首页|Findings from Georgia Institute of Technology Update Knowledge of Machine Learni ng (Screening Environmentally Benign Ionic Liquids for Co2 Absorption Using Repr esentation Uncertainty-based Machine Learning)
Findings from Georgia Institute of Technology Update Knowledge of Machine Learni ng (Screening Environmentally Benign Ionic Liquids for Co2 Absorption Using Repr esentation Uncertainty-based Machine Learning)
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Current study results on Machine Learn ing have been published. According to news originating from Atlanta, Georgia, by NewsRx correspondents, research stated, "Screening ionic liquids (ILs) with low viscosity, low toxicity, and high CO2 absorption using machine learning (ML) mo dels is crucial for mitigating global warming. However, when candidate ILs fall into the extrapolation zone of ML models, predictions may become unreliable, lea ding to poor decision-making." Funders for this research include United States Department of Agriculture (USDA) , National Science Foundation (NSF), National Science Foundation-U.S. Department of Agriculture, National Natural Science Foundation of China (NSFC).
AtlantaGeorgiaUnited StatesNorth a nd Central AmericaCyborgsEmerging TechnologiesIonic LiquidsMachine Learn ingSolventsGeorgia Institute of Technology
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