GigaFRoST: the gigabit fast readout system for tomography

Abstract

Owing to recent developments in CMOS technology, it is now possible to exploit tomographic microscopy at third-generation synchrotron facilities with unprecedented speeds. Despite this rapid technical progress, one crucial limitation for the investigation of realistic dynamic systems has remained: a generally short total acquisition time at high frame rates due to the limited internal memory of available detectors. To address and solve this shortcoming, a new detection and readout system, coined GigaFRoST, has been developed based on a commercial CMOS sensor, acquiring and streaming data continuously at 7.7 GB s À1 directly to a dedicated backend server. This architecture allows for dynamic data pre-processing as well as data reduction, an increasingly indispensable step considering the vast amounts of data acquired in typical fast tomographic experiments at synchrotron beamlines (up to several tens of TByte per day of raw data).

Dynamic in-situ imaging of methane hydrate formation and self-preservation in porous media

“…Characteristic time for one full scan is about 1-5 min for microtomography and about 5-60 min for nanotomography, depending on the sample size, instrument optics, and hardware limitations. Recent instrument developments (Mokso et al, 2017) allow to capture processes with sub-second temporal resolution. Important applications of fast imaging include multi-phase fluid flow in porous rocks (Youssef et al, 2013;Blunt et al, 2013;Fusseis et al, 2014a), deformation and geomechanical testing of samples (Baker et al, 2012;Li et al, 2015;Wang et al, 2016), and hydraulic fracturing (Kiss et al, 2015).…”

In situ observation of the percolation threshold in multiphase magma analogues

“…At the synchrotron, we performed two suites of X-ray tomography experiments using a GigaFRoST camera (Mokso et al 2017) which has a pixel size of 11 μm and a chip size of 2016 × 2016 pixels. These specificities combined with the optical magnification of the microscope of × 6.8 yield an effective pixel size for the measurements of 1.6 μm.…”

Impact of lossy compression of X-ray projections onto reconstructed tomographic slices

“…This is likely due to the worse signal-to-noise ratio typically encountered in 'fast' settings. Despite their small size of typically $ 4 GB and, therefore, reduced potential with respect to size reduction in absolute terms for a single dataset, tomographic experiments in the 'fast' setting modality foresee the acquisition of volumetric datasets in a time-resolved sustained manner with a data rate as high as 8 GB s À1 (Mokso et al, 2017), leading to tens of TB of raw data per day. Despite the need of higher attention in the threshold selection, compression of such datasets is, therefore, of utmost relevance.…”