The collaboration between the PaNOSC and SSHOC clusters led to the successful creation of a dedicated Jupyter notebook for processing data from 2D µXRD experiments. This has significantly improved the efficiency of the experiments by saving time, providing a record of processed maps and their respective methods, ensuring consistency among users and sessions, and facilitating data reuse after embargo periods.
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Challenge
2D µXRD maps refer to two-dimensional X-ray diffraction maps obtained using a technique called micro X-ray diffraction (µXRD). X-ray diffraction is a powerful method used to analyse the crystal structure of materials. In the context of artwork analysis, 2D µXRD maps provide information about the arrangement and orientation of crystals within the paint layers of works of art.
Solution
To make the process of conducting 2D µXRD experiments more efficient, PaNOSC and a dedicated Jupyter notebook for data processing was the perfect solution. Here's why:
- Time-saving: By using a Jupyter notebook, researchers can streamline the data processing steps, making it quicker and easier to analyse the results of 2D µXRD experiments. This saves valuable time during the research process.
- Tracking processed maps: The notebook allows researchers to keep track of which 2D maps have already been processed and how. This ensures that there is no duplication of work and helps maintain an organised record of the experiment's progress.
- Consistency between users and sessions: Having a dedicated Jupyter notebook promotes consistency in data processing methods among different users and across multiple experimental sessions. This ensures that the results obtained from different experiments can be compared and analysed reliably.
- Data reuse after embargo: Some research data may be subject to an embargo period before it can be publicly shared. With a Jupyter notebook, researchers can document their data processing steps, making it easier for future users to reuse the processed data once the embargo period has ended. This promotes collaboration and knowledge sharing among researchers.
Impact
By performing 2D µXRD scans on painting fragments, researchers can identify the types of minerals, pigments, and other crystalline components present in the paint. This information can help determine the composition of the artwork, assess its authenticity, understand the materials used by the artist, and even reveal details about the painting's production techniques or potential alterations over time.
Creating reproducible and user-friendly 2D µXRD maps means developing a method that can be consistently applied by non-expert users at synchrotron facilities. Synchrotrons are specialised research facilities that produce intense X-ray beams, allowing for high-resolution and sensitive analysis. Making the process user-friendly ensures that researchers without extensive X-ray diffraction expertise can still obtain meaningful and reliable results when analysing painting fragments.
Access the source code on Gitlab via the link below.
