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Physico‐Chemical Properties of Laponite®/Polyethylene‐oxide Based Composites.

  • Published In: Chemical Record, 2024, v. 24, n. 2. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Lysenkov, Eduard; Klepko, Valery; Bulavin, Leonid; Lebovka, Nikolai 3 of 3

Abstract

This review aims to provide a literature overview as well as the authors' personal account to the studies of Laponite® (Lap)/Polyethylene‐oxide (PEO) based composite materials and their applications. These composites can be prepared over a wide range of their mutual concentrations, they are highly water soluble, and have many useful physico‐chemical properties. To the readers' convenience, the contents are subdivided into different sections, related with consideration of PEO properties and its solubility in water, behavior of Lap systems(structure of Lap‐platelets, properties of aqueous dispersions of Lap and aging effects in them), analyzing ofproperties LAP/PEO systems, Lap platelets‐PEO interactions, adsorption mechanisms, aging effects, aggregation and electrokinetic properties. The different applications of Lap/PEO composites are reviewed. These applications include Lap/PEO based electrolytes for lithium polymer batteries, electrospun nanofibers, environmental, biomedical and biotechnology engineering. Both Lap and PEO are highly biocompatible with living systems and they are non‐toxic, non‐yellowing, and non‐inflammable. Medical applications of Lap/PEO composites in bio‐sensing, tissue engineering, drug delivery, cell proliferation, and wound dressings are also discussed. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Chemical Record. 2024/02, Vol. 24, Issue 2, p1
  • Document Type:Article
  • Subject Area:Engineering
  • Publication Date:2024
  • ISSN:1527-8999
  • DOI:10.1002/tcr.202300166
  • Accession Number:175327862
  • Copyright Statement:Copyright of Chemical Record is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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