Log InRegister
Quick Links : The Mindat ManualThe Rock H. Currier Digital LibraryMindat Newsletter [Free Download]
Home PageAbout MindatThe Mindat ManualHistory of MindatCopyright StatusWho We AreContact UsAdvertise on Mindat
Donate to MindatCorporate SponsorshipSponsor a PageSponsored PagesMindat AdvertisersAdvertise on Mindat
Learning CenterWhat is a mineral?The most common minerals on earthInformation for EducatorsMindat ArticlesThe ElementsThe Rock H. Currier Digital LibraryGeologic Time
Minerals by PropertiesMinerals by ChemistryAdvanced Locality SearchRandom MineralRandom LocalitySearch by minIDLocalities Near MeSearch ArticlesSearch GlossaryMore Search Options
Search For:
Mineral Name:
Locality Name:
Keyword(s):
 
The Mindat ManualAdd a New PhotoRate PhotosLocality Edit ReportCoordinate Completion ReportAdd Glossary Item
Mining CompaniesStatisticsUsersMineral MuseumsClubs & OrganizationsMineral Shows & EventsThe Mindat DirectoryDevice SettingsThe Mineral Quiz
Photo SearchPhoto GalleriesSearch by ColorNew Photos TodayNew Photos YesterdayMembers' Photo GalleriesPast Photo of the Day GalleryPhotography

Iqbal, Sadaf, Aftab, Kiran, tul Jannat, Fakiha, Ali Baig, Muhammad, Kalsoom, Umme (2024) A bibliographic analysis of optimization of hydrogen production via electrochemical method using machine learning. Fuel, 372. 132126 doi:10.1016/j.fuel.2024.132126

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleA bibliographic analysis of optimization of hydrogen production via electrochemical method using machine learning
JournalFuel
AuthorsIqbal, SadafAuthor
Aftab, KiranAuthor
tul Jannat, FakihaAuthor
Ali Baig, MuhammadAuthor
Kalsoom, UmmeAuthor
Year2024 (September)Volume372
PublisherElsevier BV
DOIdoi:10.1016/j.fuel.2024.132126Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID17432879Long-form Identifiermindat:1:5:17432879:9
GUID0
Full ReferenceIqbal, Sadaf, Aftab, Kiran, tul Jannat, Fakiha, Ali Baig, Muhammad, Kalsoom, Umme (2024) A bibliographic analysis of optimization of hydrogen production via electrochemical method using machine learning. Fuel, 372. 132126 doi:10.1016/j.fuel.2024.132126
Plain TextIqbal, Sadaf, Aftab, Kiran, tul Jannat, Fakiha, Ali Baig, Muhammad, Kalsoom, Umme (2024) A bibliographic analysis of optimization of hydrogen production via electrochemical method using machine learning. Fuel, 372. 132126 doi:10.1016/j.fuel.2024.132126
In(2024) Fuel Vol. 372. Elsevier BV

See Also

These are possibly similar items as determined by title/reference text matching only.

Jannat, Fakiha tul, Aftab, Kiran, Akhtar, Kalsoom, Khan, Samreen Gul, Ali, Majid (2025) Optimizing acidogenic fermentation for NiFe2O4-rGO nanoparticles enhanced biohydrogen generation using Box-Behnken design. Fuel, 388. doi:10.1016/j.fuel.2025.134512
Javed, Nighat; Aftab, Kiran; Jannat, Fakiha Tul; Siddique, Zumaira (2025) Electrocatalytic performance of modified NiFe2O4/rGO composite deposited on fluorine-doped tin oxide electrode using polyvinylidene fluoride binder. Journal of Materials Research, 40 (5). doi:10.1557/s43578-025-01532-8
Aftab, Kiran, Javed, Javeria, Habibhah Siddiqua, Umme, Malik, Ayesha, Hassan, Afifa, Rizwan Khan, Mohammad, Busquets, Rosa, Ahmad, Naushad, Haque, Anzarul (2024) Process optimization and method validation for efficient valorization of low- grade coal into humic substances. Fuel, 369. 131796 doi:10.1016/j.fuel.2024.131796
Mousavitabar, Seyed Mohammad Ali, Khoshgoftar Manesh, Mohammad Hasan (2024) Multi-objective optimization and 4E analysis of a novel stand-alone LNG production system by employing the machine-learning approach. Fuel, 374. 132415 doi:10.1016/j.fuel.2024.132415
Zaka, Alishbah, Aftab, Misha, Fatima, Nudrat, Mashood, Khola, Asghar, Muhammad Adeel, Numan, Arshid, Ahmad, Muhammad Sheraz, Haider, Ali, Iqbal, Mudassir, Shah, Waqas Ali, et al. (2025) MnFe2O4 thin film electrodes via AACVD: A facile route for enhanced oxygen evolution reaction. Fuel, 395. doi:10.1016/j.fuel.2025.135179
Mehmood, Rana Adeel, Aslam, Awais Ali, Iqbal, Muhammad Javid, Sajid, Ali Hamza, Hamza, Ameer, Tahira, Hina Fatima, Islam, Izaz Ul, Yabalak, Erdal (2025) A review on hydrogen production using decorated metal-organic frameworks by electrocatalytic and photocatalytic water splitting. Fuel, 387. doi:10.1016/j.fuel.2025.134416
Sun, Yesen, Dai, Hong-liang, Moayedi, Hossein, Nguyen Le, Binh, Muhammad Adnan, Rana (2024) Predicting steady-state biogas production from waste using advanced machine learning-metaheuristic approaches. Fuel, 355. 129493 doi:10.1016/j.fuel.2023.129493
Nayab, Rida, Imran, Muhammad, Ramzan, Muhammad, Tariq, Muhammad, Taj, Muhammad Babar, Akhtar, Muhammad Nadeem, Iqbal, Hafiz M.N. (2022) Sustainable biodiesel production via catalytic and non-catalytic transesterification of feedstock materials – A review. Fuel, 328. 125254 doi:10.1016/j.fuel.2022.125254
Al-Qadri, Ali A., Ahmed, Usama, Abdur Razzak, Shaikh, Shahbaz, Muhammad, Hussain, Murid, Zein, Sharif H (2025) Technical and economic assessment of hydrogen production from heavy fuel oil via thermochemical conversion routes. Fuel, 385. doi:10.1016/j.fuel.2024.134054
Alanazi, Amer, Ali, Mujahid, Ali, Muhammad, Keshavarz, Alireza, Iglauer, Stefan, Hoteit, Hussein (2024) The reversal of carbonate wettability via alumina nanofluids: Implications for hydrogen geological storage. Fuel, 370. 131842 doi:10.1016/j.fuel.2024.131842
Zhao, Qingqi, Wang, Hongsheng, Chen, Cheng (2024) Underground hydrogen storage: A recovery prediction using pore network modeling and machine learning. Fuel, 357. 130051 doi:10.1016/j.fuel.2023.130051
 
and/or  
Mindat.org is an outreach project of the Hudson Institute of Mineralogy, a 501(c)(3) not-for-profit organization.
Copyright © mindat.org and the Hudson Institute of Mineralogy 1993-2025, except where stated. Most political location boundaries are Β© OpenStreetMap contributors. Mindat.org relies on the contributions of thousands of members and supporters. Founded in 2000 by Jolyon Ralph.
To cite: Ralph, J., Von Bargen, D., Martynov, P., Zhang, J., Que, X., Prabhu, A., Morrison, S. M., Li, W., Chen, W., & Ma, X. (2025). Mindat.org: The open access mineralogy database to accelerate data-intensive geoscience research. American Mineralogist, 110(6), 833–844. doi:10.2138/am-2024-9486.
Privacy Policy - Terms & Conditions - Contact Us / DMCA issues - Report a bug/vulnerability Current server date and time: August 31, 2025 04:41:01
Go to top of page