Extracting fiber and network connectivity data using microtomography images of paper
Source abstract
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%.
Source: openalex_inverted_index · Quality: baseline
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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