Shape-Enhanced Photocatalytic Activities of Thoroughly Mesoporous ZnO Nanofibers

Xiaolong Ren, Huilin Hou, Zhixiong Liu, Fengmei Gao, Jinju Zheng, Lin Wang, Wenge Li, Pengzhan Ying, Weiyou Yang, Tao Wu

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

1D mesoporous materials have attracted extensive interest recently, owning to their fascinating properties and versatile applications. However, it remains as a grand challenge to develop a simple and efficient technique to produce oxide nanofibers with mesoporous architectures, controlled morphologies, large surface areas, and optimal performances. In this work, a facile foaming-assisted electrospinning strategy with foaming agent of tea saponin is used to produce thoroughly mesoporous ZnO nanofibers with high purity and controlled morphology. Interestingly, mesoporous fibers with elliptical cross-section exhibit the significantly enhanced photocatalytic activity for hydrogen production, as compared to the counterparts with circular and rectangular cross-sections, and they also perform better than the commercial ZnO nanopowders. The unexpected shape dependence of photocatalytic activities is attributed to the different stacking modes of the mesoporous fibers, and a geometrical model is developed to account for the shape dependence. This work represents an important step toward producing thoroughly mesoporous ZnO nanofibers with tailored morphologies, and the discovery that fibers with elliptical cross-section render the best performance provides a valuable guideline for improving the photocatalytic performance of such mesoporous nanomaterials. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Original languageEnglish (US)
Pages (from-to)4007-4017
Number of pages11
JournalSmall
Volume12
Issue number29
DOIs
StatePublished - Jun 23 2016

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: The work was supported by the National Natural Science Foundation of China (NSFC, Grant Nos. 51372122 and 51372123) and the Program of Shanghai Outstanding Technical Leaders (Grant No. 14XD1425400). This work was also supported by the King Abdullah University of Science and Technology (KAUST).

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