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    ChatGPT in Early Childhood Science Education: Can It Offer Innovative Effective Solutions to Overcome Challenges?
    (Mdpi, 2025) Ugras, Mustafa; Cakir, Zehra; Zacharis, Georgios; Kalogiannakis, Michail
    This study explores the potential of ChatGPT to address challenges in Early Childhood Science Education (ECSE) from the perspective of educators. A qualitative case study was conducted with 33 Early Childhood Education (ECE) teachers in T & uuml;rkiye, using semi-structured interviews. Data were analyzed through content analysis with MAXQDA 24 software. The results indicate that ECE teachers perceive ChatGPT as a partial solution to the scarcity of educational resources, appreciating its ability to propose alternative material uses and creative activity ideas. Participants also recognized its potential to support differentiated instruction by suggesting activities tailored to children's developmental needs. Furthermore, ChatGPT was seen as a useful tool for generating lesson plans and activity options, although concerns were expressed that overreliance on the tool might undermine teachers' pedagogical skills. Additional limitations highlighted include dependence on technology, restricted access to digital tools, diminished interpersonal interactions, risks of misinformation, and ethical concerns. Overall, while educators acknowledged ChatGPT's usefulness in supporting ECSE, they emphasized that its integration into teaching practice should be cautious and balanced, considering both its educational benefits and its limitations.
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    DFT-based structural and energetic characterisation of nitrogen-rich tetrazine/triazine derivatives with Kamlet-Jacobs performance predictions
    (Taylor & Francis Ltd, 2026) Ekincioglu, Yavuz; Kepceoglu, Abdullah; Cakir, Zehra; Senturk, Sukru
    Nitrogen-rich heterocycles are attractive candidates for next-generation energetic materials because they can deliver high heats of formation while producing relatively benign, N2-rich decomposition products. In this work, three nitrogen-rich frameworks 3,6-bis(tetrazol-5-yl)-1,2,4,5-tetrazine (H2BTTz), 2,4,6-tris(tetrazol-5-yl)-1,3,5-triazine (H3TTT), and 2,3,5,6-tetra(tetrazol-5-yl)pyrazine (H4TTP) were investigated using a combined conformational sampling and density functional theory (DFT) approach. Initial conformational searches were carried out with the MMFF method, and the lowest-energy structures were optimised at the DFT/B3LYP/6-311++G(d,p) level a widely used compromise between accuracy and computational cost for nitrogen-rich energetic molecules. Electronic structure analyses included frontier molecular orbitals, Mulliken and natural population charges, and molecular electrostatic potential maps. Energetic performance was evaluated through heats of formation, detonation velocity and pressure, and impact sensitivity estimates. Topological descriptors such as ELF, LOL, and NCI were analyzed using Multiwfn program. The calculated HOMO - LUMO gaps (3.54-4.90 eV) indicate electronically stable molecular frameworks. Gas-phase formation enthalpies were converted to condensed-phase values using a sublimation correction, and detonation properties were estimated via the Kamlet-Jacobs equations. The predicted performance follows the order H4TTP > H(2)BTTz > H3TTT. Although their detonation performance is lower than that of FOX-7 and CL-20, these nitrogen-rich systems remain promising candidates for reduced-sensitivity energetic materials and merit further experimental investigation.