Mass of 101Sn and Bayesian extrapolations to the proton drip line

Ireland, C. M.; Bollen, G.; Campbell, S. E.; Chen, X.; Erington, H.; Gamage, N. D.; Godbey, K.; Houff, A. M.; Izzo, C.; Knight, B.; Lalit, S.; Leistenschneider, E.; Lykiardopoulou, E. M.; Maier, F. M.; Nazarewicz, W.; Orford, R.; Porter, W. S.; Quick, C.; Ravlić, A.; Redshaw, M.; Reinhard, P. -G.; Ringle, R.; Schwarz, S.; Sumithrarachchi, C. S.; Valverde, A. A.; Villari, A. C. C.

doi:10.1103/vck7-1c4t

Mass of ¹⁰¹Sn and Bayesian extrapolations to the proton drip line

Journal Article · Tue Feb 17 00:00:00 EST 2026 · Physical Review. C

DOI:https://doi.org/10.1103/vck7-1c4t· OSTI ID:3018617

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Michigan State University, East Lansing, MI (United States)
University of Notre Dame, IN (United States)
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Michigan State University, East Lansing, MI (United States); University of Zagreb (Croatia)
Michigan State University, East Lansing, MI (United States); Central Michigan University, Mount Pleasant, MI (United States)
Universität Erlangen (Germany)
Argonne National Laboratory (ANL), Argonne, IL (United States)

The favorable energy configurations of nuclei at magic numbers of 𝑁 neutrons and 𝑍 protons are fundamental for understanding the evolution of nuclear structure. The 𝑍 = 50 (tin) isotopic chain is a frontier for such studies, with particular interest at and around the doubly magic ¹⁰⁰Sn isotope, for which the mass is a topic of debate. Precise mass values for neutron-deficient isotopes provide necessary anchor points for mass models to test extrapolations near the proton drip line, where experimental studies remain out of reach. In this work, we report a Penning trap mass measurement of ¹⁰¹Sn . The determined mass excess of −59889.89⁢(96) keV for ¹⁰¹Sn represents a factor-of-300 improvement over the current precision and indicates that ¹⁰¹Sn is less bound than previously thought. Mass predictions from a recently developed Bayesian model combination framework employing statistical machine learning and nuclear masses computed within seven global models based on nuclear density functional theory agree within 1⁢𝜎 with experimental masses from the 48 ≤ 𝑍 ≤ 52 isotopic chains. The framework's resilience to new mass data gave confidence in the extrapolation of tin masses down to 𝑁 = 46. Our calculations suggest that ⁹⁶Sn is a two-proton drip line nucleus and predict a mass excess of −58090⁢(800) keV for ¹⁰⁰Sn , showing a preference within 1⁢𝜎 for the mass of ¹⁰⁰Sn derived from the 𝛽-delayed 𝑄 value measured at GSI.

View Accepted Manuscript (DOE)

Research Organization:: Michigan State University; Michigan State University, East Lansing, MI (United States)

Sponsoring Organization:: U.S. National Science Foundation; USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF); USDOE Office of Science (SC), High Energy Physics (HEP); USDOE Office of Science (SC), Nuclear Physics (NP)

Grant/Contract Number:: AC02-05CH11231; AC02-06CH11357; NA0003960; NA0004074; SC0013365; SC0018362; SC0022538; SC0023175; SC0023633; SC0023688

Other Award/Contract Number:: PHY-2111185
PHY-2310059

OSTI ID:: 3018617

Alternate ID(s):: OSTI ID: 3015603
OSTI ID: 3029799

Journal Information:: Physical Review. C, Journal Name: Physical Review. C Journal Issue: 2 Vol. 113; ISSN 2469-9985; ISSN 2469-9993

Publisher:: American Physical Society (APS)Copyright Statement

Country of Publication:: United States

Language:: English

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