Annual General Meeting of ORSO




The third annual meeting of the Open Reflectometry Standards Organisation.

The purpose of the meeting is to discuss topics of interest to the ORSO community. The program will consist of scientific anf technical talks together with discussion forums for each of the working groups

Please note that the timetable is using the time zone: Europe (Stokholm)

Each session has it's own Zoom link, please click on the session blocks in the timetable to find the link.

    • 09:00 12:00
      Plenary: Session 1

      Summary of progress since the last meeting
      3-4 scientific talks (speakers to be confirmed)

      Convener: Thomas Arnold (European Spallation Source ERIC)
      • 09:00
        Introduction 15m
        Speaker: Thomas Arnold (European Spallation Source ERIC)
      • 09:15
        Reproducible science in the neutron reflection context 30m

        Reproducibility is a broad term that covers many aspects of the scientific endeavour. In the context of a reflectometry experiment, ‘reproducibility’ can be understood to cover the details of sample preparation, data collection, data reduction, and data analysis. Attention to reproducibility is enabling: it allows the experiment to be repeated, the data handling pipeline to be checked, the data to be reanalysed, and the model to be reused.

        As data is passed from instrument to instrument scientists to user to journal article it is also transformed from complex formats with rich metadata into lowest-common-denominator formats often with no metadata. While ‘standard’, the data transformations are seldom published and the low fidelity of the transforms with regards metadata frustrates reproducibility. Significant progress has been made in the reproducibility of data analysis, with more publications making use of open source code that has been described in the literature; the specific details of the models including code to reproduce the analysis is now routinely featured in the publications from some groups.

        Recent achievements in improving the reproducibility of NR analysis will be illustrated using details from selected publications. Examples of good practice will be discussed, along with challenges (caused by current workflows, software, and file formats) that either prevent or discourage reproducibility.

        Speaker: Dr. Stuart Prescott (UNSW Chemical Engineering)
      • 09:45
        Spatially resolved neutron reflectometry by computed tomography 30m

        Neutron reflectometry (NR) has been employed to analyze the nanometric structure of the surface and interfaces of various materials. In a conventional NR experiment, the illuminated area is on the order of 1 - 10 cm^2; therefore, it has been difficult to use the NR for the sample with in-plane inhomogeneity. This work realized a spatially resolved NR technique by the combination of a "sheet-shaped" neutron beam with a two-dimensional detector and the computed tomography. The depth profile of the neutron scattering length density was analyzed at a local area smaller than 1 mm^2. The current NR tomography method would enable NR measurements for an interface with an inhomogeneous structure.

        Speaker: Hiroyuki Aoki
      • 10:15
        Coffee Break 15m
      • 10:30
        Resonant x-ray reflectivity: probing the chemical and magnetic profiles 30m
        Speaker: Tom Hase
      • 11:00
        Nina-Juliane Steinke 30m
      • 11:30
        The Data Formats Working Group 15m
        Speaker: Jochen Stahn (Paul Scherrer Institut)
      • 11:45
        The Education and Outreach Working Group 15m
        Speaker: Bridget Murphy
    • 19:00 22:00
      Plenary: Session 2

      Summary of progress since the last meeting
      3-4 scientific talks (speakers to be confirmed)

      Convener: Thomas Arnold (European Spallation Source ERIC)
      • 19:00
        Introduction 15m
        Speaker: Thomas Arnold (European Spallation Source ERIC)
      • 19:15
        Reinventing time-of-flight reflectometry—return of a proven approach 30m

        T. Charlton, H. Ambaye and A. Huon (ORNL)
        M.R. Fitzsimmons (ORNL/University of Tennessee, Knoxville)

        In this self-hosted Zoom-chat, I will discuss data acquisition and analysis techniques for neutron reflectometry at continuous wave (CW) sources applied to a pulsed-neutron source. I show data collected using the BL4A reflectometer at the Spallation Neutron Source (ORNL) using the so-called “CW-approach” and their analysis. The approach produces the reflectivity versus wavevector transfer without knowledge of the neutron beam spectrum. The results are compared to measurements of the same sample using the same instrument but with the traditional approach that involves normalization to the neutron beam spectrum typical of time-of-flight reflectometry. We find data acquired and analyzed using the CW-approach is less prone to instrumental artifacts than those obtained with the traditional approach and yields information that is more consistent with that obtained from X-ray reflectometry (at least for the sample studied). I discuss the implications of this study on how reflectometry data are collected at existing and proposed pulsed-neutron sources. I conclude with two parting and provocative questions:
        • Why did the time-of-flight reflectometry and SANS communities take such radically different approaches to data acquisition and analysis?
        • Given the success of the CW-approach, is a high frequency pulsed-source better suited for reflectometry than a low frequency source?

        Work funded by the U.S. Department of Energy under contract No. DE-AC05-00OR22725.

        Weblink to software and dataset in support of the presentation:

        Speaker: Tim Charlton
      • 19:45
        Free Thiols Regulatation of the Interactions and Self-Assembly of Thiol-Passivated Metal Nanoparticles investigated with X-ray scattering and MD simulations. 30m

        Pan Suna,1, Linsey M. Nowack b,1, Wei Bu a, Mrinal K. Bera a, Sean Griesemer b, Morgan Reik b, Joshua Portner b, Stuart A. Riceb,d, Mark L. Schlossman c and Binhua Lin a,b*
        a NSF’s ChemMatCARS, University of Chicago, Chicago, IL 60637, USA
        b James Franck Institute, University of Chicago, Chicago, IL 60637, USA
        c Department of Physics, University of Illinois at Chicago, Chicago, IL 60607, USA
        d Department of Chemistry, University of Chicago, Chicago, IL 60637, USA
        ABSTRACT: Thiol ligands bound to the metallic core of nanoparticles determine their interactions with the environment and self-assembly. Recent studies suggest that equilibrium between bound and free thiols alters the ligand coverage of the core. Here, X-ray scattering and MD simulations investigate water-supported monolayers of gold-core nanoparticles as a function of the core-ligand coverage that is varied in experiments by adjusting the concentration of total thiols (sum of free and bound thiols). Simulations demonstrate that the presence of free thiols produces a nearly symmetrical coating of ligands on the core. X-ray measurements show that above a critical value of core-ligand coverage the nanoparticle core rises above the water surface, the edge-to-edge distance between neighboring nanoparticles increases, and the nanoparticle coverage of the surface decreases. These results demonstrate the important role of free thiols: they regulate the organization of bound thiols on the core and the interactions of nanoparticles with their surroundings [1].
        [1] Pan Sun, Linsey M. Nowack, Wei Bu, Mrinal K. Bera, Sean Griesemer, Morgan Reik, Joshua Portner, Stuart A. Rice, Mark L. Schlossman, and Binhua Lin
        Nano Letters 2021 21 (4), 1613-1619
        DOI: 10.1021/acs.nanolett.0c04147

        Speaker: Binhua Lin
      • 20:15
        Coffee Break 15m
      • 20:30
        Why NeXus? 30m
        Speaker: Ray Osborn
      • 21:00
        35 years of x-ray reflectivity at NSLS & NSLS II: science hiding in small features and the new kid (instrument) on the block 30m
        Speaker: Ben Ocko
      • 21:30
        The Data Analysis Working Group 15m
        Speaker: Brian Maranville
      • 21:45
        The Reproducibility Working Group 15m
        Speaker: Andrew McCluskey (European Spallation Source ERIC)
    • 11:00 12:00
      Data Formats Working Group: Session 1: The present state
    • 13:00 14:00
      Data Formats Working Group: Session 2: Recommendations
    • 21:00 23:00
      Data Formats Working Group: Session 3: A common dictionary for reflectometry
    • 11:00 13:00
      Reproducibility Working Group: Session 1: The standard samples and calibrations project
    • 21:00 23:00
      Reproducibility Working Group: Session 2: The reproducible experiment checklist
    • 13:00 15:30
      Data Analysis Working Group: Session 1: Software Demonstrations/Tutorials
      • 13:00
        RefNX 20m

        Speaker: Andrew Nelson (Australian Nuclear Science and Technology Organisation)
      • 13:20
        GenX 20m

        Speaker: Artur Glavic (PSI - Paul Scherrer Institute)
      • 13:40
        BornAgain 20m

        Speaker: Joachim Wuttke
      • 14:00
        Coffee Break 20m
      • 14:20
        RasCAL2 20m
        Speaker: Arwel Hughes
      • 14:40
        Refl1D 20m

        Speaker: Brian Maranville
      • 15:00
        Analyzer 20m

        Speaker: Mrinal Bera
      • 15:20
        Dicussion 10m
    • 21:00 23:00
      Data Analysis Working Group: Session 2: Software Discussion Session
    • 11:00 13:00
      Education and Outreach Working Group: Session 1: The SLD database project
    • 14:00 16:00
      Education and Outreach Working Group: Session 2: A tutorial paper on the analysis of reflectometry
    • 19:00 21:00
      Plenary: Session 3

      Summary of progress since the last meeting
      3-4 scientific talks (speakers to be confirmed)

      • 19:00
        Summary of the working group sessions 30m
      • 19:30
        New Methods in Reflectivity Analysis: Neural Networks and the Fisher Information 30m
        Speakers: Joshanial Cooper, James Durant
      • 20:00
        Artificial Intelligence Analysis of Reflectivity Data 30m

        Stefan Kowarik1, Alessandro Greco2, David Marecek1, Erich Hüthmair1, Vladimir Starostin2, Alexander Hinderhofer2, Alexander Gerlach2, Maximilian Skoda3, and Frank Schreiber2
        — 1Department of Physical Chemistry, University of Graz, Austria
        — 2Institute of Applied Physics, University of Tübingen, Germany
        — 3Rutherford Appleton Lab, ISIS Neutron and Muon Source, UK
        We review the applicability of artificial neural networks to analyse X-ray reflectivity (XRR) and neutron reflectivity data. Compared to standard iterative fitting approaches, the neural network analysis can predict sample parameters without needing a good initial guess of the fit parameters. Also, a neural network analysis copes well with a low signal to noise ratio and a high background signal as long as features such as the total reflection edge are prominent. However, the prediction accuracy is lower than a standard fit with parameter errors around 10 %.
        In comparison with iterative fitting the neural network analysis is orders of magnitude faster, which is beneficial e.g. for estimates of parameter errors via quick predictions of multiple ‘leave-one-out’ / jack-knife XRR datasets. The processing speed also offers advantages for (on the fly) batch processing of large datasets e.g. from real-time experiments. Lastly, neural networks can co-refine multiple reflectivity curves, while taking into account prior information. For the example of XRR curves acquired during thin film growth this reduces parameter errors when compared to individual fits and also enables predictions not only of thickness, roughness or density but also of temporal parameters such as growth rate.
        [1] Greco et al., J. Appl. Cryst., 52, 1342 (2019)
        [2] Greco et al. Mach. Learn.: Sci. Technol. in press (2021)

        Speaker: Stefan Kowarik
      • 20:30
        Towards reflectivity profile inversion through artificial neural networks 30m

        The goal of specular neutron and x-ray reflectometry is to infer a material's scattering length density (SLD) profile from its experimental reflectivity curves. In this talk I will quickly describe the ill-posed non-invertible problem and an approach to some solutions via the use of artificial neural networks (ANNs). In particular, I will describe a set of tailored numerical experiments with the aim of assessing the applicability of data science and machine learning to the analysis of data generated at large-scale neutron scattering facilities. For this purpose, sample physical models are described under a new paradigm: layer-by-layer descriptions --in terms of SLDs, thicknesses and roughnesses, are replaced by parameter-free curves ρ(z), moving the focus of a priori assumptions towards the sample family to which a given sample belongs (e.g., 'thin film,' 'lamellar structure',etc.). The proposed methodology, when implemented correctly would enable quicker batch analyses of large datasets.

        Speaker: Juan Carmona Loaiza
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