Ambient-Air Stable Lithiated Anode for Rechargeable Li-Ion Batteries with High Energy Density
Bibliographic record
Abstract
An important requirement of battery anodes is the processing step involving the formation of the solid electrolyte interphase (SEI) in the initial cycle, which consumes a significant portion of active lithium ions. This step is more critical in nanostructured anodes with high specific capacity, such as Si and Sn, due to their high surface area and large volume change. Prelithiation presents a viable approach to address such loss. However, the stability of prelithiation reagents is a big issue due to their low potential and high chemical reactivity toward O 2 and moisture. Very limited amount of prelithiation agents survive in ambient air. In this research, we describe the development of a trilayer structure of active material/polymer/lithium anode, which is stable in ambient air (10–30% relative humidity) for a period that is sufficient to manufacture anode materials. The polymer layer protects lithium against O 2 and moisture, and it is stable in coating active materials. The polymer layer is gradually dissolved in the battery electrolyte, and active materials contact with lithium to form lithiated anode. This trilayer-structure not only renders electrodes stable in ambient air but also leads to uniform lithiation. Moreover, the degree of prelithiation could vary from compensating SEI to fully lithiated anode. With this strategy, we have achieved high initial Coulombic efficiency of 99.7% in graphite anodes, and over 100% in silicon nanoparticles anodes. The cycling performance of lithiated anodes is comparable or better than those not lithiated. We also demonstrate a Li 4 Ti 5 O 12 /lithiated graphite cell with stable cycling performance. The trilayer structure represents a new prelithiation method to enhance performance of Li-ion batteries.
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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".