<i>(Battery Division Early Career Award Sponsored by Neware Technology Limited Award)</i> Replacing Inactive Components to Improve Li- and Na-ion Cells
Bibliographic record
Abstract
The ability of lithium- and sodium-ion cells to hold their charge at elevated temperature over extended periods of time is important for a number of applications, e.g., electric vehicles and stationary battery systems for storage of renewable energy deployed in hot climates. We found that LFP and NMC-based lithium-ion cells can experience rapid self-discharge when stored at elevated temperatures, if they do not contain effective electrolyte additives. Cells with LFP positive electrodes show significantly more self-discharge than NMC-based cells. [1-3] Surprisingly, it was found that the rapid self-discharge could be attributed to the in-situ generation of a redox shuttle in commercial LFP and NMC/graphite cells. [1-3] A redox shuttle is a molecule that can diffuse between the positive and negative electrode of a battery and transport electrons from one side to the other through a reversible redox reaction, accepting an electron from the negative electrode and donating it to the positive electrode. This results in lithium ions being transferred from the negative to the positive electrode without charge being drawn from the cell. To fix the self-discharge problem, the origin and formation mechanism of the redox shuttle need to be investigated. First, the reversible and irreversible self-discharge of LFP- and NMC-based cells was quantified with a designated storage protocol. Subsequently, the influence of different formation temperatures on self-discharge was studied. Surprisingly, the visual inspection of the electrolyte extracted from pouch cells after high temperature formation revealed strong discoloration. [1-2] The extracted electrolytes with intense red and brown color showed relatively large shuttling currents in a newly developed Al/Li coin cell setup. [4] Ultra-high precision coulometry was used to detect inefficiencies during cycling, e.g., charge endpoint capacity slippage. [4] Electrolyte additives that effectively passivate the negative electrode, e.g., vinylene carbonate, were effective at preventing the redox shuttle generation as indicated by the absence of electrolyte discoloration, shuttling currents, and charge endpoint capacity slippage. [4] All evidence pointed to a shuttle molecule created at the negative electrode during the formation cycle, i.e., before a passivating solid-electrolyte interface is in place. But what is the shuttle molecule? The identity and formation mechanism of the redox shuttle were investigated by targeted experiments that probe the chemical stability of inactive cell components. We dissected many commercial lithium-ion cells from renowned manufacturers to investigate the composition of the inactive components (see Figure 1). [5] Such inactive components are laminated foils used in pouch cells, gaskets of cylindrical cells, adhesive tapes on the electrodes, separators, and metallized polymer current collectors composed of a thin polymer layer with Al or Cu deposited on both sides. All these components need to be chemically stable, as they could otherwise participate in detrimental side reactions during battery operation. Using gas chromatography and nuclear magnetic resonance spectroscopy, we show that different polymers have vastly different chemical stability against lithium alkoxides that are generated at the unpassivated negative electrode. [5] In the presence of alkoxides some of the polymers decompose into reaction products that can act as redox shuttles. Finally, we will explain how to make Li and Na-ion cells with chemically stable polymer components and demonstrate that self-discharge is virtually eliminated in these cells. [5-7] Figure 1 . A selection of mobile phone batteries that were dissected to find out which inactive components are causing self-discharge. Keywords : Lithium-ion cells, Sodium-ion cells, Self-discharge, Inactive components, Redox shuttles References : [1] T. Boulanger, M. Metzger et al. J. Electrochem. Soc. 169 , 040518 (2022). [2] S. Buechele, M. Metzger et al. J. Electrochem. Soc. 170 , 010511 (2023). [3] S. Buechele, M. Metzger et al. J. Electrochem. Soc. 170 , 010518 (2023). [4] T. Boetticher, M. Metzger et al. J. Electrochem. Soc. 170 , 060507 (2023). [5] A. Adamson, M. Metzger et al. Nature Materials 22 1380–1386 (2023). [6] Z. Ye, = H. Hijazi, = M. Metzger et al. J. Electrochem. Soc. 171 110503 (2024). [7] A. Adamson, M. Metzger et al. J. Electrochem. Soc. 172 010527 (2025). Figure 1
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".