Direct Evidence of Solution-Mediated Superoxide Transport and Organic Radical Formation in Sodium-Oxygen Batteries
Bibliographic record
Abstract
Advanced large-scale electrochemical energy storage requires cost-effective battery systems with high energy densities. Aprotic sodium-oxygen (Na-O2) batteries offer advantages, being comprised of low-cost elements and possessing much lower charge overpotential and higher reversibility compared to their lithium-oxygen battery cousins. Although such differences have been explained by solution-mediated superoxide transport, the underlying nature of this mechanism is not fully understood. Water has been suggested to solubilize superoxide via formation of hydroperoxyl (HO2), but direct evidence of these HO2 radical species in cells has proven elusive. Here, we use ESR spectroscopy at 210 K to identify and quantify soluble HO2 radicals in the electrolyte-cold-trapped in situ to prolong their lifetime-in a Na-O2 cell. These investigations are coupled to parallel SEM studies that image crystalline sodium superoxide (NaO2) on the carbon cathode. The superoxide radicals were spin-trapped via reaction with 5,5-dimethyl-pyrroline N-oxide at different electrochemical stages, allowing monitoring of their production and consumption during cycling. Our results conclusively demonstrate that transport of superoxide from cathode to electrolyte leads to the nucleation and growth of NaO2, which follows classical mechanisms based on the variation of superoxide content in the electrolyte and its correlation with the crystallization of cubic NaO2. The changes in superoxide content upon charge show that charge proceeds through the reverse solution process. Furthermore, we identify the carbon-centered/oxygen-centered alkyl radicals arising from attack of these solubilized HO2 species on the diglyme solvent. This is the first direct evidence of such species, which are likely responsible for electrolyte degradation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".