Pore structure evolution of Qingshankou shale (kerogen type I) during artificial maturation via hydrous and anhydrous pyrolysis: Experimental study and intelligent …

B Liu, MR Mohammadi, Z Ma, L Bai, L Wang, Y Xu… - Energy, 2023 - Elsevier
In this study, alterations in the pore structure of the Qingshankou shale during hydrous and
anhydrous pyrolysis (HP and AHP) over wide ranges of temperature (300–450° C) were …

Modeling interfacial tension of surfactant–hydrocarbon systems using robust tree-based machine learning algorithms

A Rashidi-Khaniabadi, E Rashidi-Khaniabadi… - Scientific Reports, 2023 - nature.com
Interfacial tension (IFT) between surfactants and hydrocarbon is one of the important
parameters in petroleum engineering to have a successful enhanced oil recovery (EOR) …

Prediction of hydrogen solubility in aqueous solutions: Comparison of equations of state and advanced machine learning-metaheuristic approaches

S Ansari, M Safaei-Farouji, S Atashrouz, A Abedi… - International Journal of …, 2022 - Elsevier
Hydrogen is the primary carrier of renewable energy stored underground. Understanding
the solubility of hydrogen in water is critical for subsurface storage. Accurately measuring the …

Modelling CO2 diffusion coefficient in heavy crude oils and bitumen using extreme gradient boosting and Gaussian process regression

Q Lv, A Rashidi-Khaniabadi, R Zheng, T Zhou… - Energy, 2023 - Elsevier
In this work, five machine learning models based on Gaussian process regression (GPR)
and Extreme gradient boosting (XGBoost) were developed for estimating the diffusion …

Modeling the solubility of light hydrocarbon gases and their mixture in brine with machine learning and equations of state

MR Mohammadi, F Hadavimoghaddam, S Atashrouz… - Scientific reports, 2022 - nature.com
Abstract Knowledge of the solubilities of hydrocarbon components of natural gas in pure
water and aqueous electrolyte solutions is important in terms of engineering designs and …

Experimental measurement and modeling of asphaltene adsorption onto iron oxide and lime nanoparticles in the presence and absence of water

S Ansari, MR Mohammadi, H Bahmaninia… - Scientific Reports, 2023 - nature.com
Asphaltene precipitation and its adsorption on different surfaces are challenging topics in
the upstream and downstream of the oil industries and the environment. In this research, the …

[HTML][HTML] Hydrogen solubility in different chemicals: A modelling approach and review of literature data

P Foroughizadeh, A Shokrollahi, A Tatar… - … Applications of Artificial …, 2024 - Elsevier
Hydrogen (H 2) solubility is a crucial parameter for industrial processes. This study utilises
various Machine Learning (ML) techniques, including Decision Tree (DT), Multilayer …

Data-driven modeling of H2 solubility in hydrocarbons using white-box approaches

F Hadavimoghaddam, MR Mohammadi… - International Journal of …, 2022 - Elsevier
As a result of technological advancements, reliable calculation of hydrogen (H 2) solubility in
diverse hydrocarbons is now required for the design and efficient operation of processes in …

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 …

Toward predicting thermal conductivity of hybrid nanofluids: Application of a committee of robust neural networks, theoretical, and empirical models

H Ghadery-Fahliyany, S Ansari, MR Mohammadi… - Powder Technology, 2024 - Elsevier
In this work, three optimized intelligent models on the basis of multilayer perceptron (MLP),
two radial basis function (RBF) models (including RBF-particle swarm optimization (PSO) …