RESUMO
With the impetus to accelerate worldwide market adoption of electrical vehicles and afford consumer electronics with better user experience, advancing fast-charging technology is an inevitable trend. However, current high-energy lithium-ion batteries are unable to support ultrafast power input without any adverse consequences, with the capacity fade and safety concerns of the mainstream graphite-based anodes being the key technological barrier. The aim of this review is to summarise the fundamentals, challenges, and solutions to enable graphite anodes that are capable of high-rate charging. First, we explore the complicated yet intriguing graphite-electrolyte interface during intercalation based on existing theories. Second, we analyse the key dilemmas facing fast-charging graphite anodes. Finally, some promising strategies proposed during the past few years are highlighted so as to outline current trends and future perspectives in this field.
RESUMO
Fast charging enables electronic devices to be charged in a very short time, which is essential for next-generation energy storage systems. However, the increase of safety risks and low coulombic efficiency resulting from fast charging severely hamper the practical applications of this technology. This Review summarizes the challenges and recent progress of lithium batteries for fast charging. First, it describes the definition of fast charging and proposes a critical value of ionic and electrical conductivity of electrodes for fast charging in a working battery. Then based on this definition, the requirements and optimization strategies of the electrode, electrolyte, and electrode/electrolyte interface for fast charging are proposed. Finally, a general conclusion and perspectives on the better understanding of lithium batteries with fast charging capability are presented.
RESUMO
Leaf area index (LAI) is one of the most important structural parameters of terrestrial ecosystem, while the remote sensing retrieval and the ground optical instrument measurement and based on canopy gap model are the effective approaches to rapidly obtain LAI. However, these two approaches can only acquire effective LAI (LAI(e)), due to the clumping of vegetation canopy. Taking the experimental forest farm of Northeast Forestry University at Maoershan Mountain in Heilongjiang Province of Northeast China as study site, this paper measured the forest canopy LAI(e) by LAI2000, and estimated the LAI by the combination of TRAC (tracing radiation and architecture of canopies) measurement of foliage clumping index. A LAI remote sensing retrieval model was constructed through the analysis of the relationships between different vegetation indices calculated from Landsat5-TM and measured LAI(e). The results showed that at the study site, the LAI of broad leaved forests was close to the LAI(e), but the LAI of needle leaved forests was 27% larger than the LAI(e). Reduced simple ratio index (RSR) had the highest relationship with measured LAI(e) (R2 = 0.763, n = 23), which could be used as the best predictor of LAI. The LAI at study site increased rapidly with increasing elevation when the elevation was below 400 m, but had a slow increase when the elevation was from 400 m to 750 m. When the elevation was above 750 m, the LAI decreased. There was a significant correlation between the forest canopy LAI and aboveground biomass.