4.7 Article

Synthesis of chitosan grafted polymethyl methacrylate nanopolymers and its effect on polyvinyl chloride membrane for acetone recovery by pervaporation

Journal

CARBOHYDRATE POLYMERS
Volume 258, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.carbpol.2021.117704

Keywords

Emulsion polymerization; Polymer nanoparticles; Characterization; Sorption and pervaporation; Acetone recovery; Optimization

Funding

  1. Council for Scientific AMP
  2. Industrial Research, (CSIR), India [22/0746/17/EMR-II]
  3. CSIR

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Biopolymer nanoparticles based on chitosan offer a cost-effective, non-toxic alternative to traditional nanoparticles, and are more compatible with polymer membranes. Chitosan, as a cationic polymer surfactant, helps generate polymer nanoparticles for improving the organophilicity of PVC membranes. The membranes prepared with chitosan grafted PMMA nanopolymers showed enhanced performance in terms of acetone flux and selectivity, fitting closely to ENSIC and solution-diffusion model for sorption and pervaporation data, respectively.
In comparison to conventional nanoparticles biopolymer like chitosan based nanoparticles will be of much lower cost, non-toxic and more compatible with polymer membranes. As a cationic polymer surfactant chitosan is able to generate polymer nanoparticles during emulsion polymerization of methyl methacrylate. Accordingly, the organophilicity of polyvinyl chloride (PVC) membrane was significantly improved by incorporating chitosan grafted polymethyl methacrylate (PMMA) nanopolymers(NPs) prepared by emulsion polymerization. The NPs and the PVC-NP blend membranes were characterized. The chitosan: MMA wt. ratio and the wt.% of NP in PVC were optimized by a 5-level factorial design. The membranes prepared from i) PVC, PVC blended with 6.5 wt.% each of ii) chitosan, iii) PMMA and iv) NP showed a pervaporative flux (kg/m(2)/h)/acetone selectivity of 0.439/24.31, 0.477/21.56, 0.461/23.41 and 0.502/27.96, respectively for 5.6 wt.% acetone in feed. The sorption and pervaporation data showed close fitting to ENSIC and six-parameter solution-diffusion model, respectively.

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