(Invited) Understanding Interfacial Reaction of LiCoO2 Positive Electrode in Aqueous Lithium-Ion Batteries
Bibliographic record
Abstract
Since the risk of catch fire using non-aqueous electrolyte solution, aqueous solution-based rechargeable lithium batteries (ARLB) have been highlighted. However, the conventional positive electrodes of lithium transition-metal oxide such as LiCoO2 (LCO) and LiNi1/3Mn1/3Co1/3O2 (NMC) have suffered from poor cyclability in aqueous medium. Representatively, the layered two-dimensional structure of LCO shows notably poor stability, possibly due to the surface degradation from water [1] and proton [2]. The understanding of interfacial reaction of LCO in the aqueous electrolyte solution is still superficial however. Here we present degradation phenomena of LCO electrode in aqueous medium using various X-ray measurement techniques, and suggest the solution to avoid such an irreversible electrochemical reaction. The aqueous solution was prepared with 0.5 M lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) and pH was controlled to ~6.8 and 10. In both cases, there was no evidence for the formation of cathode-electrolyte interphase (CEI) on LCO in contrast to the one with non-aqueous electrolyte solution. The direct contact of aqueous electrolyte solution to LCO surface results in the short-range disorder of LCO structure such as the distortion of octahedral CoO6, and irreversible Li+ desertion during 10 cycles. To improve electrochemical reversibility and structural stability of LCO, we prepared the organic protection layer that opened the Li+ mass transport route while inhibiting H2O contact from hydrophobic surface. As a result, the capacity retention was improved to ~85% during 30 cycles at pH ~ 6.8. Furthermore, we developed the way to protect LCO surface by anion engineering and in the absence of protection layer, which give insight into the inner Helmholtz plane (IHP) structure and its effect for LCO degradation in aqueous medium.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".