Traditional Water Conservation Techniques in India

Water conservation is a practice needed for survival. In India, various techniques are used to save water, which are practical and climate-responsive. From the age of the Indus valley civilization, till today many practices are seen in different parts of India. The traditional practices used for conserving water and even cooling buildings in ancient times. Forts surrounded water bodies for protection from enemies. Indians continue to build structures to catch and store the monsoon rains. Some unique water conservation techniques are still practiced in India and are efficient. These are sometimes better than the presentday water-saving techniques. The paper summarizes the transformation over the years in the construction and advancements of water conservation practices in India. In dry regions, these practices have helped people survive tough times. Keywords: Rain water harvesting, Storage, Tanks, Traditional methods, Water conservation

Hydrazide- and Diazole-Linked Covalent Organic Frameworks and Their Water Harvesting Properties

We report a retrosynthetic strategy and its implementation to making covalent organic frameworks (COFs) with irreversible hydrazide and diazole (oxadiazole and thiadiozole) linkages. This involved the synthesis of a series of 2D and 3D hydrazine-linked frameworks, followed by their oxidation and dehydrative cyclization. Each linkage synthesis and functional group transformation—hydrazine, hydrazide, oxadiazole, and thiadia-zole—was evidenced by 15N multi-CP-MAS NMR. In addition, the isothermal water uptake profiles of these frameworks were studied, leading to the discovery that one hydrazide-linked COF is suitable for water harvest-ing from air in arid conditions. These COFs displayed characteristic S-shaped water sorption profiles, a steep pore-filling step below 18% relative humidity at 25 °C, and a total uptake capacity of 0.45 g g–1 at P/Psat = 0.95. In addition, a total of ten 2D and 3D structures with various such linkages were studies for their affinity to water. We found that even small changes made on the molecular level can lead to major differences in the water isotherm profiles and therefore pointing to the utility of water sorption analysis as a complementary analytical tool to study linkage transformations.

Machine Learning-Assisted Computational Screening of Metal-Organic Frameworks for Atmospheric Water Harvesting

Atmospheric water harvesting by strong adsorbents is a feasible method of solving the shortage of water resources, especially for arid regions. In this study, a machine learning (ML)-assisted high-throughput computational screening is employed to calculate the capture of H2O from N2 and O2 for 6013 computation-ready, experimental metal-organic frameworks (CoRE-MOFs) and 137,953 hypothetical MOFs (hMOFs). Through the univariate analysis of MOF structure-performance relationships, Qst is shown to be a key descriptor. Moreover, three ML algorithms (random forest, gradient boosted regression trees, and neighbor component analysis (NCA)) are applied to hunt for the complicated interrelation between six descriptors and performance. After the optimizing strategy of grid search and five-fold cross-validation is performed, three ML can effectively build the predictive model for CoRE-MOFs, and the accuracy R2 of NCA can reach 0.97. In addition, based on the relative importance of the descriptors by ML, it can be quantitatively concluded that the Qst is dominant in governing the capture of H2O. Besides, the NCA model trained by 6013 CoRE-MOFs can predict the selectivity of hMOFs with a R2 of 0.86, which is more universal than other models. Finally, 10 CoRE-MOFs and 10 hMOFs with high performance are identified. The computational screening and prediction of ML could provide guidance and inspiration for the development of materials for water harvesting in the atmosphere.