JOURNAL ARTICLE

Decay characteristics of nuclei of interest in the synthesis of Z = 120 isotopes.

  • Published In: International Journal of Modern Physics E: Nuclear Physics, 2024, v. 33, n. 12. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Prathapan, K.; Damodaran, Lisha 3 of 3

Abstract

The alpha and cluster decay characteristics of 2 9 9 − 3 0 2 120 isotopes in the superheavy region are investigated within the Coulomb and Proximity Potential Model (CPPM) framework. The study is significant since several attempts were made during the last one and half decades for the synthesis of Z = 120 isotopes. The alpha decay half-lives are compared with the spontaneous fission half-lives estimated using the formula of Santhosh et al.1 and identified the isotopes which are stable against spontaneous fission. Possible light cluster emission from the selected isotopes and the branching ratio (BR) are also calculated. Further, heavy cluster emission probability is also studied within the framework of the empirical formula of Prathapan and Biju (PB)2 and the Modified Balasubramaniam Formula (MBF).3 We could identify many possible heavy particle emissions with decay half-lives comparable to that of the alpha decay. Experiments can be conducted for the identification of such possible emission fragments. The alpha and cluster decay half-lives are computed using the Universal Decay Law (UDL)4 and with the Modified Universal Decay Law (MUDL)5 are also presented for comparison purposes. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Modern Physics E: Nuclear Physics. 2024/12, Vol. 33, Issue 12, p1
  • Document Type:Article
  • Subject Area:Physics
  • Publication Date:2024
  • ISSN:0218-3013
  • DOI:10.1142/S0218301324500666
  • Accession Number:183581866
  • Copyright Statement:Copyright of International Journal of Modern Physics E: Nuclear Physics is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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