One of the techniques at synchrotron sources that attract large user communities is X-ray absorption spectroscopy
(XAS). This technique allows researchers to probe electronic and structural properties of almost any type of material.
In general, detailed information on oxidation states and coordination geometries can be obtained in a straight forward
way on sample concentration ranging from pure metals to ppm levels of contaminants.
A selection of research areas covered by Beamline I811:
- The solubility of metal ions in natural waters is of high interest in forest, agricultural and environmental sciences
- Metal pollution, solubility and transport properties in organic soils
- Metal pollution and in fly ash from combustion processes
- Interaction between metal containing proteins and medical drugs
- To understand the how metal containing pigments works in glass
- To find the best preservation methods for the Vasa and other old ships by probing their sulphur and iron content
- Studies of oxidation changes in new battery types
- The structures of new nano-dot magnetic materials on surfaces
- In-situ studies of catalytic processes important for industrial applications and engine catalysts
The XAS experiment is conceptually simple. A highly monochromatic X-ray beam is scanned in energy while measuring the
X-ray beam intensity before and after passing through the sample. At specific energies each atomic species display so
called absorption edges, which is a sudden increase in absorption due to the excitation of the electrons in the atom.
The excitation energy is dependent on e.g. the oxidation state of the element, and the shape of the absorption edge
gives a "finger print" of the coordination geometry (often called X-ray absorption near edge structure, XANES).
After the absorption edge an interference pattern due to the neighbouring atoms can be seen (this is the extended X-ray
absorption fine structure, EXAFS). From this EXAFS pattern, detailed structural information such as bonding distances can
be deduced by fitting a structural model to the data.
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