Recent advancements in hydrogen storage-Comparative review on methods, operating conditions and challenges
Green hydrogen, proposed as a sustainable alternative for conventional fuels, has gained
utmost importance due to its reduced carbon footprint and potential application in …
utmost importance due to its reduced carbon footprint and potential application in …
Sustainable energies and machine learning: An organized review of recent applications and challenges
In alignment with the rapid development of artificial intelligence in the era of data
management, the application domains for machine learning have expanded to all …
management, the application domains for machine learning have expanded to all …
Machine-learning models to predict hydrogen uptake of porous carbon materials from influential variables
Hydrogen (H 2) absorption percentage by porous carbon media (PCM) is important for
identifying efficient H 2 storage media. PCM with H 2-uptakes of greater than 5 wt% are …
identifying efficient H 2 storage media. PCM with H 2-uptakes of greater than 5 wt% are …
Hydrogen production and pollution mitigation: Enhanced gasification of plastic waste and biomass with machine learning & storage for a sustainable future
The pursuit of carbon neutrality confronts the twofold challenge of meeting energy demands
and reducing pollution. This review article examines the potential of gasifying plastic waste …
and reducing pollution. This review article examines the potential of gasifying plastic waste …
Synergetic effect of N/O functional groups and microstructures of activated carbon on supercapacitor performance by machine learning
Heteroatoms-rich activated carbon (AC) can effectively promote the pseudo-capacitance of
AC-based electrodes used in supercapacitors. The well-known microstructural properties of …
AC-based electrodes used in supercapacitors. The well-known microstructural properties of …
Yield prediction and optimization of biomass-based products by multi-machine learning schemes: Neural, regression and function-based techniques
Pyrolysis, as a thermochemical conversion of biomass, is a superior biofuel production
procedure. The determining procedure for the optimal operational parameters, biomass …
procedure. The determining procedure for the optimal operational parameters, biomass …
Improving predictions of shale wettability using advanced machine learning techniques and nature-inspired methods: Implications for carbon capture utilization and …
The utilization of carbon capture utilization and storage (CCUS) in unconventional
formations is a promising way for improving hydrocarbon production and combating climate …
formations is a promising way for improving hydrocarbon production and combating climate …
Leveraging machine learning in porous media
The emergence of artificial intelligence (AI) and, more particularly, machine learning (ML),
has had a significant impact on engineering and the fundamental sciences, resulting in …
has had a significant impact on engineering and the fundamental sciences, resulting in …
Modeling the thermal transport properties of hydrogen and its mixtures with greenhouse gas impurities: A data-driven machine learning approach
This study introduces machine learning (ML) algorithms to predict hydrogen (H 2)
thermodynamic properties for geological storage, focusing on its mixtures with natural gas …
thermodynamic properties for geological storage, focusing on its mixtures with natural gas …
Advancements in sorption-based materials for hydrogen storage and utilization: A comprehensive review
F Qureshi, M Yusuf, S Ahmed, M Haq, AM Alraih… - Energy, 2024 - Elsevier
With its remarkable energy density and eco-friendly combustion properties, hydrogen stands
as a beacon of hope in our quest to meet future energy needs while ushering in a cleaner …
as a beacon of hope in our quest to meet future energy needs while ushering in a cleaner …