Lake carbon dioxide (CO) evasion is a crucial component of global carbon cycle, yet the influence of environmental factors on CO emissions within different hydrological connectivity remains uncertain. Based on multiple machine learning methods, we in...
Carbon capture and storage (CCS) is a crucial technology for reducing industrial CO emissions and mitigating climate change. However, its large-scale deployment faces significant financial challenges, with CO capture and compression accounting for th...
This study develops and evaluates advanced hybrid machine learning models-ADA-ARD (AdaBoost on ARD Regression), ADA-BRR (AdaBoost on Bayesian Ridge Regression), and ADA-GPR (AdaBoost on Gaussian Process Regression)-optimized via the Black Widow Optim...
Greenhouse gas emissions and water quality decline are two major issues currently affecting lakes worldwide. Determining how to control both greenhouse gas emissions and water quality decline is a long-term challenge. We compiled data on the annual a...
Artificial Intelligence (AI) is applied in this research for the analysis of a novel green method for production of nanomedicine. The method is based on supercritical solvent for production of drug nanoparticles in which the AI was used to estimate t...
Journal of molecular graphics & modelling
Apr 26, 2025
Ionic liquids (ILs) have gained attention in recent times as potentially effective absorbents for CO emissions owing to the number of their notable attributes, including reduced volatility, enhanced thermal consistency etc. Due to the number of chall...
As the challenge of climate change continues to grow, we need creative solutions to predict better and track industrial waste carbon emissions, focusing on sustainable waste management practices. The present study proposes a state-of-the-art Metavers...
Journal of chemical information and modeling
Apr 15, 2025
Accurate solubility prediction in supercritical carbon dioxide (scCO) is crucial for optimizing experimental design by eliminating unnecessary and costly trials at an early stage, thereby streamlining the workflow. A comprehensive solubility database...
Environmental science and pollution research international
Apr 15, 2025
This study presents the modeling and simulation of carbon dioxide (CO₂) absorption in hybrid amine solutions using machine learning algorithms and response surface methodology (RSM). The process was governed by adjustable input parameters, including ...
Global warming is one of the most pressing and critical problems facing the world today. It is mainly caused by the increase in greenhouse gases in the atmosphere, such as carbon dioxide (CO). Understanding how soils respond to rising temperatures is...
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