# Magnetic Resonance Imaging of Granular Materials

**Authors:** Ralf Stannarius

arXiv: 1703.01211 · 2018-09-14

## TL;DR

This paper explores the use of MRI for imaging granular materials, highlighting its advantages, limitations, and potential applications in studying packing, flow, and diffusion without particle tracking.

## Contribution

It provides an overview of MRI principles applied to granular matter, demonstrating its unique capabilities for dynamic and spatially resolved measurements.

## Key findings

- MRI can image granular packing, flow, and diffusion.
- Fast MRI slices can outperform X-ray in certain applications.
- MRI offers unique flow and diffusion profiling without particle tracking.

## Abstract

Magnetic Resonance Imaging (MRI) has become one of the most important tools to screen humans in medicine, virtually every modern hospital is equipped with an NMR tomograph. The potential of NMR in 3D imaging tasks is by far greater, but there is only 'a handful' of MRI studies of particulate matter. The method is expensive, time-consuming, and requires a deep understanding of pulse sequences, signal acquisition and processing. We give a short introduction into the physical principles of this imaging technique, describe its advantages and limitations for the screening of granular matter and present a number of examples of different application purposes, from the exploration of granular packing, via the detection of flow and particle diffusion, to real dynamic measurements. Probably, X-ray computed tomography is preferable in most applications, but fast imaging of single slices with modern MRI techniques is unmatched, and the additional opportunity to retrieve spatially resolved flow and diffusion profiles without particle tracking is a unique feature.

## Full text

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## Figures

18 figures with captions in the complete paper: https://tomesphere.com/paper/1703.01211/full.md

## References

98 references — full list in the complete paper: https://tomesphere.com/paper/1703.01211/full.md

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Source: https://tomesphere.com/paper/1703.01211