(Invited) Garnet-Based Hybrid Composite Electrolytes for the All-Solid-State Li-S Battery
Bibliographic record
Abstract
Lithium sulfur (Li-S) batteries have emerged as one of the most promising post LIBs technologies with a remarkably high theoretical energy density and abundance of elemental sulfur. Nonetheless, there are many problems associated with lithium sulfur batteries such as safety hazard due to lithium dendrite formation and fast capacity decay due to polysulfide dissolution effect.1 Solid electrolytes are promising to prevent lithium dendrite formation and polysulfide dissolution. Among different ceramic electrolytes garnet-type solid inorganic electrolytes are very promising because of its high ionic conductivity and stability with metallic lithium. But the high interfacial resistance with the electrode is the major bottleneck for the practical use of garnet electrolyte.2 However, polymer-based solid electrolytes possess low interfacial resistance but associated low ionic conductivity at room temperature is the biggest challenge for the utilization in solid-state-batteries.3 Recent research theme of Thangadurai group is mainly focused on garnet-type and polymer-garnet composite electrolytes for the practical utilization in all-solid-state Li batteries. Surface modifications of the garnet-type electrolytes and novel composite electrolytes developed in the laboratory have been successfully employed in all-solid-state-Li-S batteries even at room temperature. Fabrication of these electrolytes in bulk scale, characterizations, electrochemical properties and all-solid-state-Li-S battery performances will be discussed. References: 1. Manthiram, A.; Fu, Y.; Chung, S.; Zu, C.; Su, Y. Chem. Rev. 2014, 114, 11751-11787. 2. Han, X.; Gong, Y.; Fu, K.; He, X.; Hitz, G.; Dai, J.; Pearse, A.; Liu, B.; Wang, H.; Rubloff, G.; Mo, Y.; Thangadurai, V.; Wachsman, E.; Hu, L. Nat. Mater. 2016, 16, 572-579. 3. Zhou, C.; Bag, S.; Thangadurai, V. ACS Energy Lett. 2018, 3, 2181-2198. 4. Bag, S.; Zhou, C.; Kim, P.; Pol, V. G.; Thangadurai, V. Energy Storage Mater. 2019 (doi.org/10.1016/j.ensm.2019.08.019)
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".