Insight into MoS<sub>2</sub>–MoN Heterostructure to Accelerate Polysulfide Conversion toward High‐Energy‐Density Lithium–Sulfur Batteries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Lithium–sulfur batteries are deemed as optimal energy devices for the next generation of high‐energy‐density energy storage. However, several problems such as low energy density and short cycle life hinder their application in industry. Here, MoS 2 –MoN heterostructure nanosheets grown on carbon nanotube arrays as free‐standing cathodes are reported. In this heterostructure, MoN works as a promoter to provide coupled electrons to accelerate the redox reaction of polysulfides while the MoS 2, with a two‐dimensional layered structure, provides smooth Li + diffusion pathways. Through their respective advantages, both MoN and MoS 2 could mutually boost the process of “adsorption‐diffusion‐conversion” of polysulfides, which have a synergy enhancement effect to restrain the lithium polysulfides from shuttling. The designed cathodes show excellent long‐term cycling performances of 1000 cycles at 1C with a low decay rate of 0.039% per cycle and a high rate capability up to 6C. A high initial areal capacity of 13.3 mAh cm −2 is also achieved under a low electrolyte volume/sulfur loading (E/S) ratio of 6.3 mL g −1 . This strategy of promoting polysulfide conversion by heterostructure MoS 2 –MoN as presented in this work can provide a more structured design strategy for future advanced Li–S energy storage systems.
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.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 it