论文标题

$^{96} $ zr($α$,n)$^{99} $ MO横截面的尺寸

Measurements of the $^{96}$Zr($α$,n)$^{99}$Mo cross section for astrophysics and applications

论文作者

Hamad, Gula, Brandenburg, Kristyn, Meisel, Zach, Brune, Carl R., Carter, Don E., Ingram, David C., Jones-Alberty, Yenuel, Massey, Thomas N., Saxena, Mansi, Soltesz, Doug, Subedi, Shiv K., Voinov, Alexander V.

论文摘要

反应$^{96} $ zr($α$,n)$^{99} $ mo在$ν$驱动的风核合成中起着重要作用,在核心 - 循环超新星中,是医疗同位素生产的可能途径。使用Edwards Accelerator实验室的激活技术进行横截面测量。分析了结果与$^{96} {\ rm zr}(α,n)$横截面和$^{96} {\ rm zr}(α,α,α)$差异横截面的$^{\ rm zr}(α,n)$ dixials cross cross cross cross cross cross cross $^{96} {\ rm zr} {\ rm zr} {\ rm zr} {\ rm zr}(α)$差异横截面,对结果进行了分析。我们比较我们的数据,以前的测量以及对反应的统计描述。与先前的实验结果相比,我们发现在低能量下的横截面更大,从而使天体物理反应率更高。这可能会影响核心溢出超新星$ν$驱动的风核合成计算的结果,但并未显着改变有关医疗物理应用的$^{99} {\ rm mo} $生产的先前结论。我们的大规模豪瑟 - 菲什巴赫计算的结果表明,现象学光学电位可能还足以描述$(α,n)$对$ν$驱动的风核合成的反应,尽管有区域调整的模型参数。

The reaction $^{96}$Zr($α$,n)$^{99}$Mo plays an important role in $ν$-driven wind nucleosynthesis in core-collapse supernovae and is a possible avenue for medical isotope production. Cross section measurements were performed using the activation technique at the Edwards Accelerator Laboratory. Results were analyzed along with world data on the $^{96}{\rm Zr}(α,n)$ cross section and $^{96}{\rm Zr}(α,α)$ differential cross section using large-scale Hauser-Feshbach calculations. We compare our data, previous measurements, and a statistical description of the reaction. We find a larger cross section at low energies compared to prior experimental results, allowing for a larger astrophysical reaction rate. This may impact results of core-collapse supernova $ν$-driven wind nucleosynthesis calculations, but does not significantly alter prior conclusions about $^{99}{\rm Mo}$ production for medical physics applications. The results from our large-scale Hauser-Feshbach calculations demonstrate that phenomenological optical potentials may yet be adequate to describe $(α,n)$ reactions of interest for $ν$-driven wind nucleosynthesis, albeit with regionally-adjusted model parameters.

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