Efficient Synthesis and Characterization of Robust MoS<sub>2</sub> and S Cathode for Advanced Li–S Battery: Combined Experimental and Theoretical Studies
Bibliographic record
Abstract
Here, we report that in situ MoS 2 and S cathodes (MGC) prepared by simple decomposition of (NH 4 ) 2 MoS 4 facilitate direct formation of Li 2 S and suppress the long-term problem associated with polysulphide shuttling in Li–S batteries. For comparison, we prepared ex situ MoS 2 and S cathodes (EMS) with a similar S/MoS 2 mole ratio to that of in situ-prepared cathodes. Discharge capacity of EMS cathodes dropped by 80% after first few cycles, while assembled MGC cells demonstrated an initial discharge capacity of 1649 mA h/g, achieving close to theoretical capacity of elemental sulfur (1675 mA h/g) at C/3 and a reversible capacity of 1500 mA h/g was obtained in further cycles. The MoS 2 nanostructure evolution after initial discharge helped in extending the cycle life of assembled cells even at a high C rate. Density functional theory (DFT) calculation was performed to understand the structural stability of intermediate MoS 3 and possible electrochemical reactions pertaining to Li + insertion in MoS 2 and S. Based on DFT studies, MoS 3 undergoes stoichiometric decomposition to stable MoS 2 and S. Furthermore, electrochemical analysis confirmed the redox activity of MoS 2 and S at 1.3 and 1.8 V against Li/Li +, respectively.
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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".