Zhaojie Liang
Research Subjects
Research Interests
Zhaojie Liang has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Bo Rao
Guangdong Provincial Key Laboratory of Source-Grid-Load-Storage Interactive Collaborative Technology, Shenzhen Power Supply Co., Ltd., Shenzhen 518000, China
1 shared publication - Jie Tian
Guangdong Provincial Key Laboratory of Source-Grid-Load-Storage Interactive Collaborative Technology (No. 2024B1212020004), Shenzhen Power Supply Co., Ltd., Shenzhen 518000, China
1 shared publication - Jinqiao Du
Guangdong Provincial Key Laboratory of Source-Grid-Load-Storage Interactive Collaborative Technology (No. 2024B1212020004), Shenzhen Power Supply Co., Ltd., Shenzhen 518000, China
1 shared publication - Jiuchun Jiang
Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen 518118, China
1 shared publication - Tengteng Li
Guangdong Provincial Key Laboratory of Source-Grid-Load-Storage Interactive Collaborative Technology (No. 2024B1212020004), Shenzhen Power Supply Co., Ltd., Shenzhen 518000, China
1 shared publication - Xiner Luo
Guangdong Provincial Key Laboratory of Source-Grid-Load-Storage Interactive Collaborative Technology (No. 2024B1212020004), Shenzhen Power Supply Co., Ltd., Shenzhen 518000, China
1 shared publication
Latest Publications
- Open Access
Design and Optimization of Failure Diagnosis Processes for Capacity Degradation of Lithium Iron Phosphate
Lithium iron phosphate (LiFePO4, LFP) batteries dominate grid-scale energy storage, yet their cycle life is capped by its capacity fade issues. Conventional failure workflows suffer from redundant tests, high cost, and long turnaround time because the underlying mechanisms remain unclear. Herein, multi-scale characterization coupled with electrochemical tests have been quantitatively established to reveal four synergistic fade modes of LFP: active-Li loss, FePO4 secondary-phase formation, SEI rupture, and particle fracture. A two-tier “screen–validate” protocol is proposed to accurately and efficiently disclose its mechanism. In the screening tier, capacity, cyclic voltammetry, electrochemical impedance spectroscopy, low-magnification scanning electron microscopy, and snapshot X-ray diffraction (XRD) rapidly flag the most probable failure cause. The validation tier then deploys mechanism-matched in situ/ex situ tools (operando XRD, TEM, XPS, ToF-SIMS, etc.) to build a comprehensive evidence chain of dynamic structural evolution, materials loss tracking, and quantitative proof. The streamlined workflow preserves scientific rigor and reproducibility while cutting analysis time and cost, offering a closed-loop route for fast failure diagnosis and targeted optimization of next-generation LFP batteries.
Open AccessDesign and Optimization of Failure Diagnosis Processes for Capacity Degradation of Lithium Iron Phosphate
Lithium iron phosphate (LiFePO4, LFP) batteries dominate grid-scale energy storage, yet their cycle life is capped by its capacity fade issues. Conventional failure workflows suffer from redundant tests, high cost, and long turnaround time because the underlying mechanisms remain unclear. Herein, multi-scale characterization coupled with electrochemical tests have been quantitatively established to reveal four synergistic fade modes of LFP: active-Li loss, FePO4 secondary-phase formation, SEI rupture, and particle fracture. A two-tier “screen–validate” protocol is proposed to accurately and efficiently disclose its mechanism. In the screening tier, capacity, cyclic voltammetry, electrochemical impedance spectroscopy, low-magnification scanning electron microscopy, and snapshot X-ray diffraction (XRD) rapidly flag the most probable failure cause. The validation tier then deploys mechanism-matched in situ/ex situ tools (operando XRD, TEM, XPS, ToF-SIMS, etc.) to build a comprehensive evidence chain of dynamic structural evolution, materials loss tracking, and quantitative proof. The streamlined workflow preserves scientific rigor and reproducibility while cutting analysis time and cost, offering a closed-loop route for fast failure diagnosis and targeted optimization of next-generation LFP batteries.