Review of technological progress in carbon dioxide capture, storage, and utilization
Emissions of substantial amounts of greenhouse gases (GHG) accumulating in the
atmosphere have caused climate alterations and increased global temperatures. Several …
atmosphere have caused climate alterations and increased global temperatures. Several …
Carbon dioxide storage in magmatic rocks: Review and perspectives
Emissions of greenhouse gases are contributing to climate change and causing global
mean temperatures to rise. CO 2 storage in magmatic rocks is considered a promising …
mean temperatures to rise. CO 2 storage in magmatic rocks is considered a promising …
Machine-learning models to predict hydrogen uptake of porous carbon materials from influential variables
Hydrogen (H 2) absorption percentage by porous carbon media (PCM) is important for
identifying efficient H 2 storage media. PCM with H 2-uptakes of greater than 5 wt% are …
identifying efficient H 2 storage media. PCM with H 2-uptakes of greater than 5 wt% are …
Improving predictions of shale wettability using advanced machine learning techniques and nature-inspired methods: Implications for carbon capture utilization and …
The utilization of carbon capture utilization and storage (CCUS) in unconventional
formations is a promising way for improving hydrocarbon production and combating climate …
formations is a promising way for improving hydrocarbon production and combating climate …
Modeling the thermal transport properties of hydrogen and its mixtures with greenhouse gas impurities: A data-driven machine learning approach
This study introduces machine learning (ML) algorithms to predict hydrogen (H 2)
thermodynamic properties for geological storage, focusing on its mixtures with natural gas …
thermodynamic properties for geological storage, focusing on its mixtures with natural gas …
Predicting uniaxial compressive strength from drilling variables aided by hybrid machine learning
Awareness of uniaxial compressive strength (UCS) as a key rock formation parameter for the
design and development of gas and oil field plays. It plays an essential role in the selection …
design and development of gas and oil field plays. It plays an essential role in the selection …
Combined machine-learning and optimization models for predicting carbon dioxide trap** indexes in deep geological formations
Emissions of carbon dioxide (CO 2) are a major source of atmospheric pollution contributing
to global warming. Carbon geological sequestration (CGS) in saline aquifers offers a …
to global warming. Carbon geological sequestration (CGS) in saline aquifers offers a …
Data-driven machine learning models for the prediction of hydrogen solubility in aqueous systems of varying salinity: Implications for underground hydrogen storage
Hydrogen is a clean and sustainable renewable energy source with significant potential for
use in energy storage applications because of its high energy density. In particular …
use in energy storage applications because of its high energy density. In particular …
Enhancing carbon sequestration: innovative models for wettability dynamics in CO2-brine-mineral systems
This study investigates the application of machine learning techniques—specifically
convolutional neural networks, multilayer perceptrons and cascaded forward neural …
convolutional neural networks, multilayer perceptrons and cascaded forward neural …
Carbon storage tanker lifetime assessment
O Gaidai, Q Hu, J Xu, F Wang, Y Cao - Global Challenges, 2023 - Wiley Online Library
CO2 capture and storage (CCS) is an important strategy to reduce global CO2 emissions.
This work presents both cutting‐edge carbon storage tanker design, as well as novel …
This work presents both cutting‐edge carbon storage tanker design, as well as novel …