Xray CT Facility

Xray CT Facility

CT scanners offer a powerful non-destructive method for three-dimensional imaging of internal structure for a wide range of samples. Examples of application include analysis of porous rocks, materials research across various industries, detection of corrosion, cracks and flaws, assembly inspection of complex mechanisms and visualisation of biological tissues.  The School houses two high resolution micro-CT Scanners both of which use X-Ray’s to perform non-destructive 3D imaging of internal structures. One of these, an Xradia Versa XRM-410 is operated and maintained by the School of Engineering. The high-quality and high resolution 3D CT scanning machine is essential for the research on fluid flow dynamics in Porous Media. The diagram below shows an exampe of how CT scanners are used to create a digitial 3D pore network model from a standard core sample.

 

The research and development team in digital porous media technology at Aberdeen University have established novel tools and methods, as well as wide applications in geo-materials, energy and environmental research. The School also houses a high resolution 2D Scanning Electron Microscope (SEM), the SEM images are suitable for analysing multiscale materials. 

Carl Zeiss GeminiSEM 300  

High resolution Field Emission Scanning Electron Microscope (FESEM) with SE (secondary electron), BSE (backscattered electron) and CL (cathodoluminescence) detectors,  resolution up to 1.0 nm

 

Xradia VersaXRM-410

This CT scanner has a spatial resolution of 0.9 µm, a maximum source of 150 kV, and employs a unique two-stage magnification process that enables true submicron resolution for a wide range of sample sizes. Xradia is equipped with an in-situ tensile/compression/bending testing stage. The combination of the CT and testing stage is employed to quantify mechanical damage progression occurring when a material is strained.

 

XT H 225ST Nikon

This CT scanner has a spatial resolution of 3 µm, a maximum source of 225 kV. It is ideal for larger sample dimensions.