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The AI gambit: leveraging artificial intelligence to combat climate change—opportunities, challenges, and recommendations
In this article, we analyse the role that artificial intelligence (AI) could play, and is playing, to
combat global climate change. We identify two crucial opportunities that AI offers in this …
combat global climate change. We identify two crucial opportunities that AI offers in this …
Harnessing the power of machine learning for carbon capture, utilisation, and storage (CCUS)–a state-of-the-art review
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 …
decarbonisation efforts to meet the Paris Agreement targets and mitigate the worst effects of …
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 …
Knowledge-based machine learning techniques for accurate prediction of CO2 storage performance in underground saline aquifers
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 …
for decreasing atmospheric CO 2 emissions. The CO 2 residual and solubility in deep saline …
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 …
[HTML][HTML] Probing Solubility and pH of CO2 in aqueous solutions: Implications for CO2 injection into oceans
E Mohammadian, F Hadavimoghaddam… - Journal of CO2 …, 2023 - Elsevier
CO 2 sequestration is among the most anticipated methods to mitigate the already
detrimental concentrations of CO 2 in the atmosphere. Among sequestration methods, CO 2 …
detrimental concentrations of CO 2 in the atmosphere. Among sequestration methods, CO 2 …
Application of machine learning techniques in environmentally benign surface grinding of Inconel 625
This work explores the grinding performance of Inconel 625 by comparing tangential forces
and surface roughness under dry, wet, and minimum quantity lubrication (MQL) …
and surface roughness under dry, wet, and minimum quantity lubrication (MQL) …
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 …
A novel hybrid machine learning model for prediction of CO2 using socio-economic and energy attributes for climate change monitoring and mitigation policies
S Kumar - Ecological informatics, 2023 - Elsevier
Industrial development has contributed to carbon emissions majorly, resulting in high
concentrations of greenhouse gases (GHGs) in the environment leading to climate change …
concentrations of greenhouse gases (GHGs) in the environment leading to climate change …
[HTML][HTML] A systematic review of machine learning approaches in carbon capture applications
Climate change and global warming are among of the most important environmental issues
and require adequate and immediate global action to preserve the planet for future …
and require adequate and immediate global action to preserve the planet for future …