Chalcocarbogels as High-Capacity and Cycle-Stable Electrode Materials for Lithium and Sodium Ion Batteries
Bibliographic record
Abstract
The low capacities of commercial Li ion batteries and cycle instabilities of amorphous metal sulfide based batteries impose constraints on their utilization for large-scale energy storage. We report here the acid-free, room-temperature (RT), and solution-based synthesis of a chalcogenide–carbonaceous hybrid aerogel, termed as “chalcocarbogel”, comprising molybdenum sulfide (MoS x ) and graphene oxide (GO). The chalcocarbogel is a nanoparticle-aggregated, porous, amorphous gel consisting of Mo 3 S 13 and Mo 2 S 12 -like structures as determined by synchrotron X-ray PDF, XANES, and EXAFS. The MoS x -GO chalcocarbogel demonstrates high specific capacities of ∼1215 and ∼807 mAh g –1 for Li/MoS x -GO and Na/MoS x -GO cells, respectively, for a 50 mAg –1 discharge rate during the first cycle. After the activation cycles, the MoS x -GO chalcocarbogel stabilizes, maintaining high specific capacities of approximately ∼700 mAh g –1 for Li/MoS x -GO and ∼473 mAh g –1 for Na/MoS x -GO cells, while continuously cycling. The MoS x -GO aerogel reported here serves as a promising platform to develop chalcocarbogels for applications spanning both Li and Na ion batteries.
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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".