Machine learning in absorption-based post-combustion carbon capture systems: A state-of-the-art review
The enormous consumption of fossil fuels from various human activities leads to a significant
amount of anthropogenic CO 2 emission into the atmosphere, which has already massively …
amount of anthropogenic CO 2 emission into the atmosphere, which has already massively …
AI models for correlation of physical properties in system of 1DMA2P‐CO2‐H2O
In this work, the density, viscosity, and specific heat capacity of pure 1‐dimethylamino‐2‐
propanol (1DMA2P) as well as aqueous unloaded and CO2‐loaded 1DMA2P solution (with …
propanol (1DMA2P) as well as aqueous unloaded and CO2‐loaded 1DMA2P solution (with …
[HTML][HTML] Modeling and optimization of CO2 capture into mixed MEA-PZ amine solutions using machine learning based on ANN and RSM models
Carbon dioxide (CO 2) sequestration by chemical absorption is widely regarded as the most
effective method for its reduction in natural gas streams or flue gases from fossil fuel power …
effective method for its reduction in natural gas streams or flue gases from fossil fuel power …
Generic AI models for mass transfer coefficient prediction in amine-based CO2 absorber, Part I: BPNN model
Accurate and reliable prediction of mass transfer coefficient is critical to evaluate the mass
transfer performance of amine-based carbon capture process. This work aims to establish a …
transfer performance of amine-based carbon capture process. This work aims to establish a …
[HTML][HTML] Exploring artificial neural network approach and RSM modeling in the prediction of CO2 capture using carbon molecular sieves
In this work, adsorption and reduction of CO 2 by carbon molecular sieves (CMS) was
modeled using response surface methodology (RSM) and artificial neuron networks (ANNs) …
modeled using response surface methodology (RSM) and artificial neuron networks (ANNs) …
Toward smart carbon capture with machine learning
Machine learning (ML) is emerging as a powerful approach that has recently shown
potential to affect various frontiers of carbon capture, a key interim technology to assist in the …
potential to affect various frontiers of carbon capture, a key interim technology to assist in the …
The Potential of Machine Learning for Enhancing CO2 Sequestration, Storage, Transportation, and Utilization-based Processes: A Brief Perspective
In the paper, we present a review of different types of CO2 capture, storage, transportation,
and utilization (CCSTU) processes. We have also reviewed their further development by …
and utilization (CCSTU) processes. We have also reviewed their further development by …
A generic machine learning model for CO2 equilibrium solubility into blended amine solutions
In this work, three machine learning methods were employed to predict carbon dioxide (CO
2) equilibrium solubility in blended amine solutions consisting of ethanolamine (MEA), N, N …
2) equilibrium solubility in blended amine solutions consisting of ethanolamine (MEA), N, N …
Modeling of carbon dioxide absorption into aqueous alkanolamines using machine learning and response surface methodology
This research focuses on modeling CO2 absorption into alkanolamine solvents using
multilayer perceptron (MLP), radial basis function network (RBF), Support Vector Machine …
multilayer perceptron (MLP), radial basis function network (RBF), Support Vector Machine …