A review of ionic liquids and deep eutectic solvents design for CO2 capture with machine learning

J Sun, Y Sato, Y Sakai, Y Kansha - Journal of Cleaner Production, 2023 - Elsevier
Ionic liquids (ILs) and deep eutectic solvents (DESs) are regarded as the next generation
solvents for carbon capture which consist of cations and anions. Thousands of combinations …

Modeling the emission characteristics of the hydrogen-enriched natural gas engines by multi-output least-squares support vector regression: Comprehensive …

T Hai, DH Kadir, A Ghanbari - Energy, 2023 - Elsevier
The hydrogen-enriched natural gas engines (HENGEs) have recently found huge popularity.
Despite the broad range of applications of the HENGE, their environmentally-associated …

Developing gasification process of polyethylene waste by utilization of response surface methodology as a machine learning technique and multi-objective optimizer …

R Hasanzadeh, P Mojaver, T Azdast… - International Journal of …, 2023 - Elsevier
This study set out to evaluate the performance of response surface methodology as a
machine learning technique on gasification process of polyethylene waste. Different models …

Exploring temporal dynamics of river discharge using univariate long short-term memory (LSTM) recurrent neural network at East Branch of Delaware River

MAA Mehedi, M Khosravi, MMS Yazdan, H Shabanian - Hydrology, 2022 - mdpi.com
River flow prediction is a pivotal task in the field of water resource management during the
era of rapid climate change. The highly dynamic and evolving nature of the climatic …

Efficient machine learning algorithm with enhanced cat swarm optimization for prediction of compressive strength of GGBS-based geopolymer concrete at elevated …

PK Dash, SK Parhi, SK Patro, R Panigrahi - Construction and Building …, 2023 - Elsevier
In order to assess building damage and develop fire safety applications, it is crucial to
examine the mechanical behavior of concrete after exposure to high temperatures …

Research on the coupling of ecological environment and socio-economic development in resource-based cities: Based on scenario simulation method

X Fan - Sustainable Cities and Society, 2024 - Elsevier
Resource-based cities (RBCs) encounter numerous challenges in terms of ecological
environment (EE) protection and socio-economy (SE) upgrading. This exerts pressure on …

Application of machine learning techniques to the modeling of solubility of sugar alcohols in ionic liquids

A Bakhtyari, A Rasoolzadeh, B Vaferi, A Khandakar - Scientific Reports, 2023 - nature.com
The current trend of chemical industries demands green processing, in particular with
employing natural substances such as sugar-derived compounds. This matter has …

Removal of recalcitrant organic matter of landfill leachate by adsorption onto biochar from sewage sludge: A quali-quantitative analysis

VRCM Zanona, CER Barquilha, MCB Braga - Journal of Environmental …, 2023 - Elsevier
Sewage sludge is a byproduct of sewage treatment, whereas landfill leachate is a complex
wastewater generated by the decomposition of solid waste. These byproducts require …

Simultaneous prediction of CO2, CO, and NOx emissions of biodiesel-hydrogen blend combustion in compression ignition engines by supervised machine learning …

L Zhang, G Zhu, Y Chao, L Chen, A Ghanbari - Energy, 2023 - Elsevier
This study mathematically inspects the effects of engine speed/load and biodiesel–hydrogen
fuel blend composition on CO 2, CO, and NO x emissions. Since this modeling task requires …

Predicting deep eutectic solvents for absorption of SO2 based on multilayer perceptron

D Jin, Y Zhu, S Tang, Z Liu - Separation and Purification Technology, 2025 - Elsevier
Sulfur dioxide (SO 2) is a common air pollutant, primarily emitted from fossil fuel combustion
and industrial flue gas. Deep eutectic solvents (DESs) have been proven to be innovative …