Tables for
Volume H
Powder diffraction
Edited by C. J. Gilmore, J. A. Kaduk and H. Schenk

International Tables for Crystallography (2018). Vol. H, ch. 2.9, pp. 194-195

Section Large-volume cells for angular-dispersive diffraction

W. van Beeka* and P. Pattisona,b

aSwiss–Norwegian Beamlines at ESRF, CS 40220, 38043 Grenoble CEDEX 9, France, and bLaboratory for Quantum Magnetism, Institute of Physics, Ecole Polytechnique Federale de Lausanne, CH-1015 Lausanne, Switzerland
Correspondence e-mail: Large-volume cells for angular-dispersive diffraction

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This application implies the use of monochromatic X-rays with extremely high energies (70 keV and above). Such energies can be easily reached on third-generation synchrotrons with in-vacuum undulators, thus providing sufficient flux for angular-dispersive diffraction experiments. The challenge with these experiments is to have a sufficiently high X-ray energy to penetrate large sample-cell vessels while maintaining reasonably good angular resolution in the diffraction pattern. When using large in situ cells with low-energy diffraction, there is a severe peak-broadening effect resulting in a deterioration of the data quality. At high energies, however, where the scattering angles are small, the sample thickness has little effect on the angular resolution provided that the area detector is positioned at a sufficient distance from the sample. O'Brien et al. (2011[link]) explain the trade-offs for such experiments in detail and have shown that it is possible to extract useful structural information. Large-volume cells that used to be exclusively the domain of neutron diffraction and EDXRD have now also been adapted for angular-dispersive powder diffraction with, in some cases, increased speed and information content. For instance, Wragg et al. (2012[link]) studed an industrial methanol-to-olefin conversion process with operando time- and space-resolved diffraction. The sample is rapidly scanned up and down to provide one-dimensional spatial information. The results complement earlier experiments performed with a microreactor. Jacques et al. (2011[link]) extracted three-dimensional information by using dynamic X-ray diffraction computed tomography (XRD-CT). They measured over 50 000 diffraction patterns on beamline ID15 at the ESRF with different sample orientations, positions and temperatures. From this huge amount of data, they reconstructed the catalyst body in three dimensions with a diffraction pattern assigned to each volume unit within the sample as a function of time. With this information, they were able to follow the evolution of the catalytically active phase throughout the sample. Wragg et al. (2015[link]) have since performed Rietveld analysis on voxels from the XRD-CT data for a methanol-to-olefin reactor bed. It is also worth mentioning work by Jensen et al. (2007[link]), performed on beamline 1-ID at APS Argonne National Laboratory, investigating the kinetics of nanoparticle formation involving a sol–gel reaction in supercritical CO2 at 10 MPa. The reaction was studied with XRD and small-angle X-ray scattering (SAXS) in a large 30 ml vessel. In a different application, Friščić et al. (2013[link]) mounted a laboratory-scale 10 ml ball mill on the ID15 beamline in order to study mechanochemical reactions, which are used in numerous industrial production processes. By averaging ten 400 ms frames, they obtained sufficiently good data to perform full-pattern refinements and kinetic analysis, providing information about otherwise completely inaccessible processes. We therefore foresee a bright future for such extreme high-energy applications together with large-volume studies, since they provide a useful bridge between the academic and industrial worlds.


Friščić, T., Halasz, I., Beldon, P. J., Belenguer, A. M., Adams, F., Kimber, S. A. J., Honkimäki, V. & Dinnebier, R. E. (2013). Real-time and in situ monitoring of mechanochemical milling reactions. Nat. Chem. 5, 66–73.Google Scholar
Jacques, S. D. M., Di Michiel, M., Beale, A. M., Sochi, T., O'Brien, M. G., Espinosa-Alonso, L., Weckhuysen, B. M. & Barnes, P. (2011). Dynamic X-ray diffraction computed tomography reveals real-time insight into catalyst active phase evolution. Angew. Chem. Int. Ed. 50, 10148–10152.Google Scholar
Jensen, H., Bremholm, M., Nielsen, R. P., Joensen, K. D., Pedersen, J., Birkedal, H., Chen, Y.-S., Almer, J., Søgaard, E., Iversen, S. & Iversen, B. (2007). In situ high-energy synchrotron radiation study of sol–gel nanoparticle formation in supercritical fluids. Angew. Chem. Int. Ed. 46, 1113–1116.Google Scholar
O'Brien, M. G., Beale, A. M., Jacques, S. D. M., Di Michiel, M. & Weckhuysen, M. (2011). Closing the operando gap: the application of high energy photons for studying catalytic solids at work. Appl. Catal. A Gen. 391, 468–476.Google Scholar
Wragg, D. S., O'Brien, M. G., Bleken, F. L., Di Michiel, M., Olsbye, U. & Fjellvåg, H. (2012). Watching the methanol-to-olefin process with time- and space-resolved high-energy operando X-ray diffraction. Angew. Chem. Int. Ed. 51, 7956–7959.Google Scholar
Wragg, D. S., O'Brien, M. G., Di Michiel, M. & Lønstad-Bleken, F. (2015). Rietveld analysis of computed tomography and its application to methanol to olefin reactor beds. J. Appl. Cryst. 48, 1719–1728.Google Scholar

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