Towards a Better Understanding of Aprotic Alkali-Oxygen Batteries
Bibliographic record
Abstract
In the search for high density electrochemical energy storage, non-aqueous rechargeable metal-O2 batteries are very attractive owing to their reliance on molecular oxygen, which forms oxides on discharge that release oxygen reversibly on charge. Much work has focused on aprotic Li–O2 cells, but the aprotic Na-O2 system is of equal interest owing to its more reversible chemistry. In both cells, a chemically stable and conductive cathode interface is prerequisite for sustainable cell operation, along with a non-aqueous electrolyte that minimizes parasitic reactions at the electrode/electrolyte interface. Li-O2 cells (unlike their sodium counterparts), are also characterized by a high charge overpotential that must be overcome in order to increase round-trip efficiency. In the last year, much progress has been made towards achieving these goals owing to a better understanding of the cell chemistries. This presentation will focus on those topics, covering developments from our lab that include non-carbonaceous cathode hosts that possess stable conductive interfaces for reduced polarization on O2 evolution, and novel soluble oxidation catalysts capable of Li2O2 oxidation without direct electrical contact with the cathode. Characterization techniques ranging from electron microscopy, surface spectroscopy and operando electrochemical mass spectrometry have been applied to investigate the viability of various proposed systems. This has resulted a deeper understanding of the critical parameters for positive electrodes in aprotic A-O2 batteries, which will be presented in this talk.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".