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Abstract Lithium-ion batteries (LIBs) have solidified their position as primary energy storage solutions for applications ranging from portable electronics to electric vehicles. As power-intensive applications expand, achieving fast charging/discharging performance is increasingly critical for high-energy-density batteries. However, the increased thickness of electrodes in LIBs presents significant challenges for charge (Li⁺ and electron) transfer kinetics, as longer charge migration distances hinder fast charging and discharging performance. Enormous efforts have been made to summarize advancements in materials chemistry—optimizing ionic pathways and crystal structure—to enhance Li⁺ transfer within the bulk of electrode materials. Yet, materials design and modifications fall short of fully addressing Li⁺and electron transport limitations in thick electrodes. Despite the significance of potentially offering a solution to these constraints, the strategic engineering of electrode architecture has been rarely discussed. In this mini-review, we highlight recent innovations in electrode structural design for fast-charging applications, examining gradient architectures, low-tortuosity structures, and novel current collector designs. By exploring these advanced approaches and offering perspectives on future developments, we aim to promote further advancements toward achieving high-energy-density, fast-charging LIBs. 

Enhanced Zn anode kinetics and reversibility are achieved at a high ZUR by guiding Zn²⁺plating underlying the SnO_1.17interphase with a regulated (101) orientation, surpassing those achieved by inducing Zn(002) plating overlying the interphase. 

This work demonstrates the design protocols for high-energy-density solid-state Li–S batteries (SSLSBs). Also, it highlights the challenging issues for achieving practical SSLSBs towards the application in next-level electric transportation. 

Abstract Advances in whole-genome sequencing (WGS) promise to enable the accurate and comprehensive structural variant (SV) discovery. Dissecting SVs from WGS data presents a substantial number of challenges and a plethora of SV detection methods have been developed. Currently, evidence that investigators can use to select appropriate SV detection tools is lacking. In this article, we have evaluated the performance of SV detection tools on mouse and human WGS data using a comprehensive polymerase chain reaction-confirmed gold standard set of SVs and the genome-in-a-bottle variant set, respectively. In contrast to the previous benchmarking studies, our gold standard dataset included a complete set of SVs allowing us to report both precision and sensitivity rates of the SV detection methods. Our study investigates the ability of the methods to detect deletions, thus providing an optimistic estimate of SV detection performance as the SV detection methods that fail to detect deletions are likely to miss more complex SVs. We found that SV detection tools varied widely in their performance, with several methods providing a good balance between sensitivity and precision. Additionally, we have determined the SV callers best suited for low- and ultralow-pass sequencing data as well as for different deletion length categories.