scispace - formally typeset
X

Xuefeng Gao

Researcher at Shenzhen University

Publications -  107
Citations -  9933

Xuefeng Gao is an academic researcher from Shenzhen University. The author has contributed to research in topics: Myeloid leukemia & Microbiome. The author has an hindex of 28, co-authored 91 publications receiving 8500 citations. Previous affiliations of Xuefeng Gao include University of Science and Technology of China & Chinese Academy of Sciences.

Papers
More filters
Journal ArticleDOI

Biophysics: Water-repellent legs of water striders

Xuefeng Gao, +1 more
- 04 Nov 2004 - 
TL;DR: It is shown that it is the special hierarchical structure of the legs, which are covered by large numbers of oriented tiny hairs (microsetae) with fine nanogrooves, that is more important in inducing this water resistance.
Journal ArticleDOI

Bioinspired surfaces with special wettability

TL;DR: Recent progress in wettability on functional surfaces is reviewed through the cooperation between the chemical composition and the surface micro- and nanostructures, which may bring great advantages in a wide variety of applications in daily life, industry, and agriculture.
Journal ArticleDOI

Directional adhesion of superhydrophobic butterfly wings.

TL;DR: Direction adhesion on the superhydrophobic wings of the butterfly is showed and it is believed that this finding will help the design of smart, fluid-controllable interfaces that may be applied in novel microfluidic devices and directional, easy-cleaning coatings.
Journal ArticleDOI

The Dry-Style Antifogging Properties of Mosquito Compound Eyes and Artificial Analogues Prepared by Soft Lithography†

TL;DR: In this paper, the superhydrophobic antifogging technique was used to prevent micro-scale fog drops from condensing on the ommatidia surface, which can prevent light scattering and reflection from nucleated droplets.
Journal ArticleDOI

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.