Neural Network Inspired Binder Enables Fast Li-Ion Transport and High Stress Adaptation for Si Anode

Autor: Sun, Baoyu, Jiao, Xingxing, Liu, Jiangning, Qiao, Rui, Mao, Caiwang, Zhao, Tuo, Zhou, Shijie, Shi, Kaiyi, Ravivarma, Mahalingam, Shi, Jianjun, Fan, Hao, Song, Jiangxuan
Zdroj: Nano Letters; 20240101, Issue: Preprints
Abstrakt: Extensive investigations have proven the effectiveness of elastic binders in settling the challenge of structural damage posed by volume expansion of high-capacity anode used in nanoscale silicon. However, the sluggish ionic conductivity of polymer binder severely restricts the electrode reactions, making it unsuitable for practical applications. Inspired by the biological tissues with rapid neurotransmission and robust muscles, we propose a biomimetic binder that contains ionic conductive polymer (by polymerization reaction of poly(ethylene glycol) diglycidyl ether and polyethylenimine) and rigid polymer backbone (polyacrylic acid), which can effectively mitigate both Li-ion transport resistance and lithiation stress to stabilize the silicon nanoparticles during cycles. Consequently, the silicon anode with biomimetic binder achieves a rate capability of 1897 mAh g–1at 8.0 A g–1and capacity retention of 87% after 150 cycles under areal capacity upon 3.0 mAh cm–2. These results demonstrate the possibility of decoupling ionic conductivity from mechanical properties toward practical high-capacity anodes for energy-dense batteries.
Databáze: Supplemental Index