Revealing the Neglected Role of Passivation Layers of Current Collectors for Solid‐State Anode‐Free Batteries
Bibliographic record
Abstract
Abstract Anode‐free sulfide‐based all‐solid‐state lithium metal batteries (ASSLMBs), which eliminate the need for a lithium metal anode during fabrication, offer superior energy density, enhanced safety, and simplified manufacturing. Their performance is largely influenced by the interfacial properties of the current collectors. Although previous studies have investigated the degradation of sulfide electrolytes on commonly used copper (Cu) and stainless steel (SS) current collectors, the impact of spontaneously formed surface oxides, such as copper oxide (Cu 2 O/CuO) and chromium oxide (Cr 2 O 3 ), on interfacial stability remains underexplored. This study systematically evaluates the neglected role of passivation layers of both Cu and SS. Results demonstrate that Cu facilitates more stable lithium deposition. Electrochemical impedance spectroscopy (EIS) reveals that interfacial resistance on SS is consistently higher than on Cu during cycling. In‐situ X‐ray absorption spectroscopy (XAS) and computational modelling confirm the formation of phosphate (PO 4 3− ) and sulfate (SO 4 2− ) species at both interfaces, attributed to reactions between the sulfide electrolyte and surface oxides. On SS, partial reversible formation of transition metal chlorides is also detected. Based on these findings, an artificial interface is engineered on Cu, significantly improving lithium plating/stripping efficiency. These insights contribute to solid‐solid interface engineering strategies and advance the fundamental understanding of anode‐free ASSLMBs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".