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Yuekun Lai

Researcher at Fuzhou University

Publications -  250
Citations -  19385

Yuekun Lai is an academic researcher from Fuzhou University. The author has contributed to research in topics: Chemistry & Engineering. The author has an hindex of 69, co-authored 193 publications receiving 13698 citations. Previous affiliations of Yuekun Lai include Soochow University (Suzhou) & University of Münster.

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A review of one-dimensional TiO2 nanostructured materials for environmental and energy applications

TL;DR: In this article, the crystal structure of 1D TiO2 and the latest development on the fabrication of 2D and 3D 1DTiO2 nanostructured materials are reviewed.
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High-Efficiency Photoelectrocatalytic Hydrogen Generation Enabled by Palladium Quantum Dots-Sensitized TiO2 Nanotube Arrays

TL;DR: The synergy between nanotubular structures of TiO(2) and uniformly dispersed Pd QDs on TiO.(2) facilitated the charge transfer of photoinduced electrons from TiO (2) nanotubes to PD QDs and the high activity of PdQDs catalytic center, thereby leading to high-efficiency photoelectrocatalytic hydrogen generation.
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A review on special wettability textiles: theoretical models, fabrication technologies and multifunctional applications

TL;DR: Inspired by the superhydrophobic lotus surface in nature, special wettability has attracted a lot of interest and attention in both academia and industry as discussed by the authors, and the strategies for constructing fabric surfaces with an anti-wetting property are categorized and discussed based on the morphology of particles coated on the textile fibre.
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Robust superhydrophobic TiO2@fabrics for UV shielding, self-cleaning and oil–water separation

TL;DR: InspInspired by the surface geometry and composition of the lotus leaf with its self-cleaning behavior, a robust superhydrophobic TiO2@fabric was further constructed by fluoroalkylsilane modification as a versatile platform for UV shielding, selfcleaning and oil-water separation as discussed by the authors.
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Designing Superhydrophobic Porous Nanostructures with Tunable Water Adhesion

TL;DR: Wang et al. as mentioned in this paper proposed a method to solve the problem of artificial neural networks in the field of computer vision and applied it to artificial intelligence in the context of artificial intelligence.