Rechargeable Li-SnO2 batteries suffer from issues such as poor electronic/ionic conductivity and huge volume changes. In order to overcome these inherent limitations, this study designed a cell with a unique hierarchical structure, denoted as SnO2@PCNF. The SnO2@PCNF cell design incorporates in-situ generated SnO2 nanoparticles strategically positioned within N-doped porous carbon nanofibers (PCNF). The in-situ generated SnO2 nanoparticles can alleviate strains during cycling and shorten the pathway for the ions and electrons, improving the utilization of active materials. Moreover, the N-doped PCNF establishes a continuously conductive network to further increase the electrical conductivity and also buffers the significant volume changes that occur during charging and discharging. The resulting SnO2@PCNF cell exhibits outstanding electrochemical performance and stable cycling characteristics. Notably, a reversible capacity of 520 mAh g-1 was achieved after 100 cycles at 70 mA g-1. Even under a higher current density of 1 A g-1, the cell maintained a capacity retention of 393 mAh g-1 after 1,000 cycles. These results highlight the SnO2@PCNF cell’s exceptional cycling stability and superior rate capability.

Lithium-ion batteries (LIBs) have attracted significant attention as potential energy storage solutions due to their high energy density, minimal self-discharge, extended cycle life, and absence of memory effects. However, conventional LIBs use graphite as the anode material and as a result struggle to meet the increasing demand for higher energy density because of the low theoretical capacity of graphite. In order to enhance Li storage capacity and address the current limitations of LIBs, this study designed and analyzed SnO2 nanoflakes/CNF, which is an advanced anode material with a unique hierarchical structure synthesized via a facile method involving incipient wetness followed by annealing. The in-situ formed SnO2 nanoflakes improve the electrolyte accessibility and shorten the ion and electron transport pathways, thereby enhancing the reaction kinetics. Additionally, the CNF matrix enhances the electrical conductivity, accelerates electron transport, and mitigates volume changes. The integrated SnO2 nanoflakes/CNF cell demonstrated outstanding cycling performance and excellent rate capability, achieving a notable reversible capacity of 636 mAh g-1 after 100 cycles at 0.1 C. This study provides valuable insights into the design of high-efficiency anode materials for the advancement of high- performance LIBs.

Since the Paris Agreement and the surge in global interest in climate change, the importance of measuring and managing national-level resource productivity has steadily grown. However, concerns about the reliability of productivity indicators persist due to inherent uncertainties. This study estimated the metal and non-metal resource productivities of 38 OECD countries through multiple regression analysis and conducted a comparative analysis of their ranking changes according to their current resource productivities. The study results revealed that the 38 OECD countries could be classified into four categories. First, countries with low overall resource productivities due to a high economic dependence on low-value metal resources by weight exhibited a substantial rise in their non-metal resource productivity rankings. Second, countries that have minimal metal industries in their national economies but generate high value-added from these sectors showed a notable increase in their metal resource productivity rankings. Third, countries with a low proportion of metal industry in their economies and low metal resource productivities experienced significant declines in their metal resource productivity rankings. Fourth, countries with a small disparity between their metal and non-metal resource productivities showed minimal changes in their rankings for both categories. These results highlight that changes in metal resource productivity rankings were more pronounced than those for non-metal resources, which implies that the influence of non-metal resources (biomass, fossil fuels, non-metallic minerals) dominates national-level resource productivity because their economic value is higher than metal resources. These findings suggest that it is necessary to manage the economic value of each resource type as distinct statistical data to provide a more nuanced understanding of national resource productivity.