Electrochemical Impedance Spectroscopy (EIS) to Diagnose the Effect of Particle Morphology and As a Tool to Model the Aging Process of Li Batteries
Bibliographic record
Abstract
Energy storage technology based on lithium is widely used in the world since their first commercialization in 1990. There are different types of technology depending on the positive electrode (LiCoO2, LiMnO2, LiNiMnCoO2, and LiFePO4) and electrolyte materials. Although being considered as one of the leading technology for mobile and stationary power, Li batteries are not free from aging phenomena which have to be modeled and controlled. Using LiFePO4 as our positive electrode material, diagnostic tools are being developed to study the aging of electrode materials (anode and cathode) for Li and Li – ion coin cells in order to predict their state of life. The lithium iron phosphate (LiFePO4) is a cathode material with low conductivity, but good thermal stability and reversible lithium intercalation processes. The graphitic carbon layer forming around LiFePO4 (LFP), as part of the synthesis process, induces a better conductivity and also improves resistance to aging. By comparing nano-sized and micron-sized materials, particle size also appears to be a parameter of great importance. Through Sol Gel [1] and plasma [2] methods, it was then possible to synthesize respectively micrometer (0.7 μm) and nanometer-sized LiFePO4materials with or without graphitic carbon layer to assess the effect of carbon layers and particle size on the aging process. Temperature, C-rate and the state of charge were chosen as parameters of accelerated aging. Electrochemical impedance spectroscopy (EIS) was our main tool of analysis. It is a rapid and versatile method to monitor charge (charge transfer and electrolyte resistance) and mass transfer parameters (diffusion coefficient) of cells. An equivalent circuit model based on diffusion in spherical coordinates was also developed to interpret the Nyquist diagram obtained at the beginning of cell life [3]. Post-mortem physicochemical analysis of the electrodes (anode and cathode) were carried out with Scanning Electron Microscope (SEM) in order to detect changes in the particle size and shape on the carbon anode, following the formation of the solid electrolyte interface (SEI), and a passivation layer on the LiFePO4 cathode. Energy-Dispersive x-ray spectroscopy (EDX) analysis was also conducted to determine the distribution map of atoms on the surface of pristine and aged electrodes. Data from accelerated aging study will be further used to validate an aging model as a tool to predict the state of life of the lithium and lithium ion batteries. Reference: 1. Peng. W, J. Lifang, Gao. H, Qi. Z, Wang. Q, Du. H, Si. Y, Wang. Y, Yuan. H, Journal of Power Sources, (2011), 196(5), 2841. 2. K. Major, J. Veilleux, and G. Brisard, Journal of Thermal Spray Technology, (2016), 25(1-2), 357. 3. A. Lasia, Electrochemical impedance spectroscopy and its application (2014), p108, Eds. Springer. Acknowledgements The financial supports of Natural Sciences and Engineering Research Council of Canada (NSERC) and Hydro-Quebec are gratefully acknowledged.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".