Article title: Multiple-models predictions for drip line nuclides in projectile fragmentation of ^40,48Ca, ^58,64Ni, and ^78,86Kr at 140 MeV/u   

文章题目：^40,48Ca, ^58,64Ni和^78,86Kr在140 MeV/u炮弹碎裂中滴线核素的多模型预测   

DOI: 10.1007/s41365-022-01137-4

One sentence summary:

一句话概要：

By applying multiple-models predictions, this study shows how far from the β-stability line the ERI can reach within the lowest detecting limitations in the newly commissioned FRIB in Michigan State University.

通过应用多模型预测，本项研究显示了在密歇根州立大学新启动的FRIB的最低检测限制下，ERI可以达到离β稳定线多远的位置。

 The Novelty (What)

创新性（主要内容）

To pursue the exploration of drip line nuclides, this study performed multiple-models predictions to predict the cross-sections of extremely rare isotope (ERI) produced in typical projectile fragmentation (PF) reactions in the Facility for Rare Isotope Beam (FRIB), namely ^78,86Kr + ⁹Be, ^58,64Ni + ⁹Be, and ^40,48Ca + ⁹Be reactions at 140 MeV/u. The multiple-models predictions comprised the EPAX3, FRACS, Bayesian neural network technology (BNN), and BNN + FRACS models. Results showed that both neutron and proton drip lines can be reached for elements of atomic number ≤ 11 with the lowest cross-section of 10⁻¹⁵ mb. The newly created most neutron-rich ³⁹Na verifies the high precision of BNN prediction. Based on the promising results, future studies may apply the proposed methods to enhance the feasibility of creating a larger variety of ERIs in the newly commissioned FRIB factory, leading to more advanced experimental research.

为了探索滴线核素，本研究在稀有同位素束流装置(FRIB)上，采用多种模型预测方法，预测了在140MeV/u下^78,86Kr + ⁹Be，^58,64Ni + ⁹Be和^40,48Ca + ⁹Be等典型的炮弹碎裂反应中产生的极稀有同位素(ERI)的截面。 所采用的预测模型包括EPAX3、FRACS、贝叶斯神经网络(BNN)和BNN+FRACS模型。 结果表明，对于原子序数Z≤11的元素，在（实验探测）最低截面为10⁻¹⁵ mb时，中子滴线和质子滴线位置都可以达到。 新发现的中子数最多的³⁹Na验证了BNN模型具有高精度预测能力。 基于这些的结果，未来的研究可能会应用所提出的模型来研究FRIB工厂生成更多种类ERIs的可行性，从而引领更先进的实验研究。

The Background (Why)

研究背景（主要原因）

Short-life, unstable, radioactive nuclei are exotic when they develop unusual structures. In order to facilitate the advancement of research, modern rare isotope beam (RIB) factories were set up to enhance the production of extremely rare isotopes (ERI) at or near drip lines. The ERI can be produced more effectively via a higher-level understanding on the projectile fragmentation reactions. As an effort to achieve that, this study performed multi-models predictions of cross-sections for ERIs in typical reactions using EPAX3, FRACS, BNN, and BNN + FRACS models, of which the BNN and BNN + FRACS models were newly developed massive learning models using Bayesian Neural Networks. The output of the study confirmed the feasibility to create a significantly large number of new isotopes in FRIB, leading to a richer knowledge base for nuclear structure, nuclear reaction, and nuclear astrophysics.

短寿命、不稳定的放射性原子核可以形成非同寻常的奇异结构。 为了促进研究的进展，现代稀有同位素束(RIB)工厂的建成能够提高滴线或滴线附近极稀有同位素(ERI)的产量。 通过对炮弹碎裂反应的更高层次的理解，可以更有效地生成ERI。 为了实现这一目标，本研究采用EPAX3、FRACS、BNN和BNN+FRACS模型对典型反应中ERI核素的截面进行了多种模型预测，其中BNN和BNN+FRACS模型是利用贝叶斯神经网络新提出的大数据学习模型。 这项研究的结果证实了在FRIB中创造大量新同位素的可行性，从而为核结构、核反应和核天体物理提供了更丰富的知识基础。

The SDG impact (Big Why)

SDG影响力（研究意义）

The new rare isotope factories provide unique technology to extend the boundaries on the chart of nucleus in experiments. This study shows how far from the β-stability line the ERI can reach within the lowest detecting limitations in the newly commissioned FRIB in Michigan State University, USA. By supporting future research related to nuclear science, its output is very well-aligned with UNSDG 9: Industries, Innovation & Infrastructure.

新的稀有同位素工厂提供了独特的技术，在实验室扩展了原子核素图的边界。 这项研究表明，在美国密歇根州立大学新启动的FRIB中，在最低的实验探测限制范围内，ERI能达到离β稳定线多远的位置。 通过支持与核科学有关的未来研究，其产出与联合国可持续发展目标9：工业、创新和基础设施非常吻合。