亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Anti-wettability of Chemically and Physically Modified Glass Surfaces

作者
Suhad Sbeih,W. Steffen,Michael Kappl
出处
期刊:Advanced materials proceedings [VBRI Sverige AB]
卷期号:6 (1): 1-4 被引量:3
标识
DOI:10.5185/amp.2021.010421
摘要

The demand for new advanced functional materials has driven scientific work over the past decades. Nature has been inspiring in the creation of different types of self-cleaning and super repellent surfaces mimicking those of plants (lotus leaves), animals (shark skin) or insects (butterfly wings, water strider). To produce and maintain super repellent materials, chemical modification of the surface by using low surface energy materials such as fluoropolymers and/or siloxanes is necessary. Also, physical modification of surface roughness enhances super-repellency against various liquids. The surface roughness can be achieved e.g., by the deposition of nano particles (NPs) using Liquid Flame Spray (LFS). Industrial applications like paper coatings, oil-water separation, and microfluidic devices have benefited from the fabrication of super-hydrophobic surfaces by LFS. In our work, glass substrates were fluorinated by chemical vapor deposition (CVD) method, and others were additionally pre-coated with silica NPs by LFS. The coated glass surfaces were characterized for their anti-wettability by measuring the contact angles of water and compare that to bare glass. The influence of the produced coatings on the wettability of surface with different liquids was examined through measuring advancing/receding contact angles as well as the roll off angle. Results showed that compared to bare glass only fluorination of glass increased the water static contact angle from 18 to almost 112 . This is indicative of hydrophobic behaviour. Coating glass with silica NPs by LFS before fluorination, enhanced the water anti-wetting property for super hydrophobicity. LFS coating provided good oleophobic characteristic.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
ZhengGangan完成签到,获得积分10
1秒前
2秒前
hzhw发布了新的文献求助10
6秒前
Breeze完成签到,获得积分10
6秒前
7秒前
受伤天真发布了新的文献求助200
8秒前
Malik发布了新的文献求助10
10秒前
14秒前
15秒前
共享精神应助Malik采纳,获得10
20秒前
jundongfan发布了新的文献求助10
21秒前
酷波er应助灯火阑珊曦采纳,获得10
22秒前
冷静发布了新的文献求助10
26秒前
27秒前
30秒前
31秒前
32秒前
33秒前
34秒前
34秒前
ZJ发布了新的文献求助10
37秒前
wxd发布了新的文献求助10
39秒前
40秒前
不安访风完成签到 ,获得积分10
41秒前
Jason发布了新的文献求助20
44秒前
英姑应助su采纳,获得10
44秒前
动人的亦旋完成签到,获得积分10
46秒前
47秒前
jundongfan完成签到,获得积分20
48秒前
50秒前
wanci应助Jason采纳,获得20
51秒前
52秒前
jjj完成签到,获得积分10
54秒前
su完成签到,获得积分20
54秒前
1123发布了新的文献求助10
54秒前
54秒前
56秒前
su发布了新的文献求助10
57秒前
58秒前
石中酒发布了新的文献求助10
59秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
48V Low-voltage Power Distribution Network (PDN) Architecture Industry Report, 2024 800
ズームレンズの光学設計に関する研究 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7297287
求助须知:如何正确求助?哪些是违规求助? 8915741
关于积分的说明 18878850
捐赠科研通 6963004
什么是DOI,文献DOI怎么找? 3210524
关于科研通互助平台的介绍 2379855
邀请新用户注册赠送积分活动 2187016