Discovery: AI models predict fission modes and half-lives of superheavy nuclei with unprecedented accuracy

Newswise – A learning Published in the journal Nuclear Science and TechnologyResearchers at Sun Yat-sen University have made a significant breakthrough in understanding the decay processes of superheavy nuclei. Their pioneering research, using a random forest machine learning algorithm, offers new insights into the decay modes and half-lives of elements beyond oganesson (element 118).

In this pioneering study, the team focused on nuclei with a proton number (Z) of 84 or greater and a neutron number (N) of 128 or greater, using semi-empirical formulas to calculate the partial half-lives for various decay modes such as alpha decay, beta-minus decay, beta- plus decay, electron capture and spontaneous decay (SF). The accuracy of these calculations was greatly improved by using the Random Forest algorithm, an advanced machine learning technique that combines different nuclear properties and decay energies. This methodology led to groundbreaking discoveries in nuclear physics, notably the dominance of alpha decay in neutron-deficient regions and beta-minus decay in neutron-rich regions. The accuracy of the algorithm was remarkable, correctly predicting the dominant decay mode in 96.9% of the cores studied, and also revealed the presence of a long spontaneous decay island to the southwest of element 298 Fl (Flerovium), highlighting the complex relationship between the decay barrier. and Coulomb repulsion in superheavy elements.

This research marks a significant leap forward in understanding superheavy nuclei, particularly in predicting their decay modes. The insights gained are crucial for investigating new elements and the elusive “island of stability” in the superheavy region. The study also highlights the importance of more accurate measurements of nuclear mass and fission energy to refine predictions. The team proposed several isotopes for future measurements that will help advance nuclear research, especially at new facilities such as CAFE2 and SHANS2 in Lanzhou.

In summary, the innovative use of the random forest algorithm has opened a new door in nuclear physics, offering a more accurate and comprehensive understanding of the decay processes of superheavy nuclei and paving the way for future discoveries in this exciting field.





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Funding information

This work was supported by the Guangdong Major Project of Basic and Applied Basic Research (2021B0301030006).

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Nuclear Science and Technology (NST) reports scientific findings, technical advances and important results in the fields of nuclear science and technology. The purpose of this periodical is to stimulate the cross-fertilization of knowledge among scientists and engineers working in the fields of nuclear research.