Literature DB >> 34299580

MR Study of Water Distribution in a Beech (Fagus sylvatica) Branch Using Relaxometry Methods.

Urša Mikac1, Maks Merela2, Primož Oven2, Ana Sepe1, Igor Serša1.   

Abstract

Wood is a widely used material because it is environmentally sustainable, renewable and relatively inexpensive. Due to the hygroscopic nature of wood, its physical and mechanical properties as well as the susceptibility to fungal decay are strongly influenced by its moisture content, constantly changing in the course of everyday use. Therefore, the understanding of the water state (free or bound) and its distribution at different moisture contents is of great importance. In this study, changes of the water state and its distribution in a beech sample while drying from the green (fresh cut) to the absolutely dry state were monitored by 1D and 2D 1H NMR relaxometry as well as by spatial mapping of the relaxation times T1 and T2. The relaxometry results are consistent with the model of homogeneously emptying pores in the bioporous system with connected pores. This was also confirmed by the relaxation time mapping results which revealed the moisture transport in the course of drying from an axially oriented early- and latewood system to radial rays through which it evaporates from the branch. The results of this study confirmed that MRI is an efficient tool to study the pathways of water transport in wood in the course of drying and is capable of determining the state of water and its distribution in wood.

Entities:  

Keywords:  beech (Fagus sylvatica); magnetic resonance imaging (MRI); moisture content (MC); relaxation times; wood

Year:  2021        PMID: 34299580     DOI: 10.3390/molecules26144305

Source DB:  PubMed          Journal:  Molecules        ISSN: 1420-3049            Impact factor:   4.411


  1 in total

1.  Two-step diffusion in cellular hygroscopic (vascular plant-like) materials.

Authors:  Marion Cocusse; Matteo Rosales; Benjamin Maillet; Rahima Sidi-Boulenouar; Elisa Julien; Sabine Caré; Philippe Coussot
Journal:  Sci Adv       Date:  2022-05-13       Impact factor: 14.957

  1 in total

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