. The method is expandable to

larger, more dense, fully fabricated objects depending upon the energy range of the incident X-

ray beam.

14

Figure captions

Figure 1 shows the intensity distribution as a function of energy from the beamline I15 on

DIAMOND at magnetic field strengths of 3.T and 1T. The useful energy range for energy

dispersive diffraction is also shown.

Figure 2 shows an optical micrograph of the sample with a diagrammatic indication of the

incident and exit beam paths. The exit collimation and gauge or sampling volume is shown in

plan and perspective view. The TEDDI image of the sample is also shown next to the

micrograph for comparison. The false colouration refers to the total intensity in the voxel so

does not refer to any specific structural feature before processing.

Figure 3 shows expanded view of the TEDDI image of the sample. The scan regions are

indicated. On the right hand side the three distinctive diffraction types are expanded with an

arrow showing their original location. The false colouration again refers to total intensity

within a voxel.

Figure 4 shows five Rietveld refinement output scans from line 20 and line 24 in the region of

the weld. Differences between 20a and 20b are due to preferred orientation. Similarly between

20d and 20e and 24a, 24b, 24d and 24e. The strain effects across the weld region in 20c and

24c manifest themselves in to form of peak broadening. The large peak visible is an

amalgamation of the (0 1 0), (0 0 2), (0 1 1) and (0 1 1) reflections. The positions of the

110 and 011 are shown by the dotted lines, there is a large growth in the latter at the LFW

Figure 5 shows the fluorescence peaks visible in all scans. Figure 5(a) shows the Rietveld

refined diffraction peaks from two voxels, one with broad and the other with narrow peaks.

The low angle florescence peaks can be seen expanded in figure 5(b). There are eight peaks in

total corresponding in energy to Pb L; Zr K; Mo K and Zr K; Mo K; two diffraction

escape peaks and the K and of Sn. All elements are present in the sample with the exception

of lead which forms part of the shielding. Figure 5(c) shows how the fluorescence peaks

broaden with increasing strain in voxels around the weld.

Figure 6 show the two phase Rietveld refinement and the quality of fit together with the

indexed peaks from the and phases.

Figure 7 Shows the normalised integrated intensity of the 110 peak, the disappearance across

the weld line is indicative of a large preferred orientation shift . PO clusters are not confined to

the weld line.

15

FIGURES

Figure 1

1.11E+11

6.11E+11

1.11E+12

1.61E+12

2.11E+12

2.61E+12

3.11E+12

3.61E+12

4.11E+12

0 20000 40000 60000 80000 100000 120000

Photon energy eV

Photon flux 0.1% bandpass-1 mrad-1 s-1

Practical usable photon energy

range for TEDDI experiments

3T

1T

16

Figure 2

Weld flash

CZT

detector

Diffracted

white beam

75 cm

collimator

Sampling volume

(gauge volume)

Incident white

X-ray beam

TEDDI image of

welded object

17

Figure 3

Line 24 Line 20

Voxel range for

values in tables 1 & 2

a

b

c

18

Figure 4

Line 20 Line 24

19

Figure 5

b

a

21.52120.52019.51918.51817.51716.51615.51514.51413.51312.51211.51110.5109.5

210

200

190

180

170

160

150

140

130

120

110

100

90

80

70

60

50

40

30

20

10

0

c 1 2

3

10 20 30 40 2

20

Figure 6

0 1 0

2 1 1 0 1 3

1 1 0

0 1 1

0 1 2

0 2 1

0 2 0

0 0 2

0 1 1 2 1 1 0 0 2

Intensity Arbitrary units

Bragg Angle 2

21

Figure 7

22

TABLES

Table 1 showing the parameters from the voxels labelled 20 a-e in figure 3

Structure File/Voxel on line 24 Wt % a Å c Å Vol Å3 GoF

phase P63/mmc 31802/24a

76(2) 2.93788(34) 4.7013(14) 35.141(13) 1.46

phase Im-3m 24(2) 3.2596(24) 34.632(77)

phase P63/mmc 31840/24b

76(2) 2.94033(96) 4.6663(48) 34.938(42) 1.16

phase Im-3m 24(2) 3.27481(82 35.120(26)

phase P63/mmc 31878/24c

18(4) 2.9980(41) 4.6803(35) 36.43(10) 1.11

phase Im-3m 82(4) 3.382(11) 38.70(39)

phase P63/mmc 31916/24d

75(2) 2.93456(47) 4.7005(23) 35.056(20) 1.38

phase Im-3m 25(2) 3.26047(98) 34.661(31)

phase P63/mmc 31954/24e

74(2) 2.94195(49) 4.7107(22) 35.309(20) 1.35

phase Im-3m 26(2) 3.2611(22) 34.681(70)

23

Table 2 showing the parameters from the voxels labelled 24 a-e in figure 3

Structure File/Voxel on line 20 Wt % a Å c Å Vol Å3 GoF

phase P63/mmc 31722/20a

77(2) 2.9423(10) 4.6967(25) 35.213(31) 1.45

phase Im-3m 23(2) 3.16830(63) 31.804(19)

phase P63/mmc 31798/20b

75(2) 2.93468(69) 4.6916(20) 34.993(22) 1.25

phase Im-3m 25(2) 3.25431(64) 34.465(20)

phase P63/mmc 31874/20c

27(4) 2.999(11) 4.850(23) 37.78(33) 1.80

phase Im-3m 73(4) 3.2923(28) 35.684(92)

phase P63/mmc 32026/20d

71(2) 2.93717(42) 4.6981(12) 35.100(13) 1.27

phase Im-3m 29(2) 3.2496(23) 34.314(71)

phase P63/mmc 32140/20e

70(2) 2.93661(39) 4.6839(10) 34.981(12) 1.50

phase Im-3m 30(2) 3.2585(10) 34.981(12)

24

References

Attallah MM, Zabeen S, Cernik RJ and

Preuss M,

Materials Characterisation, 2009 1248-1256

Barnes, P. Colston S, Craster B, Hall

C, Jupe A, Jacques S, Cockcroft J,

Morgan S, Johnson M, O’Connor D

and Bellotto M

J. Synchrotron Radiation. 2000 7(Pt 3), 167–177

Beale, AM, Jacques, SDM, Bergwerff,

JA, Barnes, P; Weckhuysen, BM

Angewandte Chemie-International Edition, 2007 46 (46): 8832-

8835

Bein, S, Bechet J

"Phase transformation kinetics and mechanisms in titanium alloys

Ti-6.2.4.6, beta-CEZ and Ti-10.2.3", La Bresse, France, 1996

Bhattacharyya D, Viswanathanm GB,

Denkenberger R, Furrer D, Fraser HL

Acta Materialia 2003, 51, 4679.

Bruneseaux F, Aeby-Gautier E,

Geandier G, Da Costa Teixeira J,

Appolaire B, Weisbecker P, Mauro A

Materials Science and Engineering: A 2008, 476, 60.

Cernik RJ, Khor KH and Hansson

CCT

R. Soc. Interface 2008 5, 477–481

Cernik, R. J., Freer, R., Leach, C.,

Mongkolkachit, C., Barnes, P.,

Jacques, S., Pile, K. & Wander, A.

J. Appl. Phys. 2007 101, 104 912.

Dollase WA J. Appl. Cryst. 1986 19, 267-272

Elmer JW, Palmer TA, Babu SS,

Specht ED

Materials Science and Engineering A 2005, 391, 104

Esslinger, J

Proceedings of the 10th World Conference on Titanium (Ti-2003), Weinheim, Germany, 2003.

Hall, C., Barnes, P., Cockcroft, J. K.,

Colston, S. L., Hausermann, D.,

Jacques, S. D. M., Jupe, A. C. & Kunz,

M.

Nucl. Instrum. Methods Phys. Res. Sect. B: Beam Interact. Mater. Atom 1998 140, 253–257.

Harding, G. & Schreiber, B. Radiation. Phys. Chem. 1999 56, 229–2545.

Johnson G, King A, Honnicke M C,

Marrow J and Ludwig W

J. Appl. Cryst. 2008 41, 310–318

Larson B C, Yang W, Ice G E, Budai J

D and Yischler J Z

Nature, 415, Feb 2002 887- 890

Lee E, Banerjee R, Kar S,

Bhattacharyya D, Fraser HL,

Philosophical Magazine 2007, 87, 3615.

Lutjering G and Wiliams JC Titanium, 2007 Berlin Springer-Verlag

Ma Q and Clarke DR J. Am. Ceram. Soc, 1993 76, [6] 1433-1440

Malinov S, Markovsky P, Sha W, Guo

Z

Journal of Alloys and Compounds 2001, 314, 181

Malinov S, Sha W, Guo Z, Tang

CC,AELong,

Materials Characterization 2002, 48, 279

Malinov S, Sha W, Markovsky P Journal of Alloys and Compounds 2003, 348, 110

Margulies L, Winther G and Poulsen H

F

Science, 291 March 2001, 2392-2394

Middelkoop, V; Boldrin, P; Peel, M;

Buslaps, T; Barnes, P; Darr, JA;

Jacques, SDM

Chemistry Of Materials, 2009 JUN 23 21 (12): 2430-2435

Stanford N, Bate P,

Acta Materialia 2004, 52, 5215.

Szczepanski CJ, Jha SK, Larsen JM,

and Jones JW

Metallurgical and materials Transactions A, 2008Vol 39A, Dec,

2841-2851 Tarin P, Alonso I, Simon AG, Badia

JM, Piris NM,

Materials Science and Engineering: A, 2006 Vol 438 364-368

25

Tarin P, Fernandez AL, Simon AG,

Badia JM, Piris NM

Materials Science and Engineering: A 2006, 438-440, 364.

Teixeira JDC, Appolaire B, Aeby-

Gautier E, Denis S, Cailletaud G,

Spath N

Materials Science and Engineering: A 2007, 448, 135

TOPAS Rietveld refinement

Bruker AXS GmbH, Karlsruhe 2003

Tunna, L.,Barclay,P., Cernik,R.

J.,Khor,K.H., O’Neill,W.& Seller, P.

Meas. Sci. Tec 2006 hnol. 17, 1767–1775

Venkatramani G, Ghosh S, Mills M, Acta Materialia 2007, 55, 3971.