Direct tomography imaging for inelastic X-ray scattering experiments at high pressure

Area of Science:

• Materials Science
• Condensed Matter Physics
• Spectroscopy

Background:

• High-pressure experiments using diamond anvil cells (DACs) often suffer from interfering signals from the cell components.
• Parasitic scattering from diamonds, gaskets, and pressure media can obscure sample signals, hindering analysis.
• Absorption edge overlaps between sample and DAC materials complicate inelastic X-ray measurements like X-ray Raman scattering spectroscopy.

Purpose of the Study:

• To develop a method for separating non-resonant inelastic X-ray scattering signals from the sample and the high-pressure sample environment.
• To overcome limitations imposed by parasitic signals in high-pressure X-ray scattering experiments.
• To demonstrate the technique's effectiveness for analyzing compressed materials.

Main Methods:

• Utilizing spatially resolved detection of scattered X-rays to distinguish sample signals from diamond anvil cell (DAC) contributions.
• Employing simple machine learning algorithms to identify detector pixels corresponding to the sample signal.
• Acquiring high-quality X-ray Raman scattering spectra of compressed α-quartz.

Main Results:

• Successfully separated sample signals from spurious scattering originating from the DAC without restricting detection angles.
• Achieved unprecedented spectral quality for the Si L_2,3-edge and O K-edge of compressed α-quartz.
• Observed clear evidence of a pressure-induced phase transition in α-quartz between 10 and 24 GPa.

Conclusions:

• The developed spatially resolved X-ray scattering technique effectively isolates sample signals in high-pressure DAC experiments.
• Machine learning aids in processing the spatially resolved data, simplifying analysis.
• The method provides high-quality spectra, enabling the detection of pressure-induced phase transitions in materials like α-quartz.