电化学
锂(药物)
材料科学
阴极
氧化物
纳米技术
无机化学
化学
电极
物理化学
冶金
医学
内分泌学
作者
Zichang Zhang,Peng‐Hu Du,Jiahui Liu,Dingguo Xia,Qiang Sun
出处
期刊:ACS Nano
[American Chemical Society]
日期:2025-02-06
卷期号:19 (6): 6554-6562
被引量:10
标识
DOI:10.1021/acsnano.4c17907
摘要
LiCoO 2 has been one of the dominant cathode materials commercially used in rechargeable lithium-ion batteries, while the performance is severely limited by its low reversible capacity (∼140 mAh/g), primarily due to the destructive phase transitions at high voltages (>4.2 V vs Li/Li + ), leading to structural degradation and rapid decay of capacity. A recent experimental study [Wang et al. Nature 2024, 629, 341] showed that chemical short-range disorder (CSRD) in LiCoO 2 can effectively prevent phase transitions and structural deterioration. To better understand the underlying mechanisms, we carry out a theoretical study on CSRD-based LiCoO 2 by performing ab initio molecular dynamics simulations accelerated by machine learning and find that CSRD effectively suppresses phase transitions from hexagonal to monoclinic at Li 0.5 CoO 2 and from O3 to H1–3 at Li 0.25 CoO 2 . The enhanced phase stability is attributed to the reduced lattice variation in the c -axis, the increased oxygen vacancy formation energies, the higher oxygen dimer formation energies, and the stabilization of Co atoms in the Li layers during delithiation. The high Li + diffusion coefficients are found to arise from the low-barrier 0-TM diffusion channels and an expanded diffusion network from 2D to quasi-3D induced by CSRD. Furthermore, CSRD narrows the band gap of LiCoO 2 with enhanced electronic conductivity, driven by the changes in the Co valence state and the introduction of linear Li–O–Li configurations. Equally important, CSRD can also enhance the stability of Li-rich cathode Li 1.2 Co 0.8 O 2 for high capacity and excellent cycling performance. This work provides theoretical insights into the effects of CSRD on LiCoO 2 and Li-rich cathodes for rational design and synthesis.
科研通智能强力驱动
Strongly Powered by AbleSci AI