journal article·2016-08-01Open access

Extracting fiber and network connectivity data using microtomography images of paper

Svetlana Borodulina, Artem Kulachenko, Erik L.G. Wernersson, Cris L. Luengo Hendriks

Abstract

We apply image analysis methods based on micro-computed tomography (μCT) to extract the parameters that characterize the structure and bonding parameters in the fiber network of paper. The scaling and variational properties of μCT images are examined by analyzing paper structural properties of two 1 × 1 mm2 test pieces, which have been cut out from a low-grammage handsheet. We demonstrate the applicability of the methods for extracting the free fiber length, fiber cross-sectional data, the distances between the fibers, and the number of fiber-to-fiber bonds, which are the key properties required for the adequate representation of the network in numerical models. We compare the extracted connectivity data with the early reported analytical estimations and conclude that the number of contacts in three-dimensional networks is controlled by the fiber aspect ratio. In addition, we compare the cross-sectional data with those measured by the fiber morphology characterization tools and estimate the fiber shrinkage from completely wet to dry state to be nearly 20%.
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Research context

OpenAlex topics: Material Properties and Processing

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Affiliations

KTH, BiMaC Innovation, Department of Solid Mechanics , Stockholm , Sweden

Science for Life Laboratory , Solna , Sweden

Flagship Biosciences, Inc. , Westminster , Colorado, USA

References

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