RESUMEN
Solid-state sodium batteries represent a highly promising option for future electrochemical energy storage applications. The ionic conductivity of solid-state electrolytes is one of the significant factors limiting the development of solid-state batteries. In this study, we establish that Sm3+ doping effectively boosts the ionic conductivity of Na3Zr2Si2PO12 (NZSP). The optimal composition, Na3.2Zr1.8Sm0.2Si2-PO12 (NZSP-S20), exhibits a total conductivity of 1.87 mS cm-1 at 23 °C. Structural and microscopic morphology analyses reveal that Sm3+ doping enhances the ionic conductivity of NZSP through structural modulation, phase fraction adjustment, and grain size reduction. High-frequency impedance spectroscopy (40 Hz to 110 MHz) demonstrates that bulk and grain boundaries contribute 49.4 and 50.6%, respectively, to the total conductivity. The structural and microscopic morphology analyses reveal that Sm3+ doping enhances the ionic conductivity of NZSP. Furthermore, the critical current density (CCD) attained in the symmetric cell, assembled by using NZSP-S20 as the solid-state electrolyte and NaSn alloy as the electrode, reaches 2.2 mA cm-1. These results furnish a theoretical foundation for comprehending the modification of solid-state electrolytes.
RESUMEN
The sluggish reaction kinetics and unfavorable shuttling effect are regarded as obstacles to the practical application of lithium-sulfur (Li-S) batteries. To resolve these inherent drawbacks, we synthesized novel multifunctional Co3O4@NHCP/CNT as the cathode materials consisting of carbon nanotubes (CNTs)-grafted N-doped hollow carbon polyhedrons (NHCP) embedded with cobalt (II, III) oxide (Co3O4) nanoparticles. The results indicate that the NHCP and interconnected CNTs could provide favorable channels for electron/ion transport and physically restrict the diffusion of lithium polysulfides (LiPSs). Furthermore, N doping and in-situ Co3O4 embedding could endow the carbon matrix with strong chemisorption and effective electrocatalytic activity toward LiPSs, thus prominently promoting the sulfur redox reaction. Benefiting from these synergistic effects, the Co3O4@NHCP/CNT electrode exhibits a high initial capacity of 1322.1 mAh/g at 0.1 C, and a capacity retention of 710.4 mAh/g after 500 cycles at 1 C. Impressively, even at a relatively high current density of 4 C, the Co3O4@NHCP/CNT electrode achieves a high capacity of 653.4 mAh/g and outstanding long-term cycle stability for 1000 cycles with a low decay rate of 0.035% per cycle. Hence, the design of N-doped CNTs-grafted hollow carbon polyhedrons coupled with transition metal oxides would provide effective promising perspective for developing high-performance Li-S batteries.
RESUMEN
Fluorinated spacer cations in quasi-2D (Q-2D) perovskites have recently been demonstrated to improve the Q-2D perovskite solar cell (PSC) performance. However, the underlying mechanism of fluorination of organic cations on the improvement is still unclear. Here, using fluorinated benzylammonium (named F-BZA) as a spacer cation in Q-2D Ruddlesden-Popper (RP) perovskites, we deeply investigate the effect of fluorination of organic cations on perovskite crystallization and intermolecular interactions for improving the charge transport and device performance. It is found that fluorination of spacer cations can slow down the crystallization rate of perovskites, resulting in vertically aligned large grains. Moreover, the interaction between the adjacent spacer cations is further enhanced, constructing a new faster charge-transport channel with a lifetime of 77 ps. Accordingly, the carrier mobility is improved by an order of magnitude and a power conversion efficiency (PCE) of 16.82% is achieved in much more stable F-BZA-based Q-2D RP PSCs, 35% higher than that of BZA-based devices (12.39%). Our results elucidate the mechanism and its importance of fluorinating spacer cations for high-performance Q-2D PSC development.
RESUMEN
As a typical model-based evolutionary algorithm, estimation of distribution algorithm (EDA) possesses unique characteristics and has been widely applied in global optimization. However, the commonly used Gaussian EDA (GEDA) usually suffers from premature convergence, which severely limits its search efficiency. This paper first systematically analyzes the reasons for the deficiency of traditional GEDA, then tries to enhance its performance by exploiting the evolution direction, and finally develops a new GEDA variant named EDA2. Instead of only utilizing some good solutions produced in the current generation to estimate the Gaussian model, EDA2 preserves a certain number of high-quality solutions generated in the previous generations into an archive and employs these historical solutions to assist estimating the covariance matrix of Gaussian model. By this means, the evolution direction information hidden in the archive is naturally integrated into the estimated model, which in turn can guide EDA2 toward more promising solution regions. Moreover, the new estimation method significantly reduces the population size of EDA2 since it needs fewer individuals in the current population for model estimation. As a result, a fast convergence can be achieved. To verify the efficiency of EDA2, we tested it on a variety of benchmark functions and compared it with several state-of-the-art EAs. The experimental results demonstrate that EDA2 is efficient and competitive.