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Hydrated electrons are anionic species that are formed when an excess electron is introduced into liquid water. Building an understanding of how hydrated electrons behave in solution has been a long-standing effort of simulation methods, of which density functional theory (DFT) has come to the fore in recent years. The ability of DFT to model the reactive chemistry of hydrated electrons is an attractive advantage over semi-classical methodologies; however, relatively few density functional approximations (DFAs) have been used for the hydrated electron simulations presented in the literature. Here, we simulate hydrated electron systems using a series of exchange–correlation (XC) functionals spanning Jacob’s ladder. We calculate a variety of experimental and other observables of the hydrated electron and compare the XC functional dependence for each quantity. We find that the formation of a stable localized hydrated electron is not necessarily limited to hybrid XC functionals and that some hybrid functionals produce delocalized hydrated electrons or electrons that react with the surrounding water at an unphysically fast rate. We further characterize how different DFAs impact the solvent structure and predicted spectroscopy of the hydrated electron, considering several methods for calculating the hydrated electron’s absorption spectrum for the best comparison between structures generated using different density functionals. None of the dozen or so DFAs that we investigated are able to correctly predict the hydrated electron’s spectroscopy, vertical detachment energy, or molar solvation volume. 

The STEM Scholars program at Bucknell University was originally supported with a five-year National Science Foundation STEP grant to begin recruitment for a summer program in 2014. The grant, with a one-year no-cost extension, supported six cohorts of students. The recruitment of participants was specifically designed to attract typically underrepresented populations into STEM (Pell eligible, first generation, students of color, female identifying). As a result of successful implementation as measured by retention, persistence, and graduation rates, the university has secured private donations from generous alumni to endow the program. The tenth cohort of scholars participated in the summer of 2024. 

In nowadays biomedical research, there has been a growing demand for making accurate prediction at subject levels. In many of these situations, data are collected as longitudinal curves and display distinct individual characteristics. Thus, prediction mechanisms accommodated with functional mixed effects models (FMEM) are useful. In this paper, we developed a classified functional mixed model prediction (CFMMP) method, which adapts classified mixed model prediction (CMMP) to the framework of FMEM. Performance of CFMMP against functional regression prediction based on simulation studies and the consistency property of CFMMP estimators are explored. Real‐world applications of CFMMP are illustrated using real world examples including data from the hormone research menstrual cycles and the diffusion tensor imaging. 

This article proposes a matrix auto-transformer switched-capacitor dc–dc converter to achieve a high voltage conversion ratio, high efficiency, and high power density for 48-V data-center applications. On the high-voltage side, the proposed converter can fully leverage the benefits of high-performance low voltage stress devices similar to the multilevel modular switched-capacitor converter. Compared with the traditional isolated LLC converter with a matrix transformer, the proposed solution utilized a matrix autotransformer concept with merged primary and secondary side windings, thus leading to reduced transformer winding loss. The resonant inductor could be integrated into the transformer similar to the LLC converter. Because of the matrix autotransformer design, it can achieve a current doubler rectifier on the low voltage side. For less than 8-V low output voltage application, the current doubler rectifier design can fully utilize the best figure-of-merit 25-V device, which is more efficient than the full-bridge rectifier solution using two 25-V devices during the operation. All the devices can achieve zero voltage switching or zero current switching and can be naturally clamped without additional clamping circuits. A 500-W 48-V to 6-V dc–dc converter hardware prototype has been developed with optimized device selection and integrated matrix autotransformer design. Both simulation and experiment results have been provided to validate the features and benefits of the proposed converter. The maximum efficiency of the proposed converter can reach 98.33%. 

Abstract Urban vegetation experiences multiple natural and human impacts during urbanization, including land conversion, local environmental factors, and human management, which may bring positive or negative impacts on vegetation gross primary productivity (GPP) at multiple scales. In this study, we analyzed the spatial-temporal changes of GPP and three urbanization factors: land urbanization (impervious surface coverage), population urbanization (Population), and economic urbanization Gross domestic product (GDP) at city-district-grid scales in Beijing during 2000–2018. Overall, both GPP and three urbanization factors showed an increased trend. The relationships between GPP and urbanization factors exhibit diverse characteristics at multiple scales: unlike the linear relationship observed at city scale, the relationships at district and grid scales all demonstrated nonlinear relationship, even a U shape between GPP and population/GDP. Furthermore, the positive impact of urbanization on GPP increased and offset the negative impact of land conversion from 9.9% in 2000 to 35% in 2018, indicating that urban management and climate during urbanization effectively promote vegetation photosynthesis and neutralize the negative impact of urban area expansion. Our findings highlight the increased growth offset by urbanization on vegetation and the importance of analysis at a finer scale. Understanding these urbanization types’ impact on vegetation is pivotal in formulating comprehensive strategies that foster sustainable urban development and preserve ecological balance.