Sustainable Metal-Organic Framework Water Harvesters in the Artificial Intelligence Era
Metal-organic frameworks (MOFs) are excellent candidates for water harvesting due to their tunable pore environments, which can be precisely engineered to capture and release water in arid conditions. Integrating artificial intelligence (AI) into MOF discovery can further accelerate the design of high-performance sorbents by identifying structural features that enhance atmospheric water harvesting (AWH), stability, and cycling efficiency. In this Perspective, we examine key MOF design principles, including cooperative adsorption, operational relative humidity (RH), uptake capacity, hysteresis, and scalability. We highlight recent design advancements such as multivariate strategies and lon...
| Authors | Reid A. Coyle, Shyam Chand Pal, Peter Walther et al. |
|---|---|
| Primary category | cond-mat.mtrl-sci |
| Published | 27 May 2026 |
| Last updated at source | 15 June 2026 |
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