AI Summary
This article discusses how scientists are using artificial intelligence algorithms to model the atomic masses of all possible protons and neutrons in the nuclide chart, aiding in the study of heavy element origins in astrophysics. The prediction of atomic masses is crucial for understanding processes like neutron star collisions that lead to the formation of new elements.
The origin of heavy elements in our universe is theorized to be the result of neutron star collisions, which produce conditions hot and dense enough for free neutrons to merge with atomic nuclei and form new elements in a split-second window of time. Testing this theory and answering other astrophysical questions requires predictions for a vast range of masses of atomic nuclei. Scientists are using machine learning algorithms to successfully model the atomic masses of the entire nuclide chart — the combination of all possible protons and neutrons that defines elements and their isotopes.