Harnessing the power of machine learning for carbon capture, utilisation, and storage (CCUS)–a state-of-the-art review

Y Yan, TN Borhani, SG Subraveti, KN Pai… - Energy & …, 2021 - pubs.rsc.org
Carbon capture, utilisation and storage (CCUS) will play a critical role in future
decarbonisation efforts to meet the Paris Agreement targets and mitigate the worst effects of …

Emerging Trends in Sustainable CO2‐Management Materials

Z Zhang, Y Zheng, L Qian, D Luo, H Dou… - Advanced …, 2022 - Wiley Online Library
With the rising level of atmospheric CO2 worsening climate change, a promising global
movement toward carbon neutrality is forming. Sustainable CO2 management based on …

A review on machine learning algorithms for the ionic liquid chemical space

S Koutsoukos, F Philippi, F Malaret, T Welton - Chemical science, 2021 - pubs.rsc.org
There are thousands of papers published every year investigating the properties and
possible applications of ionic liquids. Industrial use of these exceptional fluids requires …

Challenges and opportunities in carbon capture, utilization and storage: A process systems engineering perspective

MMF Hasan, MS Zantye, MK Kazi - Computers & Chemical Engineering, 2022 - Elsevier
Carbon capture, utilization, and storage (CCUS) is a promising pathway to decarbonize
fossil-based power and industrial sectors and is a bridging technology for a sustainable …

Generic AI models for mass transfer coefficient prediction in amine‐based CO2 absorber, Part II: RBFNN and RF model

H Quan, S Dong, D Zhao, H Li, J Geng, H Liu - AIChE Journal, 2023 - Wiley Online Library
In this work, the radial basis function neural network (RBFNN) and random forest (RF)
algorithms were employed to develop generic AI models predicting mass transfer coefficient …

Application of machine learning in carbon capture and storage: An in-depth insight from the perspective of geoscience

P Yao, Z Yu, Y Zhang, T Xu - Fuel, 2023 - Elsevier
Greenhouse gas emissions cause serious global climate change, and it is urgent to curb CO
2 emissions. As the last-guaranteed technology to reduce carbon emissions, carbon capture …

Knowledge-based machine learning techniques for accurate prediction of CO2 storage performance in underground saline aquifers

HV Thanh, Q Yasin, WJ Al-Mudhafar, KK Lee - Applied Energy, 2022 - Elsevier
Carbon dioxide storage in underground saline aquifers is considered a promising technique
for decreasing atmospheric CO 2 emissions. The CO 2 residual and solubility in deep saline …

[HTML][HTML] Prediction of CO2 solubility in deep eutectic solvents using random forest model based on COSMO-RS-derived descriptors

J Wang, Z Song, L Chen, T Xu, L Deng, Z Qi - Green Chemical Engineering, 2021 - Elsevier
This work presents the development of molecular-based mathematical model for the
prediction of CO 2 solubility in deep eutectic solvents (DESs). First, a comprehensive …

Computer-aided molecular design of ionic liquids as advanced process media: a review from fundamentals to applications

Z Song, J Chen, J Cheng, G Chen, Z Qi - Chemical Reviews, 2023 - ACS Publications
The unique physicochemical properties, flexible structural tunability, and giant chemical
space of ionic liquids (ILs) provide them a great opportunity to match different target …

Prediction of CO2 solubility in Ionic liquids for CO2 capture using deep learning models

M Ali, T Sarwar, NM Mubarak, RR Karri, L Ghalib… - Scientific Reports, 2024 - nature.com
Ionic liquids (ILs) are highly effective for capturing carbon dioxide (CO2). The prediction of
CO2 solubility in ILs is crucial for optimizing CO2 capture processes. This study investigates …