RESUMO
The minimization of irreversible active lithium loss stands as a pivotal concern in rechargeable lithium batteries, particularly in the context of grid-storage applications, where achieving the utmost energy density over prolonged cycling is imperative to meet stringent demands, notably in terms of life cost. Departing from conventional methodologies advocating electrode prelithiation and/or electrolyte additives, a new paradigm is proposed here: the integration of a designer lithium reservoir (DLR) featuring lithium orthosilicate (Li4SiO4) and elemental sulfur. This approach concurrently addresses active lithium consumption through solid electrolyte interphase (SEI) formation and mitigates minor yet continuous parasitic reactions at the electrode/electrolyte interface during extended cycling. The remarkable synergy between the Li-ion conductive Li4SiO4 and the SEI-favorable elemental sulfur enables customizable compensation kinetics for active lithium loss throughout continuous cycling. The introduction of a minute quantity of DLR (3 wt% Li4SiO4@S) yields outstanding cycling stability in a prototype pouch cell (graphite||LiFePO4) with an ampere-hour-level capacity (≈2.3 Ah), demonstrating remarkable capacity retention (≈95%) even after 3000 cycles. This utilization of a DLR is poised to expedite the development of enduring lithium batteries for grid-storage applications and stimulate the design of practical, implantable rechargeable batteries based on related cell chemistries.
RESUMO
In insects, the frequency distribution of the measurements of sclerotized body parts is generally used to classify larval instars and is characterized by a multimodal overlap between instar stages. Nonparametric methods with fixed bandwidths, such as histograms, have significant limitations when used to fit this type of distribution, making it difficult to identify divisions between instars. Fixed bandwidths have also been chosen somewhat subjectively in the past, which is another problem. In this study, we describe an adaptive kernel smoothing method to differentiate instars based on discontinuities in the growth rates of sclerotized insect body parts. From Brooks' rule, we derived a new standard for assessing the quality of instar classification and a bandwidth selector that more accurately reflects the distributed character of specific variables. We used this method to classify the larvae of Austrosimulium tillyardianum (Diptera: Simuliidae) based on five different measurements. Based on head capsule width and head capsule length, the larvae were separated into nine instars. Based on head capsule postoccipital width and mandible length, the larvae were separated into 8 instars and 10 instars, respectively. No reasonable solution was found for antennal segment 3 length. Separation of the larvae into nine instars using head capsule width or head capsule length was most robust and agreed with Crosby's growth rule. By strengthening the distributed character of the separation variable through the use of variable bandwidths, the adaptive kernel smoothing method could identify divisions between instars more effectively and accurately than previous methods.
