[HTML][HTML] Enhancing Li+ recovery in brine mining: integrating next-gen emotional AI and explainable ML to predict adsorption energy in crown ether-based hierarchical …

SI Abba, J Usman, I Abdulazeez, LT Yogarathinam… - RSC …, 2024 - pubs.rsc.org
Artificial intelligence (AI) is being employed in brine mining to enhance the extraction of
lithium, vital for the manufacturing of lithium-ion batteries, through improved recovery …

New-generation machine learning models as prediction tools for modeling interfacial tension of hydrogen-brine system

A Gbadamosi, H Adamu, J Usman, AG Usman… - International Journal of …, 2024 - Elsevier
Abstract Recently, hydrogen (H 2) gas has gained prodigious attention as a sustainable
energy carrier to reduce acute dependence on fossil fuels due to its fascinating properties …

Bibliometric analysis of artificial intelligence in wastewater treatment: Current status, research progress, and future prospects

X Li, J Su, H Wang, G Boczkaj, J Mahlknecht… - Journal of …, 2024 - Elsevier
Wastewater treatment is an important topic for improving water quality and environmental
protection, and artificial intelligence has become a powerful tool for wastewater treatment …

Development of integrative data intelligence models for thermo-economic performances prediction of hybrid organic rankine plants

H Tao, OA Alawi, HM Kamar, AA Nafea, MM AL-Ani… - Energy, 2024 - Elsevier
Computer aid models such as machine learning (ML) are massively observed to be
successfully applied in different engineering-related domains. The current research was …

Recovery of Brine Resources Through Crown-Passivated Graphene, Silicene, and Boron Nitride Nanosheets Based on Machine-Learning Structural Predictions

I Abdulazeez, SI Abba, J Usman… - ACS Applied Nano …, 2023 - ACS Publications
The rising global demand for brine resources necessitates the exploration of alternative
sources to complement existing natural sources. It is imperative to explore innovative …

Insight into soft chemometric computational learning for modelling oily-wastewater separation efficiency and permeate flux of polypyrrole-decorated ceramic-polymeric …

U Baig, J Usman, SI Abba, LT Yogarathinam… - … of Chromatography A, 2024 - Elsevier
Reliable modeling of oily wastewater emphasizes the paramount importance of sustainable
and health-conscious wastewater management practices, which directly aligns with the …

[HTML][HTML] Ensemble hybrid machine learning to simulate dye/divalent salt fractionation using a loose nanofiltration membrane

N Baig, SI Abba, J Usman, M Benaafi… - Environmental Science …, 2023 - pubs.rsc.org
The escalating quantity of wastewater from multiple sources has raised concerns about both
water reuse and environmental preservation. Therefore, there is a pressing need for …

Spatial analysis and predictive modeling of energy poverty: insights for policy implementation

S Gawusu, SA Jamatutu, X Zhang, ST Moomin… - Environment …, 2024 - Springer
Understanding and alleviating energy poverty is critical for sustainable development. This
study harnesses a suite of Machine Learning (ML) algorithms to predict Multidimensional …

[HTML][HTML] Drinking Water Resources Suitability Assessment Based on Pollution Index of Groundwater Using Improved Explainable Artificial Intelligence

SI Abba, MA Yassin, AS Mubarak, SMH Shah, J Usman… - Sustainability, 2023 - mdpi.com
The global significance of fluoride and nitrate contamination in coastal areas cannot be
overstated, as these contaminants pose critical environmental and public health challenges …

Designing desalination MXene membranes by machine learning and global optimization algorithm

X Ma, C Lan, H Lin, Y Peng, T Li, J Wang… - Journal of Membrane …, 2024 - Elsevier
The development of energy-efficient and low-cost desalination techniques is crucial. Among
these techniques, reverse osmosis (RO) is considered one of the most promising solutions …