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

•Chitosan coated PMMA nanopolymers were prepared by emulsion polymerization.•The nanopolymers were incorporated in PVC membrane to enhance acetone flux and selectivity.•The membranes were characterized by FTIR, NMR, DLS, XRD, DTA-TGA, SEM, TEM, EDAX & DMA.•Chitosan: MMA and wt.% of nanopolymer i...

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Veröffentlicht in:Carbohydrate polymers 2021-04, Vol.258, p.117704, Article 117704
Hauptverfasser: Banerjee, Amritanshu, Ray, Samit Kumar
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Sprache:eng
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Zusammenfassung:•Chitosan coated PMMA nanopolymers were prepared by emulsion polymerization.•The nanopolymers were incorporated in PVC membrane to enhance acetone flux and selectivity.•The membranes were characterized by FTIR, NMR, DLS, XRD, DTA-TGA, SEM, TEM, EDAX & DMA.•Chitosan: MMA and wt.% of nanopolymer in PVC were optimized with factorial design.•The optimised membrane showed high flux and selectivity for pervaporative dehydration of acetone. 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/m2h)/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.
ISSN:0144-8617
1879-1344
DOI:10.1016/j.carbpol.2021.117704