Use cases

Use Case 32 – Reflectometry case study

Description of research

Dr McCluskey et al. were interested in the structure of phospholipid monolayers at the surface of a novel Deep Eutectic Solvent (DES). They were able to collect a series of X-ray reflectometry data. However the analysis could not rely on the usual assumptions made about these materials previously measured on water.


Reflectometry is a model-dependent technique and as such, information about the sample under investigation is crucial to the analysis of experimental data.

The models are usually based on three parameters accounting for the density, roughness and thickness of layers at an interface. Typically the starting values are a mixture of sample knowledge, published results and trail and error.

Reflectometry publications have traditionally struggled to publish sufficient information about samples to allow the results to be fully reproducible. This is particularly true for delicate soft-matter samples that are prepared during experiments at air-liquid or solid-liquid interfaces.

Recent efforts from the community have led to the establishment of the Open Reflectometry Standards Organisation (ORSO) which is attempting to standardise file formats, data collection, reduction and analysis methodologies across both synchrotron and neutron large facilities.

How can ExPaNDS help?

  • Minting a DOI for the dataset and offering a data landing page where authorised users can download the dataset;
  • Associating the dataset, publication and analysis workflow and having each of them referencing the other using persistent identifier;
  • Tagging the dataset and analysis workflow application using community ontologies to make the elements easier to find by interested parties;
  • Making the data findable by the common search API and available in the PaN commons;
  • Explore options around the publishing and long-term preservation of data and best practices in open science.

ORSO and the FAIR principles applied to surface science were presented at the SXNS conference in January 2022: see last two presentations of the recording above.

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