New isotopic data from presolar SiC grains are best reproduced by hydrodynamic models of CO novae, establishing them as the primary source for 1-2% of such grains.
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DustNET is proposed as a shared dataset to train machine learning models that complement traditional physics equations for predictive modeling of dusty plasmas across laboratory and natural scales.
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New NanoSIMS Multielement Isotope Data Reveal CO Novae As Key Sources Of 13C-rich Presolar Silicon Carbide Grains
New isotopic data from presolar SiC grains are best reproduced by hydrodynamic models of CO novae, establishing them as the primary source for 1-2% of such grains.
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DustNET: enabling machine learning and AI models of dusty plasmas
DustNET is proposed as a shared dataset to train machine learning models that complement traditional physics equations for predictive modeling of dusty plasmas across laboratory and natural scales.