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This empirical study assessed the potential of developing a machine-learning model to identify children and adolescents with poor oral health using only self-reported survey data. Such a model could enable scalable and cost-effective screening and targeted interventions, optimizing limited resources to improve oral health outcomes. To train and test the model, we used data from 2,133 students attending schools in a Portuguese municipality.

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Size Effect on Ultrafast Dynamics of the Photoexcited Be Electron in Be@C (2 = 60, 70, and 80).

J Phys Chem Lett

January 2025

MOE Key Laboratory for Non-equilibrium Synthesis and Modulation of Condensed Matter, School of Physics, Xi'an Jiaotong University, Xi'an 710049, China.

The ultrafast excited-state dynamics of endohedral fullerenes are crucial in their photophysical and photochemical processes when they are employed as photovoltaic devices, photocatalytic devices, and single-molecule devices. In this study, by employing the non-adiabatic molecular dynamics simulations based on the time-dependent Kohn-Sham (TD-KS) method, we theoretically studied the size effect on ultrafast excited-state decay dynamics of the photoexcited Be electron in endohedral fullerenes Be@C (2 = 60, 70, and 80). These excited-state decay dynamics, which involve the charge-transfer process, occur in an ultrafast time scale of about 3 ps.

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