Insights into Multiphase Reactions during Self-Discharge of Li-S Batteries
Bibliographic record
Abstract
Lithium-sulfur (Li-S) batteries are promising next-generation rechargeable energy storage systems due to their high energy density and use of abundant and inexpensive materials. However, rapid self-discharge and poor cycling stability due to the solubility of intermediate polysulfide conversion products have slowed their commercialization. Herein, we provide a detailed account of the multiphasic reactions occurring during the self-discharge of a Li-S battery held at various depth of discharge (DOD) through both simulation and experiment. For the first time, self-discharge of a full Li-S battery is simulated using a 1D model to describe reactions at both the anode and cathode. The model accurately describes experimentally derived results obtained over the longest durations of self-discharge studied to date (140 h). This validated model was used to follow the reversible and irreversible capacity loss caused by shuttling and precipitation of insoluble Li2S2 and Li2S as a function of DOD. While the most rapid self-discharge is observed at low DOD, this also leads to the smallest irreversible loss. The results suggest that resting a Li-S battery near 2.1 V minimizes both reversible and irreversible losses.
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".