<p>Aqueous zinc-ion batteries offer inherent safety and low cost, yet performance is limited by unstable zinc metal negative electrodes and dissolution-prone positive electrodes, causing dendrite growth, sluggish ion transport, and rapid capacity decay. Replacing both electrodes with intercalation hosts provides a solution, but progress is slowed by the lack of a universal principle for selecting kinetically compatible pairs. Most existing efforts optimize single components rather than addressing the electrodes’ kinetic mismatch governing full-cell stability. Here we show a machine-learning-assisted kinetic-matching framework that quantitatively evaluates ion-transport compatibility in intercalation-type zinc-ion batteries electrodes. By correlating interlayer spacing with Zn<sup>2+</sup> diffusion behavior, the model introduces two descriptors predicting synchronized ion flux for rational electrode pairing. Using this framework, an optimized Zn<sub>3</sub>V<sub>3</sub>O<sub>8</sub> | |NH<sub>4</sub>V<sub>4</sub>O<sub>10</sub> system achieves a specific capacity of 310 mAh g<sup>-1</sup> and retains over 12,000 cycles at 5 A g<sup>-1</sup>. The strategy further extends to deformable formats through conductive hydrogel architectures, enabling omnidirectionally stretchable, all-hydrogel zinc-ion batteries with an areal capacity of 1.2 mAh cm<sup>-2</sup> and an energy density of 1070 μWh cm<sup>-2</sup>. These results provide a quantitative design route for next-generation zinc-ion batteries.</p>

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Machine learning-assisted kinetic matching model for rational electrode design in aqueous zinc-ion batteries

  • Qian Xie,
  • Yurong You,
  • Dingshuo Qiao,
  • Huan Xia,
  • Hanning Zhang,
  • Song-Zhu Kure-Chu,
  • Tomasz Wejrzanowski,
  • Tao Shui,
  • Wei Zhang,
  • ZhengMing Sun

摘要

Aqueous zinc-ion batteries offer inherent safety and low cost, yet performance is limited by unstable zinc metal negative electrodes and dissolution-prone positive electrodes, causing dendrite growth, sluggish ion transport, and rapid capacity decay. Replacing both electrodes with intercalation hosts provides a solution, but progress is slowed by the lack of a universal principle for selecting kinetically compatible pairs. Most existing efforts optimize single components rather than addressing the electrodes’ kinetic mismatch governing full-cell stability. Here we show a machine-learning-assisted kinetic-matching framework that quantitatively evaluates ion-transport compatibility in intercalation-type zinc-ion batteries electrodes. By correlating interlayer spacing with Zn2+ diffusion behavior, the model introduces two descriptors predicting synchronized ion flux for rational electrode pairing. Using this framework, an optimized Zn3V3O8 | |NH4V4O10 system achieves a specific capacity of 310 mAh g-1 and retains over 12,000 cycles at 5 A g-1. The strategy further extends to deformable formats through conductive hydrogel architectures, enabling omnidirectionally stretchable, all-hydrogel zinc-ion batteries with an areal capacity of 1.2 mAh cm-2 and an energy density of 1070 μWh cm-2. These results provide a quantitative design route for next-generation zinc-ion batteries.