Probing the Structural and Electronic Properties of the Anionic and Neutral Tellurium-Doped Boron Clusters TeBnq (n = 3-16, q = 0, -1).

In this study, we employ density functional theory along with the artificial bee colony algorithm for cluster global optimization to explore the low-lying structures of TeBnq (n = 3-16, q = 0, -1). The primary focus is on reporting the structural properties of these clusters. The results reveal a consistent doping pattern of the tellurium atom onto the in-plane edges of planar or quasi-planar boron clusters in the most energetically stable isomers. Additionally, we simulate the photoelectron spectra of the cluster anions. Through relative stability analysis, we identify three clusters with magic numbers -TeB7-, TeB10, and TeB12. The aromaticity of these clusters is elucidated using adaptive natural density partitioning (AdNDP) and magnetic properties analysis. Notably, TeB7- exhibits a perfect σ-π doubly aromatic structure, while TeB12 demonstrates strong island aromaticity. These findings significantly contribute to our understanding of the structural and electronic properties of these clusters.

Exploring the stability and aromaticity of rare earth doped tin cluster MSn16- (M = Sc, Y, La).

Rare earth elements have high chemical reactivity, and doping them into semiconductor clusters can induce novel physicochemical properties. The study of the physicochemical mechanisms of interactions between rare earth and tin atoms will enhance our understanding of rare earth functional materials from a microscopic perspective. Hence, the structure, electronic characteristics, stability, and aromaticity of endohedral cages MSn16- (M = Sc, Y, La) have been investigated using a combination of the hybrid PBE0 functional, stochastic kicking, and artificial bee colony global search technology. By comparing the simulated results with experimental photoelectron spectra, it is determined that the most stable structure of these clusters is the Frank-Kasper polyhedron. The doping of atoms has a minimal influence on density of states of the pure tin system, except for causing a widening of the energy gap. Various methods such as ab initio molecular dynamics simulations, the spherical jellium model, adaptive natural density partitioning, localized orbital locator, and electron density difference are employed to analyze the stability of these clusters. The aromaticity of the clusters is examined using iso-chemical shielding surfaces and the gauge-including magnetically induced currents. This study demonstrates that the stability and aromaticity of a tin cage can be systematically adjusted through doping.

Aromatic and magnetic properties in a series of heavy rare earth-doped Ge6 cluster anions.

A series of pentagonal bipyramidal anionic germanium clusters doped with heavy rare earth elements, REGe 6 - (RE = Gd, Tb, Dy, Ho, Er, Tm, Yb, and Lu), have been identified at the PBE0/def2-TZVP level using density functional theory (DFT). Our findings reveal that the centrally doped pentagonal ring structure demonstrates enhanced stability and heightened aromaticity due to its uniform bonding characteristics and a larger charge transfer region. Through natural population analysis and spin density diagrams, we observed a monotonic decrease in the magnetic moment from Gd to Yb. This is attributed to the decreasing number of unpaired electrons in the 4f orbitals of the heavy rare earth atoms. Interestingly, the system doped with Er atoms showed lower stability and anti-aromaticity, likely due to the involvement of the 4f orbitals in bonding. Conversely, the systems doped with Gd and Tb atoms stood out for their high magnetism and stability, making them potential building blocks for rare earth-doped semiconductor materials.

Making Sense of the Growth Behavior of Ultra-High Magnetic Gd2-Doped Silicon Clusters.

The growth behavior, stability, electronic and magnetic properties of the Gd2Sin- (n = 3-12) clusters are reported, which are investigated using density functional theory calculations combined with the Saunders 'Kick' and the Artificial Bee Colony algorithm. The lowest-lying structures of Gd2Sin- (n = 3-12) are all exohedral structures with two Gd atoms face-capping the Sin frameworks. Results show that the pentagonal bipyramid (PB) shape is the basic framework for the nascent growth process of the present clusters, and forming the PB structure begins with n = 5. The Gd2Si5- is the potential magic cluster due to significantly higher average binding energies and second order difference energies, which can also be further verified by localized orbital locator and adaptive natural density partitioning methods. Moreover, the localized f-electron can be observed by natural atomic orbital analysis, implying that these electrons are not affected by the pure silicon atoms and scarcely participate in bonding. Hence, the implantation of these elements into a silicon substrate could present a potential alternative strategy for designing and synthesizing rare earth magnetic silicon-based materials.

A bidirectional association between internet addiction and depression: A large-sample longitudinal study among Chinese university students.

BACKGROUND: Internet addiction (IA) is associated with adverse consequences, especially for younger people. Evidence indicates that IA is associated with depression, but no studies have yet investigated potential common vulnerability between them. METHODS: IA (measured by the Young's 20-item Internet Addiction Test Scale) and depressive symptoms (measured by the Patient Health Questionnaire-9 Scale) among 12 043 undergraduates were surveyed at baseline and at a respective 12 month follow-up for each participant. Application of a cross-lagged panel model approach (CLPM) revealed an association between IA and depression after adjusting for demographic variables. RESULTS: Rates of baseline IA and depression were 5.47% (95% CI: 5.07%, 5.88%) and 3.85% (95% CI: 3.51%, 4.20%), respectively; increasing to 9.47% (95% CI: 8.94%, 9.99%) and 5.58% (95% CI: 5.17%,5.99%), respectively, at follow-up. Rates of new-incidences of IA and depression over 12 months were 7.43% (95% CI: 6.95%, 7.91%) and 4.47% (95% CI: 4.09%, 4.84%), respectively. Models in the present analysis revealed that baseline depression had a significant net-predictive effect on follow-up IA, and baseline IA had a significant net-predictive effect on follow-up depression. LIMITATIONS: The follow-up survey response rate was moderate (54.69%) in this analysis of university students. Moreover, the IAT-20 scale did not allow differentiate between specific forms of Internet activity. CONCLUSIONS: Common vulnerability and bidirectional cross-causal effects may both contribute to the association between IA and depression, with common vulnerability likely playing a more significant role than cross-causal effects.