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New software protocols for enabling laboratory based temporal CT

delete2018-09-05
delete18
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OA
AI
P
Parmesh Gajjar *
J
Jakob Sauer Jørgensen
J
Jose R. A. Godinho
C
C. G. Johnson
A
Andrew Ramsey
P
Philip J. Withers
DOI:10.1063/1.5044393delete
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摘要

摘要

En 中文
Temporal micro-computed tomography (CT) allows the non-destructive quantification of processes that are evolving over time in 3D. Despite the increasing popularity of temporal CT, the practical implementation and optimisation can be difficult. Here, we present new software protocols that enable temporal CT using commercial laboratory CT systems. The first protocol drastically reduces the need for periodic intervention when making time-lapse experiments, allowing a large number of tomograms to be collected automatically. The automated scanning at regular intervals needed for uninterrupted time-lapse CT is demonstrated by analysing the germination of a mung bean (vigna radiata), whilst the synchronisation with an in situ rig required for interrupted time-lapse CT is highlighted using a shear cell to observe granular segregation. The second protocol uses golden-ratio angular sampling with an iterative reconstruction scheme and allows the number of projections in a reconstruction to be changed as sample evolution occurs. This overcomes the limitation of the need to know a priori what the best time window for each scan is. The protocol is evaluated by studying barite precipitation within a porous column, allowing a comparison of spatial and temporal resolution of reconstructions with different numbers of projections. Both of the protocols presented here have great potential for wider application, including, but not limited to, in situ mechanical testing, following battery degradation and chemical reactions. Published by AIP Publishing.
Keyword:
X-RAY MICROTOMOGRAPHY
COMPUTED-TOMOGRAPHY
MICRO-CT
IMAGE-RECONSTRUCTION
MICROSTRUCTURE
MORPHOLOGY
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期刊

Review of Scientific Instruments 封面图
Review of Scientific Instruments
IF:
1.7
论文数:
627
被引数:
3.5W

机构

U
University of Manchester
学者数:
5.7W
论文数: 5.3W
被引数: 7.4W
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