Wet-strength agent improves recyclability of dip-catalyst fabricated from gold nanoparticle-embedded bacterial cellulose and plant fibers
Source abstract
Abstract
Noble metal nanoparticles (MNPs) and proper structural supporting materials can be fabricated into a sheet like catalytic composite, which is called dip-catalyst. Dip-catalyst is accentuated by its highly convenient deployment, easy separation and great recyclability. Polymeric film- or paper-based dip-catalyis has problems of low catalytic efficiency and MNP leaching or aggregation. Bacterial cellulose (BC) with its naturally nano-porous surface structure can efficiently support and stabilize the MNPs. Further compositing with plant fibers, the economy, catalytic efficiency and mechanical stiffness of the dip-catalyst may be greatly improved. However, the aqueous phase recyclability of the cellulosic fiber-based dip-catalyst is still limited, impairing its broad application. In this study, polyethylenimine (PEI) was used to crosslink BC-fiber and fiber–fiber within the BC-fiber matrix to improve the wet strength of the dip-catalyst. In detail, plant fibers were composited with the Au NP-embedded BC to fabricate a dip-catalyst through the paper handsheet making method. During the process, PEI was added as a wet-strength agent. The catalytic activity of this dip-catalyst was evaluated on the reduction of 4-nitrophenol in water by using NaBH4. Adding 1% PEI reduced the turnover frequency of 10% Au-BC sheet from 131.9 to 53.7 h−1, but greatly improved its recyclability and reusability. After reused for 30 times, reaction rate and yield was well maintained without impaired for the Au-BC catalytic sheets with PEI additions. This study promotes much broader applications for the BC-fiber dip-catalyst in chemical reactions.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Nanomaterials for catalytic reactions · Advanced Cellulose Research Studies · Copper-based nanomaterials and applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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