Suppr超能文献

用于高效大气水收集的仿生表面工程

Nature-Inspired Surface Engineering for Efficient Atmospheric Water Harvesting.

作者信息

Li Zihao, Tang Luheng, Wang Hanbin, Singh Subhash C, Wei Xiaoming, Yang Zhongmin, Guo Chunlei

机构信息

The Institute of Optics, University of Rochester, Rochester, New York 14627, United States.

School of Physics and Optoelectronics, South China University of Technology, Guangzhou 510640, China.

出版信息

ACS Sustain Chem Eng. 2023 Jul 18;11(30):11019-11031. doi: 10.1021/acssuschemeng.3c00760. eCollection 2023 Jul 31.

Abstract

Atmospheric water harvesting is a sustainable solution to global water shortage, which requires high efficiency, high durability, low cost, and environmentally friendly water collectors. In this paper, we report a novel water collector design based on a nature-inspired hybrid superhydrophilic/superhydrophobic aluminum surface. The surface is fabricated by combining laser and chemical treatments. We achieve a 163° contrast in contact angles between the superhydrophilic pattern and the superhydrophobic background. Such a unique superhydrophilic/superhydrophobic combination presents a self-pumped mechanism, providing the hybrid collector with highly efficient water harvesting performance. Based on simulations and experimental measurements, the water harvesting rate of the repeating units of the pattern was optimized, and the corresponding hybrid collector achieves a water harvesting rate of 0.85 kg m h. Additionally, our hybrid collector also exhibits good stability, flexibility, as well as thermal conductivity and hence shows great potential for practical application.

摘要

大气水收集是解决全球水资源短缺的一种可持续解决方案,这需要高效、高耐久性、低成本且环保的集水器。在本文中,我们报告了一种基于受自然启发的超亲水/超疏水铝表面的新型集水器设计。该表面通过激光和化学处理相结合制成。我们在超亲水图案与超疏水背景之间的接触角上实现了163°的对比度。这种独特的超亲水/超疏水组合呈现出自泵送机制,为混合集水器提供了高效的集水性能。基于模拟和实验测量,对图案重复单元的集水率进行了优化,相应的混合集水器实现了0.85 kg m h的集水率。此外,我们的混合集水器还具有良好的稳定性、柔韧性以及热导率,因此在实际应用中显示出巨大潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed57/10394688/aa96cb5d98c8/sc3c00760_0002.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验