Recently, a research paper entitled "A Gradient Lithiophilic Structure for Stable Lithium Metal Anodes with Ultrahigh Rate and Ultradeep Capacity" was published in the renowned journal Small by Professor Liu Fude's research group at the Institute for Advanced Study, Shenzhen University. This journal holds a high Impact Factor of 13.3 and is considered among the top journals by the Chinese Academy of Sciences. The first author of this paper is Peng Gangqiang, a year 2019 undergraduate student at the Institute. Professor Liu Fude, the corresponding author of the paper, represents the Institute for Advanced Study of Shenzhen University as its first affiliation.

Figure 1.Graphical abstract of the paper.

Using three-dimensional current collectors (3DCC) as frameworks for lithium metal anodes (LMAs) is a promising approach to inhibit dendrite growth. However, the intrinsically accumulated current density on the top surface and limited Li-ion transfer in the interior of 3DCC still lead to the formation of lithium dendrites, which can pose safety risks. In this study, we report that gradient lithiophilic structures can induce uniform lithium deposition within the interior of the 3DCC, greatly suppressing dendrite formation, as confirmed by COMSOL simulations and experimental results. With this concept, we synthesize a gradient-structured zinc oxide-loaded copper foam (GSZO-CF) via an easy solution-combustion method at low cost. The resulting Li@GSZO-CF symmetric cells demonstrate stable cycling performance for over 800 cycles, with an ultra-deep capacity of 10 mAh cm-2 even under an ultra-high current density of 50 mA cm-2, the top results reported in the literature. Moreover, when combined with a LiFePO4 (LFP) cathode under a low negative/positive (N/P) capacity ratio of 2.9, the Li@GSZO-CF||LFP full cells exhibit stable performance for 200 cycles, with a discharge capacity of 130 mAh g-1 and retention of 85.5% at a charging/discharging rate of 1C. These findings suggest a promising strategy for the development of new-generation LMAs.

The work was supported by the Peacock Plan Research Fund [Project Code 000580] and Startup Fund for Distinguished Professorship [Project Code 0000021259].

Link to this paper: https://onlinelibrary.wiley.com/doi/10.1002/smll.202303787