A systematic literature review of deep learning neural network for time series air quality forecasting

N Zaini, LW Ean, AN Ahmed, MA Malek - Environmental Science and …, 2022 - Springer
Rapid progress of industrial development, urbanization and traffic has caused air quality
reduction that negatively affects human health and environmental sustainability, especially …

Hybrid Smart Strategies to Predict Amine Thermal Degradation in Industrial CO2 Capture Processes

A Azarpour, S Zendehboudi - ACS omega, 2023 - ACS Publications
CO2 emission reduction is an essential step to achieve the climate change targets. Solvent-
based post-combustion CO2 capture (PCC) processes are efficient to be retrofitted to the …

[HTML][HTML] Application of machine learning models to improve the prediction of pesticide photodegradation in water by ZnO-based photocatalysts

A Dashti, AH Navidpour, F Amirkhani, JL Zhou… - Chemosphere, 2024 - Elsevier
Pesticide pollution has been posing a significant risk to human and ecosystems, and
photocatalysis is widely applied for the degradation of pesticides. Machine learning (ML) …

Carbon capture using ionic liquids: An explicit data driven model for carbon (IV) Oxide solubility estimation

OE Agwu, S Alatefi, A Alkouh, RA Azim… - Journal of Cleaner …, 2024 - Elsevier
In this study, carbon dioxide (CO 2) solubility in 20 different ionic liquids (ILs) belonging to
various chemical families was estimated across a broad range of pressures (0.0098–72.24 …

Toward predicting SO2 solubility in ionic liquids utilizing soft computing approaches and equations of state

MR Mohammadi, F Hadavimoghaddam… - Journal of the Taiwan …, 2022 - Elsevier
Background The use of novel and green solvents like ionic liquids (ILs) for the capture of air
pollutant gases has gained extensive attention in recent years. However, getting reliable …

[HTML][HTML] Estimation of CO2 solubility in aqueous solutions of commonly used blended amines: Application to optimised greenhouse gas capture

F Amirkhani, A Dashti, M Jokar, AH Mohammadi… - Journal of Cleaner …, 2023 - Elsevier
One of the key concerns in the 21st century, alongside the growing population, is the
increase in energy consumption and the resulting global warming. The impact of CO 2, a …

Insights into the estimation of surface tensions of mixtures based on designable green materials using an ensemble learning scheme

R Soleimani, AH Saeedi Dehaghani - Scientific Reports, 2023 - nature.com
Precise estimation of the physical properties of both ionic liquids (ILs) and their mixtures is
crucial for engineers to successfully design new industrial processes. Among these …

Predicting solubility of nitrous oxide in ionic liquids using machine learning techniques and gene expression programming

MN Amar, MA Ghriga, MEAB Seghier… - Journal of the Taiwan …, 2021 - Elsevier
Abstract Background-Nitrous oxide (N 2 O), as a potent greenhouse gas, is increasingly
becoming a major multidisciplinary concern in recent years. Therefore, the removal of N 2 O …

Chemical structure and thermodynamic properties based models for estimating nitrous oxide solubility in ionic Liquids: Equations of state and Machine learning …

R Nakhaei-Kohani, S Atashrouz… - Journal of Molecular …, 2022 - Elsevier
In past decades, nitrous oxide (N 2 O), a strong greenhouse gas, has become a serious
transdisciplinary issue. As a result, removing N 2 O utilizing strong green solvents like ionic …

Estimating flashpoints of fuels and chemical compounds using hybrid machine-learning techniques

F Amirkhani, A Dashti, H Abedsoltan, AH Mohammadi… - Fuel, 2022 - Elsevier
Flashpoint of organic materials is a crucial physical property in industrial applications and
laboratory experiments, which provides information on safety standards and needed …