Wood–Moisture Relationships Studied with Molecular Simulations: Methodological Guidelines

Mingyang Chen (1) , Chi Zhang (1) , Ali Shomali (1) , Benoit Coasne (2) , Jan Carmeliet (3) , Dominique Derome (1)

1 ETH Zürich - Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich]
2 LIPhy - Laboratoire Interdisciplinaire de Physique [Saint Martin d’Hères]
3 ETH - Etude multi-échelle des Transferts en milieux Hétérogènes

This paper aims at providing a methodological framework for investigating wood polymers using atomistic modeling, namely, molecular dynamics (MD) and grand canonical Monte Carlo (GCMC) simulations. Atomistic simulations are used to mimic water adsorption and desorption in amorphous polymers, make observations on swelling, mechanical softening, and on hysteresis. This hygromechanical behavior, as observed in particular from the breaking and reforming of hydrogen bonds, is related to the behavior of more complex polymeric composites. Wood is a hierarchical material, where the origin of wood-moisture relationships lies at the nanoporous material scale. As water molecules are adsorbed into the hydrophilic matrix in the cell walls, the induced fluid-solid interaction forces result in swelling of these cell walls. The interaction of the composite polymeric material, that is the layer S2 of the wood cell wall, with water is known to rearrange its internal material structure, which makes it moisture sensitive, influencing its physical properties. In-depth studies of the coupled effects of water sorption on hygric and mechanical properties of different polymeric components can be performed with atomistic modeling. The paper covers the main components of knowledge and good practice for such simulations.

Mots clés: hygromechanical; wood; moisture; molecular dynamics; Monte Carlo simulations; S2 layer; upscaling

Domaines: Matière Condensée [cond-mat]; Matériaux

Mingyang Chen, Chi Zhang, Ali Shomali, Benoit Coasne, Jan Carmeliet, et al.. Wood–Moisture Relationships Studied with Molecular Simulations: Methodological Guidelines. Forests, 2019, 10 (8), pp.628. ⟨10.3390/f10080628⟩. ⟨hal-02328680⟩