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The effect of high relative humidity on a network of water-sensitive particles (couscous) as revealed by in situ X-ray tomography.

Ilija VegoAlessandro TengattiniEdward AndòNicolas LenoirGioacchino Viggiani
Published in: Soft matter (2022)
Water significantly influences the mechanical behaviour of all granular materials but none as much as hygroscopic amorphous particles. With sufficiently high water content, particles can swell, agglomerate and their mechanical properties can be reduced, having direct effects on the macroscopic response of the material. In the food and pharmaceutical industry this can cause loss of product functionality. Despite their relevance, very little is known about the microscopic processes that induce these phenomena. Previous studies focused on single particle behaviour, the strength of agglomerated particles and the material flowability, leaving unexplored the link connecting the particle behaviour and the bulk response. This experimental study aims to investigate this aspect with quantitative measurements at both particle and macroscopic scales. A sample of fine couscous is exposed to a high relative humidity (RH) air flow, while being subjected to oedometric conditions, in order to reproduce the storage-silo conditions. In the meantime, X-ray tomographies are acquired continuously and the resulting images are analysed. The designed spatial resolution allows each particle of the sample to be identified and tracked, allowing volumetric evolution to be compared to the properties of the whole sample. The analysis reveals a dilation-compaction macroscopic behaviour, a result of the competition between the particle swelling and the higher deformability as the water content increases. The number, orientations and inter-particle contacts are computed. Their area is related to the applied boundary conditions, and is found to be consistent with the particle swelling and dependent on the applied stress direction.
Keyphrases
  • magnetic resonance imaging
  • computed tomography
  • air pollution
  • deep learning
  • risk assessment
  • room temperature
  • case control
  • contrast enhanced