Abstract
X-ray computed micro-tomography typically involves a trade-off between sample size and resolution, complicating the study at a micrometer scale of representative volumes of materials with broad feature size distributions (e.g. natural stones). X-ray dark-field tomography exploits scattering to probe sub-resolution features, promising to overcome this trade-off. In this work, we present a quantification method for sub-resolution feature sizes using dark-field tomograms obtained by tuning the autocorrelation length of a Talbot grating interferometer. Alumina particles with different nominal pore sizes (50 nm and 150 nm) were mixed and imaged at the TOMCAT beamline of the SLS synchrotron (PSI) at eighteen correlation lengths, covering the pore size range. The different particles cannot be distinguished by traditional absorption µCT due to their very similar density and the pores being unresolved at typical image resolutions. Nevertheless, by exploiting the scattering behavior of the samples, the proposed analysis method allowed to quantify the nominal pore sizes of individual particles. The robustness of this quantification was proven by reproducing the experiment with solid samples of alumina, and alumina particles that were kept separated. Our findings demonstrate the possibility to calibrate dark-field image analysis to quantify sub-resolution feature sizes, allowing multi-scale analyses of heterogeneous materials without subsampling.
Highlights
X-ray computed micro-tomography typically involves a trade-off between sample size and resolution, complicating the study at a micrometer scale of representative volumes of materials with broad feature size distributions
We present a method to estimate the size of the unresolved pores in a material, based tunable grating interferometry performed at the TOMCAT beamline of the Swiss Light Source (Paul Scherrer Institut)
We discuss the results of the validation experiments, which are twofold: one experiment utilizes high-resolution synchrotron-based tomography of the same sample to validate the dark-field-based quantification, and the others validate the reproducibility of the dark-field signal analysis procedure by repeating it on single solid samples of the same alumina material, and on a control sample where multiple smaller alumina grains with distinct nominal pore sizes were kept separated (Fig. 13)
Summary
X-ray computed micro-tomography typically involves a trade-off between sample size and resolution, complicating the study at a micrometer scale of representative volumes of materials with broad feature size distributions (e.g. natural stones). By exploiting the scattering behavior of the samples, the proposed analysis method allowed to quantify the nominal pore sizes of individual particles. Our findings demonstrate the possibility to calibrate dark-field image analysis to quantify sub-resolution feature sizes, allowing multi-scale analyses of heterogeneous materials without subsampling. A complementary approach is to visualize the pore space with imaging techniques such as optical and electron microscopy, X-ray and neutron imaging, and ultrasound imaging[4] Each of these techniques has its respective advantages and disadvantages with respect to resolution, sample preparation, destructiveness, output format, etc. Is that the best achievable resolution is about three orders of magnitude times smaller than the field-of-view (FOV)[14] This results in a trade-off between the FOV and spatial resolution for both synchrotron and lab-based setups, implying that at the highest resolution, the imaged volume is not representative for materials that exhibit multi-scale structural heterogeneity (e.g. natural stones)
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