NSLS-II   |   Brookhaven National Laboratory

Data Mining in Correlative Multi-modal X-ray Microscopy

Yijin Liu, Stanford Synchrotron Radiation Lightsource

The studies of structurally complex and chemically heterogeneous systems usually require a suite of analytical tools that are capable of providing complementary information. X-ray microscopy offers several different imaging modalities that probe structural and chemical information through different contrast mechanisms at different length scales. As a result, X-ray microscopy has been recognized as a powerful tool for researches across different scientific disciplines.

In this presentation, the strength of correlative multi-modal X-ray microscopy will be highlighted through brief discussion of a few scientific case studies including the researches in geoscience [1] and petroleum industry [2]. The information extraction aspect of these researches will be emphasized. More recent developments in the data mining associated with the spectro-microscopy will also be discussed by presenting case studies in energy material research [3].

References

[1] aYang et al., Sci. Rep. 5, 10635 (2015);

bHingerl et al., Int. J. Greenhouse Gas Control 48, 69–83 (2016).

cShi et al., Nat. Geosci. 6, 971–975 (2013);

dLiu et al., in prep.

[2] aMeirer et al., Sci. Adv. 1, e1400199 (2015);

bMeirer et al., J. Am. Chem. Soc.137, 102−105 (2015);

cLiu et al., Nat. Comm. 7, 12634 (2016).

dSimonetti et al., in prep.

[3] aYang et al., Nano Lett. 14, 4334-4341 (2014);

bXu et al., Nano Energy 28, 164-171 (2016);

cYu et al., Adv. Energy Mater. 5, 1402040 (2015);

dKuppan et al., Nat. Comm. 8, 14309 (2017);

eXu et al., in prep.