journal article·2022-08

A novel application of cellulose aerogel composites from pineapple leaf fibers and cotton waste: Removal of dyes and oil in wastewater

Phu V. Vu, Trung D. Doan, Giang C. Tu, Nga H. N. Do, Kien A. Le, Phung K. Le

Journal of Porous Materials· Volume 29· Issue 4
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Abstract

Abstract In a world where demands for freshwater are ever-growing, wastewater remediation becomes a global concern. Especially, water, which is contaminated by oil, dyes, poses challenges to the management of water resources. The development of innovative processes for wastewater treatment is still a major obstacle. With regard to its fast removal rate and environmental compatibility, cellulose aerogel composites are recently considered as a potential contributor for water remediation. In this study, cellulose aerogel composites are fabricated using the sol-gel method from two-agroindustrial wastes: pineapple leaf fibers and cotton waste fibers in alkali-urea solution followed by freeze-drying. The prepared cellulose aerogel composites are extremely lightweight with a low density (0.053−0.069 g.cm−3) and high porosity of nearly 95%. It is worth noting that the mechanical strength of the cellulose aerogel composites is remarkably improved with their Young’s modulus increasing by 5-9 times compared to that of the previous aerogel composites using polyvinyl alcohol as a binder. The as-synthesized aerogel composites are directly applied to adsorb cationic methylene blue and exhibit a maximum adsorption uptake of 34.01 g.g-1. The methyltrimethoxysilane-coated cellulose aerogel composites also show their ability to deal with oil pollution with a maximum oil adsorption capacity of 15.8 g.g−1 within only 20 sec. Besides the oil removal, our developed cellulose aerogel composites have demonstrated their capability in treating dye-contaminated wastewater for the first time based on their evidenced ability to eliminate methylene blue.
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Research context

OpenAlex topics: Advanced Cellulose Research Studies · Aerogels and thermal insulation

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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