Synchrotron-based hard X-ray micro-tomography is a great tool for studying dynamic material changes:  the high flux at synchrotrons allow collection of full 3D images at close to 1 micron resolution in as little ~1 second, with the hard X-rays penetrating sample environments so that samples can be imaged at relevant temperatures and pressures. These microCT experiments come with two major challenges. First is the large data volumes of the experiment--extracting quantitative information and constructing computational models from microCT data is a challenge regardless of the data size, but the fact that most in situ experiments generate terabytes of data means that overcoming data management issues is a requirement. Second is the fact that microCT data cannot resolve nanometer structures or provide chemical information, so that it must be used as part of a suite of multi-modal tools in order to give real understanding.<br/>I will describe a few projects in which in situ microCT was carried out at the Hard X-ray Tomography Beamline (8.3.2) at the Advanced Light Source (ALS) at Lawrence Berkeley National Laboratory, and how it was combined with other techniques to create realistic and predictive computational models of the systems. These examples will include studies of lithium batteries during cycling; of Pd-Cu/Hydrotallcite catalysts (used to produce biodiesel) during gas and liquid phase reactions; of transport processes in thin porous carbon materials in polymer-electrolyte fuel cells and anion exchange membrane fuel cells during operation;<br/>I will present the advanced data management and analysis infrastructure that has been developed at the ALS, and how it was used to create computational models that incorporate 3D spatial information from microCT along with information from other experiments, including microscopy, spectroscopy, or scattering.

Modeling energy materials by integrating large microCT image volumes with data from microscopy, spectroscopy, and scattering

254th National Meeting (2017)

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