Prediction of Adsorption and Desorption Isotherms for Atmospheric Water Harvesting
dc.contributor.author | El-Amin, Mohamed F. | |
dc.date.accessioned | 2024-05-26T05:07:06Z | |
dc.date.available | 2024-05-26T05:07:06Z | |
dc.date.issued | 2024-03-01 | |
dc.identifier.doi | https://doi.org/10.1109/LT60077.2024.10469136 | en_US |
dc.identifier.uri | http://hdl.handle.net/20.500.14131/1683 | |
dc.description.abstract | This study improves the mathematical modeling for the potential of atmospheric water harvesting (AWH) using desiccant materials. This research is crucial in highlighting the sustainable water management strategies of AWH systems in converting atmospheric moisture into a vital water source. The primary focus of our research methodology was the analytical derivation of sorption isotherms, essential for the hygrothermal simulation of desiccant materials. This was accomplished through the application of two established models, namely, the Guggenheim-Anderson-de Boer (GAB) and Van Genuchten (VG). Experimental data on various anhydrous salts from existing literature have been used. An in-depth comparative analysis of these models reveals that the VG model aligns more closely with the experimental data, thus asserting its superiority in enhancing the selection and efficiency of desiccant materials in AWH systems. By confirming the VG model’s superiority in accurately modeling sorption isotherms, our research not only improves the model of AWH systems but also, importantly, contributes to the development of advanced water harvesting technologies. | en_US |
dc.publisher | IEEE | en_US |
dc.subject | Water;Adaptation models;Analytical models;Atmospheric modeling;Soil;Predictive models;Mathematical models;Atmospheric water harvesting (AWH);sorption isotherms;Guggenheim-Anderson-de Boer (GAB) model;Van Genuchten (VG) model | en_US |
dc.title | Prediction of Adsorption and Desorption Isotherms for Atmospheric Water Harvesting | en_US |
dc.contributor.researcher | College collaboration | en_US |
dc.contributor.lab | Energy Lab | en_US |
dc.subject.KSA | ENERGY | en_US |
dc.contributor.ugstudent | 0 | en_US |
dc.contributor.alumnae | 0 | en_US |
dc.source.index | Scopus | en_US |
dc.contributor.department | NSMTU | en_US |
dc.contributor.pgstudent | 0 | en_US |
dc.contributor.firstauthor | Narjisse, Kabbaj | |
dc.conference.location | Effat University, Jeddah, KSA | en_US |
dc.conference.name | 2024 21st Learning and Technology Conference (L&T) | en_US |
dc.conference.date | 2024-01-26 |