Three-dimensional, multimodal synchrotron data for machine learning applications.

Machine learning techniques are being increasingly applied in medical and physical sciences across a variety of imaging modalities; however, an important issue when developing these tools is the availability of good quality training data. Here we present a unique, multimodal synchrotron dataset of a bespoke zinc-doped Zeolite 13X sample that can be used to develop advanced deep learning and data fusion pipelines. Multi-resolution micro X-ray computed tomography was performed on a zinc-doped Zeolite 13X fragment to characterise its pores and features before spatially resolved X-ray diffraction computed tomography was carried out to characterise the topographical distribution of sodium and zinc phases.

Effective macropore diffusivity of carbon dioxide on binderless pellets of Y-type zeolites.

Unlabelled: The adsorption kinetics of carbon dioxide (CO) in three cationic forms of binderless pellets of Y-types zeolites (H-Y, Na-Y, and TMA exchanged Na-Y) are studied using the zero-length column (ZLC) technique. The measurements were carried out at [Formula: see text] and [Formula: see text] using different flowrates and an initial CO partial pressure of [Formula: see text]- conditions representative of post-combustion CO capture applications. The mass transport within the adsorbent pellets was described using a 1-D Fickian diffusion model accounting for intra- and inter-crystalline mass transport.