Electrolyte-Phobic Surface for the Next-Generation Nanostructured Battery Electrodes
Bibliographic record
Abstract
Nanostructured electrodes are among the most important candidates for high-capacity battery chemistry. However, the high surface area they possess causes serious issues. First, it would decrease the Coulombic efficiencies. Second, they have significant intakes of liquid electrolytes, which reduce the energy density and increase the battery cost. Third, solid-electrolyte interphase growth is accelerated, affecting the cycling stability. Therefore, the interphase chemistry regarding electrolyte contact is crucial, which was rarely studied. Here, we present a completely new strategy of limiting effective surface area by introducing an "electrolyte-phobic surface". Using this method, the electrolyte intake was limited. The initial Coulombic efficiencies were increased up to ∼88%, compared to ∼60% of the control. The electrolyte-phobic layer of Si particles is also compatible with the binder, stabilizing the electrode for long-term cycling. This study advances the understanding of interphase chemistry, and the introduction of the universal concept of electrolyte-phobicity benefits the next-generation battery designs.
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".