16-22 October 2022
Institut Laue Langevin
Europe/Paris timezone
Registration and Call for Abstracts are now OPEN!

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ADD2022

School and Conference on Analysis of Diffraction Data in Real Space

Grenoble, 16 to 21 October 2022

 Co-organised by:
     
Institut Laue-Langevin (ILL) and The European Synchrotron (ESRF)

 

Aim, Scope and Format

The ADD2022 School and Conference aim to deepen the understanding and to further the training of the various communities working on real-space data analysis for neutron and x-ray diffraction techniques.  Fourier transformation of diffraction data into real-space, traditionally used for the structural determination of liquids and glasses, is now increasingly employed for partially-disordered crystalline powder samples, as well as for single-crystal samples exhibiting some local atomic disorder, and most recently for short-range spin-spin correlations in disordered or frustrated magnetic systems (in the case of neutron diffraction).

The scientific scope of ADD2022 pertains to both x-ray and neutron diffraction techniques, and will again include single-crystal diffuse scattering as an integral part of the School and the Conference.  Note that we also welcome presentations and participants in the field of e-beam diffraction having real-space analysis techniques.  The School proposes pedagogic lectures on real-space data-analysis techniques followed by 9 separate sessions of hands-on tutorials for training with various data-modelling software packages: DiffPy-CMI, diffpy.mpdf, DISCUS, Dissolve, EPSR, PDFgui, RMCProfile, Spinvert and Yell.  The Conference proposes 8 invited talks and about 16 additional oral contributions, as well as a poster session.

The Fourier transformation of diffraction data into real-space produces a Pair-Distribution Function (PDF) that provides a model-independent "snapshot" of the local structure within the sample.  The PDF(r) thus probes both static and dynamic atomic correlations (and also magnetic spin-spin correlations in the case of neutron diffraction).  The so-called "PDF-analysis" technique is therefore complementary to the well-known Rietveld method of refining diffraction data in Q-space that provides a space-time averaged picture of the sample's structure.  PDF-analysis now enjoys a wide field of application, in particular to nano-structured materials.

Building on the success of our previous ADD workshops in Grenoble (ADD2019 of 17-22 March 2019, ADD2016 of 7-11 March 2016, ADD2013 of 18-22 March 2013, ADD2011 of 12-14 October 2011), the ADD2019 School+Conference will start Sunday evening 16 October 2022 and finish Friday afternoon 21 October, a full 5-day programme that includes 2-1/2 days for the School followed by 2-1/2 days for the Conference, basically the same format as for ADD2019.

As compared to ADD2019, the 2022 edition includes two additional hands-on tutorials: (1) Dissolve, which builds on the success of EPSR and employs similar techniques, but utilises a full classical forcefield and is extensible to multi-configuration, million-atom simulations, and (2) diffpy.mpdf, which as an extension module of DiffPy-CMI allows for real-space modeling of local magnetic spin correlations.

And as for ADD2019, ADD2022 also features pedagogic lectures on nitty-gritty data-reduction and data-correction techniques for x-ray and neutron diffraction as concerns liquids/glasses, disordered crystals and single-crystal diffuse scattering.

Real-space analysis of diffraction data deals with general structural concepts such as atomic/spin distribution functions and structural/magnetic correlation lengths, and now employs standard formulae common to neutron, x-ray and other diffraction techniques.  It therefore facilitates a synergetic convergence of hitherto largely disjoint communities: liquids/glasses diffraction, crystalline powder diffraction, single-crystal diffuse scattering and diffuse magnetic scattering.

 

 

Sponsors

 

 

 

       

 

       
         

      

 

 

                                              

 

 

               

 

 

 

 

 

 

 

 

 

 

 

 

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