In-Situ Characterization of Molecular Processes at the Anode/Na<sub>3</sub>SbS<sub>4</sub> Electrolyte Interface in All-Solid-State Sodium Batteries
Bibliographic record
Abstract
Sulfur based solid-state Na+ conductors exhibit high ionic conductivity and are promising candidates for electrolytes used in the next generation all-solid-state sodium-ion batteries. Sodium thioantimonate (Na3SbS4), for example, shows an ionic conductivity of 1 mS/cm, comparable to its liquid counterparts. In contrast to the well-known thiophosphate solid-state electrolytes, Na3SbS4 is chemically stable in dry air. However, solid-state Na-ion batteries assembled using Na3SbS4 as the electrolyte show a decaying performance over the charge and discharge cycles. This work characterized the molecular processes occurring at the interface between Na3SbS4 solid electrolyte and the anode. This interfacial chemistry was probed in real-time (in-situ) using Raman spectroscopy while the battery was in operation. Combined with the characterization results obtained from X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM), we observed a largely irreversible decomposition of SbS4 3- while Na3SbS4 was directly exposed to negative potentials (vs. Na/Na+). Sb2S3 and elemental Sb are the two major decomposition byproducts formed and accumulated at the Na3SbS4/anode interface. This result unravels the decomposition mechanism at the Na3SbS4/anode interface in all-solid sodium batteries. It provides deep molecular insights into designing ideal protective layers at this critical interface.
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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".