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Multiscale polyethylene fiber – bacterial nanocellulose composites through combined laser fusion and bacterial in situ synthesis

  • Samuel Schlicht EMAIL logo , Mara Wesinger , Anke Kaufmann , Uta Rösel , Dagmar Fischer and Dietmar Drummer
Published/Copyright: March 19, 2025
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International Polymer Processing
From the journal International Polymer Processing Volume 40 Issue 3

Abstract

Ultra-high molecular weight polyethylene (UHMW-PE) fibers and bacterial nanocellulose (BNC) display exceptional mechanical properties alongside the outstanding tribological properties of UHMW-PE while showing unrestricted biocompatibility. For combining the intrinsic advantages of both materials, the present work demonstrates an approach that integrates the slurry-based laser fusion of PE-polyvinylpyrrolidone (PE-PVP) composites and the subsequent bacterial biosynthesis of nanocellulose. PE-PVP composites exhibiting a fraction of 10 % of UHMW-PE fibers were additively manufactured through the locally selective laser-based layer-wise evaporation and subsequent sintering of aqueous suspensions, yielding fiber composites with a water-soluble matrix. The in situ synthesis of bacterial nanocellulose exploits the gelling and dissolving of high-molecular PVP in aqueous media. By allowing for the infiltration of printed PE-PVP composites with nanocellulose-producing Komagataeibacter xylinus, a multiscale composite of polyethylene fibers and bacterial nanocellulose was obtained, corroborating the infiltration of micrometer-scale PE fibers with nanoscale cellulose fibers. Release experiments using methylene blue confirmed the potentials of PE-BNC composites for drug delivery applications, showing first order sigmoidal release kinetics.

Keywords: multiscale composite; bacterial nanocellulose; polyethylene; drug delivery; additive manufacturing; UHMW-PE
Corresponding author: Samuel Schlicht, Institute of Polymer Technology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Am Weichselgarten 10, 91058 Erlangen, Germany, E-mail:

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission. S.S.: Conceptualization, Investigation, Methodology, Validation, Visualization, and Writing – Original Draft; M.W.: Writing – Original Draft, Investigation, Methodology; A.K.: Writing – Review and Editing; U.R.: Investigation; D.F.: Writing – Review and Editing, Funding Acquisition, D.D.: Writing – Review and Editing, Funding Acquisition.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors state no conflicts of interest.

  6. Research funding: None declared.

  7. Data availability: The data are available upon reasonable request from the corresponding author.

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Received: 2024-12-03
Accepted: 2025-03-04
Published Online: 2025-03-19
Published in Print: 2025-07-28

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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https://doi.org/10.1515/ipp-2024-0158
Keywords for this article
multiscale composite; bacterial nanocellulose; polyethylene; drug delivery; additive manufacturing; UHMW-PE

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. PPS2024 Ferrol: advances and perspectives in polymer processing
  4. Research Articles
  5. Applying network theory to the modeling of multilayer flows in slot dies: a use case for symbolic regression-based co-extrusion prediction models
  6. Multiscale polyethylene fiber – bacterial nanocellulose composites through combined laser fusion and bacterial in situ synthesis
  7. Novel approach to produce reinforced plastic weld seams using an additive friction stir welding process
  8. Local thermal activation for a combined thermoforming and 3D-printing process
  9. A new recycling strategy for airbag waste
  10. Highly electro-conductive PEDOT based thermoplastic composites: effect of filler form factor on electrical percolation threshold
  11. Cavity balance improvement for injection molded parts via automated flow leader generation
  12. Application of artificial intelligence techniques to select the objectives in the multi-objective optimization of injection molding
  13. Modeling melt conveying and power consumption of conveying elements in co-rotating twin-screw extruders
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