Dissolving Vanadium into Titanium Nitride Lattice Framework for Rational Polysulfide Regulation in Li–S Batteries
Bibliographic record
Abstract
Abstract Rational regulation of host–guest interactive chemistry is of great significance but has not yet effectively been applied in lithium–sulfur (Li–S) batteries. Herein, a unique titanium vanadium nitride (TVN) solid solution fabric is developed as an ideal platform for fine structure modulation towards efficient and durable sulfur electrochemistry. The dissolution of V into the TiN lattice framework is shown to subtly tailor the coordinative and electronic structures of Ti and V, tuning their respective chemical affinity to sulfur species. Consequently, the optimized Ti–V interplay renders the highest overall polysulfide adsorpabiltiy, and contributes to strong sulfur immobilization and fast reaction kinetics. The resultant Li–S cells realize an outstanding cyclability with high capacity retention of 97.7% after 400 cycles. Moreover, reversible areal capacity over 6.11 mAh cm−2 can be sustained under a high sulfur loading of 6.0 mg cm−2 and a limited electrolyte concentration of 6.5 mL g−1. This work provides a novel strategic perspective for the rational regulation of fine structure towards superior Li–S batteries and beyond.
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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 | 0.000 | 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) | 0.001 | 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 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".