Neutron texture analysis on GEM at ISIS

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Abstract

Texture analysis by time-of-flight neutron diffraction, carried out on a multidetector instrument, requires just a few sample orientations. Moreover, on a diffractometer like GEM at ISIS with sufficiently high detector coverage a quantitative bulk texture analysis can be performed even on a stationary sample in a matter of minutes. A ‘single-shot’, rapid texture measurement on a high-count-rate instrument can be of considerable benefit for studying materials at non-ambient conditions or for bulky samples that cannot be mounted on a goniometer. The capabilities of GEM for texture analysis are demonstrated with results on copper texture standards, which were studied to accompany diffraction analyses of archaeological objects.

Introduction

Neutron diffraction is a well-established tool in engineering and geological sciences for quantitative analysis of the crystallographic texture of a material, which is related to geological and mechanical deformation processes. Low absorption of neutrons is of considerable advantage for studying big, coarse-grained geological samples but also for testing intact and unique museum objects for which sampling is unacceptable. Texture is measured by recording diffraction patterns as a function of the scattering angle, either by (i) rotating the sample on a goniometer and/or by (ii) using a multi-detector surrounding the sample. The amount of texture information is roughly given by the product of the number of pole figures (h k l) times the number of sample orientations [1]. Hence, by using a polychromatic beam and with many detectors at fixed scattering angles, time-of-flight (TOF) neutron diffraction has some considerable advantages for texture analysis since significant portions of both reciprocal space and orientation space are simultaneously covered in one measurement. The capabilities and benefits of extracting the orientation distribution function (ODF) of a material from TOF data is well documented both from the experimental and the data treatment point of view. TOF texture analysis with a multidetector set-up was previously demonstrated at the pulsed source IBR-2, Russia [2] and at the pulsed spallation source LANSCE, USA [3]. Moreover, in the past few years Rietveld codes such as MAUD [4] and GSAS [5] have been developed to determine texture coefficients from TOF data. Texture measurements increasingly take advantage of this development in crystallography and Rietveld analysis, allowing texture information from complex low symmetry and polyphase materials to be extracted.

By increasing the detector coverage on a TOF diffractometer fewer sample rotations are required for quantitative texture analysis, as was demonstrated on HIPPO at LANCSE [3], [6] with typically 4–8 sample orientations and total collection times in the order of 20 min. Here we show that on GEM at ISIS, quantitative texture information can be obtained even faster from a single measurement without any sample rotations. Results on copper reference samples that were measured to calibrate the diffraction results of complex archaeological metal objects are presented to assess the texture analysis capabilities of GEM.

Section snippets

Experimental details

GEM is a high-count-rate materials diffractometer designed to study the structures of both crystalline and liquid and amorphous samples [7]. GEM is equipped with 6 detector banks, housing a total of about 7000 individual detector elements with banks 1 and 6 covering forward and backscattering angles, respectively (Fig. 1(a)). One detector element is typically about 5×200 mm2 in size, corresponding to an angular coverage of about 0.2°×10° for a typical sample–detector distance at 90°. The total

Results and discussion

Fig. 2 shows reconstructed (1 1 1), (2 0 0) and (2 2 0) pole figures of the cold-rolled sample 1 for the three setting of Fig. 1(b)–(d) with data collection times of 2 min per orientation. The pole figures showing the typical hallmarks of a rolling texture are very similar for the three types of coverage models. Maximum multiples of a random distribution (m.r.d.) values and texture indices F2 [1] are in reasonable agreement (Table 1). It can be concluded that the texture can be determined from a

Acknowledgements

Support by L. Lutterotti, University of Trento, Italy, with the MAUD program is gratefully acknowledged. We would like to thank H. Phiesel, Bonn University, Germany, for providing the reference samples.

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