A Dielectric MXene-Induced Self-Built Electric Field in Polymer Electrolyte Triggering Fast Lithium-Ion Transport and High-Voltage Cycling Stability.
Baolin ZhangYufeng SuYangyang ChenShengguang QiMianrui LiWenwu ZouGuoxing JiangWeifeng ZhangYuqing GaoChenhui PanHuiyu SongZhiming CuiChuanfang John ZhangZhenxing LiangLi DuPublished in: Angewandte Chemie (International ed. in English) (2024)
Quasi-solid polymer electrolyte (QPE) lithium (Li)-metal battery holds significant promise in the application of high-energy-density batteries, yet it suffers from low ionic conductivity and poor oxidation stability. Herein, a novel self-built electric field (SBEF) strategy is proposed to enhance Li + transportation and accelerate the degradation dynamics of carbon-fluorine bond cleavage in LiTFSI by optimizing the termination of MXene. Among them, the SBEF induced by dielectric Nb 4 C 3 F 2 MXene effectively constructs highly conductive LiF-enriched SEI and CEI stable interfaces, moreover, enhances the electrochemical performance of the QPE. The related Li-ion transfer mechanism and dual-reinforced stable interface are thoroughly investigated using ab initio molecular dynamics, COMSOL, XPS depth profiling, and ToF-SIMS. This comprehensive approach results in a high conductivity of 1.34 mS cm -1 , leading to a small polarization of approximately 25 mV for Li//Li symmetric cell after 6000 h. Furthermore, it enables a prolonged cycle life at a high voltage of up to 4.6 V. Overall, this work not only broadens the application of MXene for QPE but also inspires the great potential of the self-built electric field in QPE-based high-voltage batteries.
Keyphrases
- solid state
- ion batteries
- molecular dynamics
- mass spectrometry
- ionic liquid
- single cell
- endothelial cells
- gold nanoparticles
- stem cells
- computed tomography
- risk assessment
- bone marrow
- optical coherence tomography
- density functional theory
- diabetic rats
- hydrogen peroxide
- deep learning
- oxidative stress
- cell therapy
- drug induced
- big data
- high intensity
- climate change
- artificial intelligence