Enhancing Fog Harvest Efficiency by 3D Filament Tree and Elastic Space Fabric

材料科学 线程(计算) 正硅酸乙酯 胶粘剂 复合材料 化学工程 纳米技术 计算机科学 操作系统 工程类 图层(电子)
作者
Luc The Nguyen,Zhiqing Bai,Jingjing Zhu,Can Gao,Hoang Luu,Bin Zhang,Jiansheng Guo
出处
期刊:ACS Sustainable Chemistry & Engineering [American Chemical Society]
卷期号:10 (34): 11176-11190 被引量:7
标识
DOI:10.1021/acssuschemeng.2c02765
摘要

Due to its multidimensional multilayer structure, elastic 3D space fabric (3D@SF) has a large fog capture area. However, it is constrained by droplet clogging. To solve the droplet clogging challenge, we created a new tree structure (Tree 3D@SF) that is almost similar to the branch of the Swamp Foxtail flower and to the two edges of a Shorebird's beaks. The filament surface of Tree 3D@SF's was modified by a simple bilayer method using silica nanoparticles and a hydrophobic adhesive to form hydrophobic bumps that periodically alternated highly hydrophobic sites. This formed the Hydrophobic/High Hydrophobic Bump-Tree 3D@SF. In addition, we adopted the sol–gel (polyurethane, tetraethyl orthosilicate and methyltriethoxysilane) and electrospray (PVAc) methods to develop High Hydrophobic-Tree 3D@SF and High Hydrophilic Knot-Tree 3D@SF. Specially, a novel-potential Auto 3D@SF fog collector was also developed by taking advantage of elasticity and change in the V-thread angle of 3D@SF, which was controlled by an automatic compression–relaxation system. Auto 3D@SF can be used in complex windy environments. Our results revealed that water harvesting rates using Auto 3D@SFs (4.31 g/cm2/h) and Tree 3D@SFs (4.29 g/cm2/h) were twice that of Original 3D@SF. This was attributed to improved synergistic effects of fog capturing, droplet growing and droplet shedding. These findings will inform the development of suitable designs of improved fog harvesters, particularly those that are based on elasticity of 3D space fabrics and textiles.

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
1秒前
ok发布了新的文献求助10
1秒前
1秒前
2秒前
2秒前
3秒前
科目三应助WSR采纳,获得10
3秒前
深情安青应助严钰佳采纳,获得30
5秒前
王木木发布了新的文献求助10
6秒前
机灵凛发布了新的文献求助30
7秒前
8秒前
8秒前
淇淇发布了新的文献求助10
8秒前
虚心臻发布了新的文献求助10
8秒前
8秒前
Ajian完成签到,获得积分20
8秒前
8秒前
科研通AI6.2应助llll采纳,获得10
9秒前
科研通AI6.4应助llll采纳,获得10
9秒前
在水一方应助llll采纳,获得10
9秒前
希望天下0贩的0应助llll采纳,获得10
10秒前
灵铭包发布了新的文献求助10
10秒前
小马甲应助llll采纳,获得10
10秒前
搜集达人应助llll采纳,获得10
10秒前
烟花应助llll采纳,获得10
10秒前
希望天下0贩的0应助llll采纳,获得10
10秒前
科研通AI6.4应助llll采纳,获得30
10秒前
wanci应助llll采纳,获得30
10秒前
CipherSage应助小熊采纳,获得10
12秒前
英姑应助瘦瘦采纳,获得10
12秒前
热情觅云完成签到 ,获得积分10
13秒前
Ajian发布了新的文献求助10
13秒前
行舟完成签到 ,获得积分10
13秒前
Orange应助lyric采纳,获得10
13秒前
Jin发布了新的文献求助10
14秒前
吴晨曦发布了新的文献求助10
14秒前
Yuki发布了新的文献求助10
15秒前
17秒前
果粒橙子完成签到 ,获得积分10
17秒前
快乐大山完成签到,获得积分10
17秒前
高分求助中
(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
Reducing Compassion Fatigue, Secondary Traumatic Stress and Burnout 600
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Mammalian Synthetic Biology 500
Auslegungsgeschichte 500
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 500
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 7638903
求助须知:如何正确求助?哪些是违规求助? 9212111
关于积分的说明 19761166
捐赠科研通 7205811
什么是DOI,文献DOI怎么找? 3275906
关于科研通互助平台的介绍 2437495
邀请新用户注册赠送积分活动 2273206