Abstract: Chen will present the beamline P08 of PETRA III. The beamline has three main setups: a six circle diffractometer, the Langmuir trough GID setup, and the Uni-Kiel owned LISA liquid surface diffractometer. He will also talk in details the recent news from our Langmuir trough GID setup and GIXOS - pseudo reflectivity method.

Introduction and discussion on how to better promote/publicise ORSO

Abstract: Having the correct sample environment is integral to any part of a neutron scattering experiment as the scientist wishes to make measurements as a function of some external environmental condition. This presentation will present an overview of the latest developments in sample environments in neutron reflectometry with a focus on the reflectometers at the neutron beam facility at the OPAL Research Reactor, ANSTO. Trends in current developments in sample environments determined from analysis of the literature will be discussed highlighting where future developments could be found.

Abstract: With the current developments in fast X-ray reflectometry (XRR) reaching scan times as short as a few hundred microseconds, the few-photon count data reflects the inherent Poisson statistics of the counting process. In this regime, standard least squares fitting - which assumes symmetric Gaussian errors - can produce biased results. While Poisson log-likelihood methods exist, we demonstrate that applying the Anscombe transform - a well known variance-stabilizing transformation that converts Poisson-distributed data into approximately Gaussian-distributed data - permits continued use of the default least squares minimization utilized in most fitting softwares such as refnx or refl1d. This approach simplifies implementation and enables incorporation of additional noise sources, such as readout noise. It offers a practical and robust solution for accurate modeling in photon-limited XRR, relevant to the ORSO reflectometry community.

Abstract: Neutron reflectometry (NR) provides sub‑nm structural information at buried interfaces; however, time‑resolved NR is constrained by the minutes‑long counting times needed for acceptable statistics. This study introduces a data‑driven denoising methodology based on convolutional neural networks (CNNs) to overcome this limitation. One million synthetic multi-layered structures were generated; for each, both ideal and noise‑degraded reflectivity profiles were computed to supervise CNN training. The resulting model was applied to experimental‑style spectra acquired with 5 % of the usual neutron counts. CNN‑filtered profiles reproduced layer thicknesses and scattering‑length‑density distributions obtained from standard exposures within experimental uncertainty. These results confirm that acquisition times can be shortened by at least an order of magnitude without compromising analytical accuracy, enabling second‑scale observation of interfacial kinetics. The proposed approach shifts the limiting factor in time‑resolved NR from neutron flux to advanced data processing, substantially expanding the applicability of this technique to dynamic surface and interface studies.

• Sample Environment Working group (Sophie Ayscough)
• Data Analysis Working group (Andrew Nelson)

Introduction and discussion on how to better promote/publicise ORSO

Abstract: Composition-space modeling provides a versatile framework for interpreting scattering data from biological and soft matter systems. Rather than starting with abstract layers of scattering length density, this approach builds real-space models based on molecular groups that fill the available volume while satisfying spatial and stoichiometric constraints. From these physically grounded models, the corresponding scattering length density profiles and predicted reflectivity curves are derived and compared to experimental data.

This talk will provide an overview of the development and principles of composition-space modeling, highlighting its relevance to systems where components overlap spatially and interact in complex ways. I will present recent applications across neutron reflectometry, X-ray diffraction, and small-angle neutron scattering. I will discuss ongoing efforts at NIST to modernize and extend the modeling framework, including its integration into the Refl1D webview interface. This integration enables real-time visual feedback, streamlining model construction and enhancing accessibility for researchers working with layered biological and soft matter systems.

Abstract: TBC

• Education and Outreach Working group (Stefan Kowarik)
• Reproducibility Working group (Maciej Jankowski)
• Data Formats Working group (Jos Cooper)

• Recruitment of a temporary stand-in chair for the Reproducibility working group (to replace Andrew McCluskey)
• Summary of the working group sessions.

Abstract: The CANDOR reflectometer at the NIST Center for Neutron Research marries the advantages of time-of-flight polychromatic reflectometers, such as those commonly employed at pulsed neutron sources, to the high time-averaged flux of a reactor neutron source. CANDOR’s unique energy dispersive detector, currently comprising 108 individual wavelength-sensitive neutron detectors operating at over 90% efficiency, allows simultaneous detection of cold neutrons in the 4 Å to 6 Å wavelength range. In this talk, I will describe instrument design, detector operation and performance, and data reduction considerations. Reflectivity curves measured by CANDOR using polychromatic detection will be compared to standard curves measured at NIST’s monochromatic reflectometers, and the performance of CANDOR’s polarization capabilities will be discussed. For measurements of materials at solid/liquid interfaces, I will show that CANDOR’s high flux and intrinsic background rejection enables measurement to about twice the scattering vector, and hence resolution, of conventional measurements.