<i>In Situ</i> Monitoring of Fast Li-Ion Conductor Li<sub>7</sub>P<sub>3</sub>S<sub>11</sub> Crystallization Inside a Hot-Press Setup
Bibliographic record
Abstract
Rechargeable solid-state lithium ion batteries (SSLB) require fast ion conducting solid electrolytes (SEs) to enable high charge and discharge rates. Li 7 P 3 S 11 is a particularly promising lithium solid electrolyte, exhibiting very high room temperature conductivities of up to 17 mS·cm –1 and high ductility, allowing fast ion transport through the bulk and intimate contact to high surface electrodes. Here we present a novel hot-press setup that facilitates the synthesis of solid electrolytes by combining in situ electrochemical impedance spectroscopy (EIS) with simultaneous temperature- and pressure-monitoring. While a high room temperature conductivity in the order of 10 mS·cm –1 is readily achieved for phase pure Li 7 P 3 S 11 with this design, it further enables monitoring of the different steps of crystallization from an amorphous Li 2 S–P 2 S 5 glass to triclinic Li 7 P 3 S 11 . Nucleation, crystallization and—at temperatures exceeding 280 °C—decomposition of the material are analyzed in real time, enabling process optimization. The results are supported ex situ by means of X-ray diffraction, X-ray photoelectron spectroscopy, scanning electron microscopy and Raman spectroscopy. Proof-of-principle experiments show the promising cycling- and rate capability of Li 0.3 In 0.7 /Li 7 P 3 S 11 /S-composite all-solid-state batteries. It is furthermore presented that discharging below a limit of 1.2 V results in decomposition of the SE/cathode 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) | 0.002 | 0.001 |
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".