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Pore and Matrix Distribution in the Fiber Wall Revealed by Atomic Force Microscopy and Image Analysis
Abstract
A method for the ultrastructural investigation of fiber cross-sections based on atomic force microscopy in combination with image analysis is presented. A uniform distribution of pores across the matrix material within the fiber wall was revealed by impregnation of pulp fibers with poly(ethylene glycol). The effects of chemical and mechanical processing on the pore and matrix structure and on the arrangement of the cellulose fibril aggregates were investigated. During chemical processing, changes in the fiber ultrastructure occur: a broadening of the pore and matrix lamella widths in combination with a reduction in their number and an enlargement of the cellulose fibril aggregates. It was found that pores formed during pulping are evenly distributed across the fiber wall in the transverse direction. In contrast, refining increases the pore and matrix lamella width in the fiber wall closest to the middle lamella an effect which gradually decrease in size toward the lumen side.
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Cited by
Cheng, G., Varanasi, P., Li, C., Liu, H., Melnichenko, Y. B., Simmons, B. A., Kent, M. S., & Singh, S. (2011) · Biomacromolecules · doi:10.1021/bm101240z · Cited by 437
Metadata
- Authors
- Fahlén, J., & Salmén, L.
- Venue
- Biomacromolecules
- Publisher
- American Chemical Society (ACS)
- Published
- 2004-12-04
- Volume
- 6
- Issue
- 1
- Pages
- 433-438
- ISSN
- 1525-7797 (ISSN-L)
- 1526-4602
- OpenAlex
- W1969294745
- Cited by
- 212
- References
- 0
- FWCI
- 2.53
- Type
- journal article
- Language
- en
- Open access
- closed
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- Fahlén, J., & Salmén, L. (2005). Pore and Matrix Distribution in the Fiber Wall Revealed by Atomic Force Microscopy and Image Analysis. Biomacromolecules. https://doi.org/10.1021/bm040068x
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
