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Identification of polymer matrix yield stress in the wood cell wall based on micropillar compression and micromechanical modelling

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Raghavan,  Rejin
Empa, Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Mechanics of Materials and Nanostructures, Feuerwerkerstrasse 39, Thun, Switzerland;
Synthesis of Nanostructured Materials, Structure and Nano-/ Micromechanics of Materials, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;

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Citation

Schwiedrzik, J., Raghavan, R., Rüggeberg, M., Hansen, S., Wehrs, J., Adusumalli, R. B., et al. (2016). Identification of polymer matrix yield stress in the wood cell wall based on micropillar compression and micromechanical modelling. Philosophical Magazine, 96(32-34), 3461-3478. doi:10.1080/14786435.2016.1235292.


Cite as: http://hdl.handle.net/21.11116/0000-0001-B288-C
Abstract
Based on a combination of micropillar compression experiments and modelling of the secondary cell wall (cw) using continuum micromechanics, the shear yield stress of the polymer matrix is identified for both normal and compression wood of Norway spruce. It is shown that the model is able to capture the differences in mechanical properties between the two tissues based on the knowledge of composition of the samples, microfibril angle, as well as phase properties on the nanometer scale. By testing an isolated piece of the cell wall with a homogeneous and uniaxial stress field on the micrometer scale and using the micromechanical model to determine average stress fields on the nanometer scale, it is possible to identify the shear yield stress of the polymer matrix in wood, which was found to be in the range of 14.9–17.5 MPa for normal and compression wood. It was shown that this corresponds to a stress in the lignin phase of approx. 17 MPa. This combined study thus demonstrates a new approach for validating multiscale models predicting yield properties with uniaxial experiments at the microscale and measuring phase properties of inhomogeneous materials by a combination of modelling and experimental approaches. © 2016 Empa Swiss Federal Laboratory for Materials Science and Technology.