Understanding the Role of Liquid Electrolytes in Performance Improvement of Solid-State Lithium Metal Batteries
Bibliographic record
Abstract
Abstract Garnet-type Li7La3Zr2O12 (LLZO) Solid-State Electrolytes (SSEs) enable Solid-State Lithium Metal Batteries (SSLMBs) with high power density due to their superior ionic conductivity over 1 mS cm-1 at room temperature and good chemical stability against Lithium (Li) metal. A major cause of failure in SSLMBs is the large interfacial resistance between LLZO and electrodes. The high resistance at the interfaces is normally associated with insufficient solid-solid surface contact. It is a common practice to introduce a Liquid Electrolyte (LE) in SSLMBs either in combination with SSEs to form quasi-solid electrolytes or as the interface to enhance battery cycling performance. Several studies are conducted on resolving the contact issue between LLZO and the Li-metal anode but very few focused on the LLZO/cathode interface. In this research, a carbonate-based LE was introduced at the interface of Li6.5La2.9Ba0.1Zr1.4Ta0.6O12 (LLBZTO) | LiNi0.6Mn0.6Co0.2O2 (NMC 622) cathode with the aim of understanding the mechanism which the LE enhances the SSLMBs performance, using the Scanning Transmission X-ray Microscopy (STXM) and X-ray Absorption Scanning (XAS). The assembled Li | LLBZTO SSEs | LE | NMC 622 cell exhibited an initial discharge capacity of 168 mAh g-1 with a capacity retention ratio of ~82 % after 30 cycles. The results from the STXM revealed the reactions of the LE with LLZO and NMC 622. The XAS analysis showed the formation of two new interfaces: Cathode-Electrolyte Interface (CEI) and Solid-Liquid Electrolyte Interface (SLEI). Also, the result indicated that the LE decomposed completely in the cell after 30 cycles and transformed to a dense and robust SLEI. This in turn led to the enhanced interfacial contact with the cathode and an improved Li+ ion transport at the interface. In addition, fluorides (i.e., LiF and LaF3) and carbonates (i.e., Li2CO3) were confirmed as the main components of the SLEI. In this study, two interfaces in SSLMBs (CEI and SLEI) were characterized. Fully understanding the roles of LE as the interface would enhance the practical application of quasi-solid electrolytes in SSLMBs. Keywords Solid-state lithium metal batteries; Garnet; Interface; Ceramic electrolyte; STXM
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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 | 0.001 | 0.001 |
| 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".