Recently, the team led by Professor Zhang Hua worked with Professor Wang Ruzhu and other team members from Shanghai Jiaotong University to publish the paper titled “Global water yield strategy for metal–organic frameworks assisted atmospheric water harvesting” in Cell Reports Physical Science. Dr. Wang Jiayun and Ying Wenjun from School of Energy and Power Engineering were both the first authors, USST was the first unit, Professor Zhang Hua was the corporate author, Professor Wang Ru Zhu was the corresponding author. The research establishes reliable models to analyze the global MOF-assisted atmospheric water-harvesting potential. This works provides guidance for the selection of adsorbents in different regions with various climates and bridge the gap between the physical properties of MOFs and their possible practical utility in SAWH systems.
Freshwater shortage is one of the most critical global problems threatening social and economic development. Sorption-based atmospheric water harvesting (SAWH) is recognized as a promising strategy for extracting atmospheric moisture to provide arid regions with potable water. However, the lack of benchmarks prevents the accurate evaluation of sorbents’ performance for system-oriented and location-/climate-specific selection. Herein, reliable models are established to analyze the global SAWH potential of metal-organic frameworks (MOFs) in terms of practical water yield.
This study constructed reliable predictive models to calculate the water-harvesting yields and energy requirements of six advanced MOFs in SAWH systems in various global climate conditions. Geospatial analysis for specific regions was conducted using high-precision weather data to reveal the application potential and prospects of the MOFs in SAWH systems in these regions.
The research work was sponsored by the General Program of the National Natural Science Foundation of China, the National Natural Science Foundation of China, the Shanghai Sailing Program, the Shanghai Morning Light Project.
Link to the paper: https://doi.org/10.1016/j.xcrp.2023.101742
