Synthesis optimization and adsorption modeling of biochar for pollutant removal via machine learning

W Zhang, R Chen, J Li, T Huang, B Wu, J Ma, Q Wen… - Biochar, 2023 - Springer
Due to large specific surface area, abundant functional groups and low cost, biochar is
widely used for pollutant removal. The adsorption performance of biochar is related to …

Advancement and State-of-art of heterogeneous catalysis for selective CO2 hydrogenation to methanol

HR Darji, HB Kale, FF Shaikh, MB Gawande - Coordination Chemistry …, 2023 - Elsevier
Addressing global warming while fulfilling the growing need for energy, fuels, and chemicals
is a huge challenge currently faced by civilization. Utilization of carbon dioxide (CO 2) or CO …

Comparison between the WFD approaches and newly developed water quality model for monitoring transitional and coastal water quality in Northern Ireland

MG Uddin, A Jackson, S Nash, A Rahman… - Science of the Total …, 2023 - Elsevier
This study aims to evaluate existing approaches for monitoring and assessing water quality
in waterbodies in the North of Ireland using newly developed methodologies. The results …

[HTML][HTML] Assessing the impact of COVID-19 lockdown on surface water quality in Ireland using advanced Irish water quality index (IEWQI) model

MG Uddin, MTM Diganta, AM Sajib, A Rahman… - Environmental …, 2023 - Elsevier
The COVID-19 pandemic has significantly impacted various aspects of life, including
environmental conditions. Surface water quality (WQ) is one area affected by lockdowns …

Design of Flame‐Made ZnZrOx Catalysts for Sustainable Methanol Synthesis from CO2

T Pinheiro Araújo, J Morales‐Vidal… - Advanced Energy …, 2023 - Wiley Online Library
Mixed zinc‐zirconium oxides, ZnZrOx, are highly selective and stable catalysts for CO2
hydrogenation to methanol, a pivotal energy vector. However, their activity remains …

[HTML][HTML] Data-driven modelling for assessing trophic status in marine ecosystems using machine learning approaches

MG Uddin, S Nash, A Rahman, T Dabrowski… - Environmental …, 2024 - Elsevier
Assessing eutrophication in coastal and transitional waters is of utmost importance, yet
existing Trophic Status Index (TSI) models face challenges like multicollinearity, data …

Artificial intelligence enabled efficient power generation and emissions reduction underpinning net-zero goal from the coal-based power plants

WM Ashraf, GM Uddin, HA Ahmad, MA Jamil… - Energy Conversion and …, 2022 - Elsevier
A large power generation facility is a complex multi-criteria system associated with
multivariate couplings, high dependency, and non-linearity among the operating variables …

Predicting municipal solid waste gasification using machine learning: A step toward sustainable regional planning

Y Yang, H Shahbeik, A Shafizadeh, S Rafiee, A Hafezi… - Energy, 2023 - Elsevier
The gasification process can treat and valorize municipal solid waste (MSW) in an
environmentally and economically friendly way. Using this process, MSW can be safely …

Machine learning based prediction and experimental validation of arsenite and arsenate sorption on biochars

W Zhang, WM Ashraf, SS Senadheera… - Science of the Total …, 2023 - Elsevier
Arsenic (As) contamination in water is a significant environmental concern with profound
implications for human health. Accurate prediction of the adsorption capacity of arsenite [As …

[HTML][HTML] Data-driven evolution of water quality models: An in-depth investigation of innovative outlier detection approaches-A case study of Irish Water Quality Index …

MG Uddin, A Rahman, FR Taghikhah, AI Olbert - Water Research, 2024 - Elsevier
Recently, there has been a significant advancement in the water quality index (WQI) models
utilizing data-driven approaches, especially those integrating machine learning and artificial …