RESUMO
The d-band center of a catalyst can be applied for the prediction of its catalytic activity, but the application of d-band theory for the electrocatalytic nitrogen reduction reaction (eNRR) has rarely been studied in perovskite materials. In this work, a series of double-perovskite LaCoxNi1-xO3 (LCNO) nanorods (NRs) were synthesized as models, where the d-band centers can be modulated by changing the stoichiometric ratios between Co and Ni elements. Experimentally, the LCNO-III NRs (x = 0.5) attained the highest faradic efficiency and NH3 yield rate among various LCNO NRs. This result matches well with the finding from theoretical calculations that LCNO-III has the most positive d-band center (εd = -0.96 eV vs Fermi level), thus confirming that LCNO-III shows the strongest adsorption ability for N2 molecules (adsorption energy value of -2.01 eV) for the subsequent N2 activation and reduction reactions. Therefore, this work proposes a general rule to adopt for developing novel catalysts (especially perovskite-based catalysts) for substantially increasing the eNRR activity by modulating the corresponding d-band centers.
RESUMO
Metal clusters confined inside zeolite materials display remarkable luminescent properties, making them very suitable as potential alternative phosphors in white LED applications. However, up to date, only single-color emitters have been reported for luminescent metal-exchanged zeolites. In this study, we synthesized and characterized white emitting silver-sulfur zeolites, which show a remarkable color tunability upon the incorporation of silver species in highly luminescent sulfur-zeolites. Via a combined steady-state and time-resolved photoluminescence spectroscopy characterization, we suggest that the observed luminescence and tunability arise from the presence of two different species. The first associated to an orange-red emitting silver cluster (Ag-CL), whereas the second is related to a blue-white emitting S-Ag-species. The relative contribution of both luminescent species depends on the synthesis procedure. It was shown that the formation of the blue-white emitting S-Ag-species is favored upon a heat-treatment of the samples.
RESUMO
This paper describes a model suitable for forecasting the use of publicly funded long-term elderly care, taking into account both ageing and changes in the health status of the population. In addition, the impact of socioeconomic factors on care use is included in the forecasts. The model is also suitable for the simulation of possible implications of some specific policy measures. The model is a static micro-simulation model, consisting of an explanatory model and a population model. The explanatory model statistically relates care use to individual characteristics. The population model mimics the composition of the population at future points in time. The forecasts of care use are driven by changes in the composition of the population in terms of relevant characteristics instead of dynamics at the individual level. The results show that a further 37 % increase in the use of elderly care (from 7 to 9 % of the Dutch 30-plus population) between 2008 and 2030 can be expected due to a further ageing of the population. However, the use of care is expected to increase less than if it were based on the increasing number of elderly only (+70 %), due to decreasing disability levels and increasing levels of education. As an application of the model, we simulated the effects of restricting access to residential care to elderly people with severe physical disabilities. The result was a lower growth of residential care use (32 % instead of 57 %), but a somewhat faster growth in the use of home care (35 % instead of 32 %).
