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Photodissociation and Theory to Investigate Uranium Oxide Cluster Cations.
The Journal of Physical Chemistry A ( IF 2.9 ) Pub Date : 2020-03-03 , DOI: 10.1021/acs.jpca.0c00453
Joshua H Marks 1 , Paula Kahn 2 , Monica Vasiliu 2 , David A Dixon 2 , Michael A Duncan 1
Affiliation  

Uranium oxide cluster cations of the form UnOm+ are produced by laser vaporization of a depleted uranium rod in a pulsed supersonic expansion. Ions are mass-analyzed and mass-selected with a time-of-flight spectrometer and studied with UV laser multiphoton dissociation. Cations of the stoichiometry UO2(UO3)n+ were observed as photofragments from all photodissociated cluster cations. (UO3)n+ clusters were also observed to result from dissociation of larger (UO3)n+ clusters, with UO3 neutral as a common leaving group. Electronic structure calculations were used to investigate the stability of the prominent uranium oxide cluster cations using density functional theory (DFT) with the hybrid B3LYP exchange-correlation functional and at the CCSD(T) level with cc-pVnZ-PP basis sets (n = D,T), including diffuse orbitals as computational expense and availability permitted. Clustering energies, relative energies and dissociation energies of the cations are reported. The lowest energy neutral (UO3)n clusters up to n = 3 are rings, n = 4 and 5 are chains with very low energy rings, and n = 6 is 3D. The lowest energy structures for UO2(UO3)n+ are composed of uranyl-like UO2+ units bound by bridging oxygens to other UO22+ units for n = 2 and 3, and for n = 4 a more complex 3D structure is predicted.

中文翻译:

用光解离和理论研究铀氧化物簇阳离子。

UnOm +形式的氧化铀簇阳离子是通过在脉冲超音速膨胀下对贫化的铀棒进行激光蒸发而产生的。使用飞行时间光谱仪对离子进行质量分析和质量选择,并通过UV激光多光子解离研究离子。从所有光解离的簇状阳离子中观察到的化学计量为UO2(UO3)n +的阳离子为光碎片。还观察到(UO3)n +团簇是由较大的(UO3)n +团簇解离产生的,其中UO3中性是常见的离去基团。电子结构计算使用密度泛函理论(DFT)和混合B3LYP交换相关函数,并在CCSD(T)级别使用cc-pVnZ-PP基集来研究突出的铀氧化物簇阳离子的稳定性(n = D,T),包括漫射轨道,作为计算费用和允许的可用性。报道了阳离子的聚集能,相对能和离解能。直到n = 3的最低能量中性(UO3)n簇是环,n = 4和5是具有非常低能量环的链,n = 6是3D。UO2(UO3)n +的最低能级结构由类似铀酰的UO2 +单元组成,这些单元通过将氧桥接到其他UO22 +单元上而形成n = 2和3,并且对于n = 4,可以预测更复杂的3D结构。
更新日期:2020-03-03
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