Monitoring the Electrochemical Processes in the Lithium–Air Battery by Solid State NMR Spectroscopy
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide A multi-nuclear solid-state NMR approach is employed to investigate the lithium–air battery, to monitor the evolution of the electrochemical products formed during cycling, and to gain insight into processes affecting capacity fading. While lithium peroxide is identified by 17 O solid state NMR (ssNMR) as the predominant product in the first discharge in 1,2-dimethoxyethane (DME) based electrolytes, it reacts with the carbon cathode surface to form carbonate during the charging process. 13 C ssNMR provides evidence for carbonate formation on the surface of the carbon cathode, the carbonate being removed at high charging voltages in the first cycle, but accumulating in later cycles. Small amounts of lithium hydroxide and formate are also detected in discharged cathodes and while the hydroxide formation is reversible, the formate persists and accumulates in the cathode upon further cycling. The results indicate that the rechargeability of the battery is limited by both the electrolyte and the carbon cathode stability. The utility of ssNMR spectroscopy in directly detecting product formation and decomposition within the battery is demonstrated, a necessary step in the assessment of new electrolytes, catalysts, and cathode materials for the development of a viable lithium–oxygen battery.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".