15 October 2026

Photo: Marta Mayer/DESY

Laura Gallardo positions a palm-leaf manuscript for X-ray analysis at beamline P62 at DESY.

For centuries, people across South and Southeast Asia wrote on palm leaves. To do so, the leaves had to undergo extensive preparation. Researchers from the CSMC and DESY have investigated what the material can reveal about these objects. The findings have been published in ‘npj Heritage Science’.

The study examined 85 manuscripts and 75 modern reference materials. The objects came from different collections and regions across South and Southeast Asia. The team investigated whether their material properties could help distinguish the palm genera used, identify different stages of leaf processing, and reveal possible links to geographical provenance. One key advantage of the method is that the analyses are non-destructive. No samples need to be removed from fragile historical objects. Instead, different X-ray techniques provide information about the leaves’ internal structure and chemical composition. The measurements were carried out at experimental station P62 at DESY’s PETRA III X-ray source, as well as at the European Synchrotron Radiation Facility (ESRF) in Grenoble, France.

Laura Gallardo, first author of the study, emphasises the importance of the non-destructive approach: ‘For rare and fragile cultural artefacts, the ability to obtain rich structural and chemical information without taking a sample is essential. By combining several synchrotron techniques, we can read different layers of a manuscript’s material history in a single experiment and compare large numbers of objects in a systematic way.’

The researchers combined three techniques, each of which captures different properties of the palm leaves. Small-angle X-ray scattering (SAXS) provides information about the structure and orientation of fibre networks. Wide-angle X-ray scattering (WAXS) provides information on the relative contributions of crystalline cellulose and amorphous substances. X-ray fluorescence (XRF) maps the distribution of chemical elements within the material.

The team used machine learning to analyse the measurement data together. Rather than relying on a single measurement, the approach draws on combinations of structural and chemical characteristics to distinguish between materials. The results show that the two palm genera examined can be distinguished comparatively reliably on the basis of their material characteristics. Processing plays an important role: after treatment, the differences between the palm genera became more pronounced. The measurable properties therefore reflect not only botanical origin but also different responses of both genera to manufacturing practices.