Data-driven design of hybrid graphene oxide-MXene polymeric membranes for water purification
Rauf Khan, Nadeem Baig, Zaher Mundher Yaseen, Mohammad Al-Suwaiyan · 2026
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Description
Rauf Khan and co-authors describe a 2026 study of thin films that clean oily water with help from data models. Two flat materials, graphene oxide and MXene, were layered on a nylon base. Four film mixes with varied amounts of one layer were made and tested for how well they held back oil.
Math models were trained to guess how well each film would work from mix and pressure settings. One model type gave the closest guesses and showed that film mix and pressure mattered most. Pairing new materials with such models could cut trial and error in filter design. Larger data sets are planned to make the guesses hold up more widely.
Catalog record
| CREATOR | Rauf Khan, Nadeem Baig, Zaher Mundher Yaseen, Mohammad Al-Suwaiyan |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 63210 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |