Mengxuan Zhou, Zhihong Luo, Jianwei Lu, Tingting Xu, Xiangqun Zhuge, Dingren Zhou, Laijun Liu, Yibing Li, Kun Luo, Xinyu Li, Weiwei Lei, Dan Liu
Uniform deposition is a promising strategy to inhibit dendrite growth and corrosion of the Zn anode in cost-effective energy storage systems: aqueous Zn-ion batteries (AZIBs). Herein, we report a regulating Zn2+ ions dissolution/deposition method for achieving a highly reversible Zn anode. 11-mercaptoundecanoic acid (MUA) as ligands was utilized to protect the (002) plane, benefiting from the strong affinity between the thiol group and Zn, with MUA anchoring in the form of Zn-S-RCOOH, which contributes to a stable interface for uniform deposition/deposition. More importantly, the MUA bonds to the (002) plane tightly and acts as a “rivet,” strengthening the Zn–Zn bonds of the (002) plane and leading to the high exposure of the (002) plane during the plating and stripping process. The MUA@Zn anode with 50 μm ultrathin thickness exhibits excellent stability (over 4000 h) and low overpotential at high current density (0.1–23 mA cm−2) and capacity (0.1–23 mAh cm−2). In addition, it also delivers a capacity of 194.1 mAh g−1 at 1 A g−1 and capacity retention of 95% after 1000 cycles. Consequently, our work provides a facial yet interfacial engineering approach in realizing the enhancement of Zn anode stability, exhibiting significant potential for practical application in AZIBs.
均匀沉积是一种有前途的策略,以抑制枝晶生长和腐蚀的锌阳极的经济高效的储能系统:水锌离子电池(azib)。在此,我们报告了一种调节Zn2+离子溶解/沉积的方法,以实现高度可逆的Zn阳极。利用11-巯基十四烷酸(MUA)作为配体保护(002)平面,利用巯基与Zn之间的强亲和力,MUA以Zn- s - rcooh的形式锚定,为均匀沉积提供了稳定的界面。更重要的是,MUA与(002)平面紧密结合,起到“铆钉”的作用,加强了(002)平面的Zn-Zn键,并导致(002)平面在电镀和剥离过程中的高暴露。在高电流密度(0.1 ~ 23 mA cm−2)和容量(0.1 ~ 23 mAh cm−2)下,厚度为50 μm的MUA@Zn阳极具有优异的稳定性(超过4000 h)和低过电位。此外,它还提供了194.1 mAh g−1的容量在1ag−1和容量保持95%后1000次循环。因此,我们的工作提供了一种表面和界面工程方法来实现锌阳极稳定性的增强,在azib的实际应用中显示出巨大的潜力。
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Understanding and managing charge carrier recombination dynamics is crucial for optimizing the performance of metal halide perovskite optoelectronic devices. In this work, we introduce a machine learning-assisted intensity-modulated two-photon photoluminescence microscopy approach for quantitatively mapping recombination processes in MAPbBr3 perovskite microcrystalline films at micrometer-scale resolution. To enhance model accuracy, a balanced classification sampling strategy was applied during the machine learning optimization stage. The trained regression chain model accurately predicts key physical parameters—exciton generation rate (