Invited Presentation: Addressing Capacity Fading Challenges in Li-S Batteries via Electrolyte/Cathode Design
Bibliographic record
Abstract
The presentation will focus on recent work in our lab involving the development of new electrolytes for the Li-S cell along with new materials for the cathode and developing insightful in situ probes of redox processes for a working cell and understanding the cathode interface. We consider these to be the most challenging issues in electrochemical energy storage cells that operate on the basis of chemical transformations, where the factors that govern capacity and cycling stability are difficult to access owing to the amorphous nature of the intermediate species. I will present results on cathodes for the Li-S cell comprised of sulfur-imbibed robust spherical carbon shells with tailored porosity that exhibit excellent cycling stability. Their highly regular nanoscale dimensions and thin carbon shells allow highly uniform electrochemical response and enable direct monitoring of sulfur speciation within the cell over the whole redox range by operando X-ray absorption spectroscopy on the S K-edge. These studies are coupled with solid state NMR investigations, and include investigations of novel electrolyte systems. Functional tailoring of the surface of the shells will also be presented, and if time permits, comparison will be drawn with Li-O2 electrochemistry.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.006 |
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".